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NOVEMBER-DECEMBER 2023 » VOLUME 13 » ISSUE 05 | ISSN 2277—3134
MILESTONE FUTURE MOBILITY The convergence of location intelligence, sensors, and space data, along with the power of HD maps and precise analytics, is transforming the mobility landscape. Over the Cloud: The Next Tech Revolution / p 08 At the Vanguard: 4D Imaging Radar and Next-Gen Mobility / p 12 Steering the Future / p 16
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CONTENTS ON THE COVER
At the Vanguard: 4D Imaging Radar and Next-Gen Mobility
VOLUME: 13 / ISSUE: 05 Editor-in-Chief Sanjay Kumar
Managing Editor
Prof. Arup Dasgupta
Steering the Future
Contributing Editors Geospatial Infrastructure John Kedar Global Defense and Security Keith J. Masback
Vice President - Media Ajit Tiwari
Deputy Executive Editor Aditya Chaturvedi
Associate Editors
P12
P16
IN-FOCUS
INTERVIEWS
22 / Modernizing Railway Infra
08 / Over the Cloud:
The Next Tech Revolution
Maj. Gen (Retd.) Clint Crosier
44 / Predictive Fleet Maintenance: Harmonizing Viability with Sustainability
INFOSPHERE
06 / Evolving Drone Delivery Landscape
SPECIAL FEATURE
30 / LiDAR Data Quandary: Then and Now
Director of Aerospace & Satellite Amazon Web Services
20 / Geolocation:
The Golden Thread in Logistics
Cornelia Raportaru CEO, Stuart
26 / Pivot to Smart Mobility Via Space
Sub Editors
Sachin Awana Jeffy Jacob
Chief Designer Subhash Kumar
Visualizers
Pradeep Chauhan Saurabh Srivastava
Circulation
Shweta Singh
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CITY SPOTLIGHT
04 / Editorial
Nibedita Mohanta
39 / Predictive Intelligence
Managing Director, Bayanat
REGULAR
Assistant Editor
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CEO and Co-Founder Array Labs
Hasan Al Hosani
Projects to Watch Out
Asia Pacific Sarah Hisham
Andrew Peterson
for a More Sustainable World
34 / Innovative Smart Mobility
Europe Meenal Dhande
CASE STUDY
33 / LightBox Provides Data for Alabama’s Cadastral Maps
42/ Bridge with BIM
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EDITORIAL
A New Turning Point
T
he term ‘mobility’ conjures up many images, but at the root of them all is the need for the most optimum way to navigate from point A to point B. It may be on foot, or via a private vehicle, or a mass transport system. It could also be by road or rail, encompassing commuters as well as cargo. The key to mobility is ease, efficiency, safety, time, and cost constraints.
Prof. Arup Dasgupta arup@geospatialworld.net
Maps and location, the two prerequisites for mobility today, are already available through GNSS-based apps and digital mapping services. The basic location information from GNSS such as the GPS are further refined realtime with the help of Satellite Based Augmentation Systems like US WAAS and Indian’s GAGAN to yield position accuracies of a metre or better. While the SBAS is mainly for aircraft navigation, it is increasingly finding use in on-ground mission critical applications such as ambulance routing as well. Maps have always been static objects and pose a problem for enhancing mobility. One of the drawback is that they are dated and do not cover new developments. Further, episodic events such as traffic jams, down time for maintenance, and disaster-led disruptions are not covered. Crowd sourcing has been the only possible remedy for such situations. This is where the concept of High Definition (HD) maps is becoming very useful. HD maps are one of the tools for realizing Digital Twins for Cities. In the context of mobility, HD maps provide centimetre level accuracy, which combined with SBAS can provide
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guidance at the traffic level. Autonomous vehicles have begun to use HD Maps as their basic data and by adding real-time feedback from their onboard sensors can provide the necessary dynamic map information which is a step beyond simple crowdsourcing. While these systems are presently available only on high-end automobiles, they do present a picture of upcoming mobility. Simple GNSSbased location devices in car navigation systems that use an augmented positioning method with about 10 metre accuracy will be replaced by SBAS enabled systems enabling under one-metre accuracy. HD maps will replace comparatively lower resolution maps, and ensure that maps get updated near real-time, if not real-time. Given the dire need to curtail emissions and combat climate change, the way people commute will undergo a shift towards integrated, multi-modal mass transit systems. Going forward, these will become the preferred mode of mobility, with the higher cost of autonomous vehicles distributed over the large number of passengers. Autonomous trains are already in operation at major airports, connecting terminals to the passenger check-in areas. Autonomous buses, trains, trams and trolley buses will form the backbone of integrated mass transit systems. Future mobility will need out-ofthe-box designs. Will there be fructification of technologies such as the Hyperloop promoted by Elon Musk? Or will we take to the air on flying cars and drones?
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INFOSPHERE
EVOLVING DRONE DELIVERY LANDSCAPE
The global drone delivery landscape is rapidly evolving, with companies such as Amazon, Walmart, Zipline, DJI, and Matternet all playing a key role. It is also driven by a combination of factors, including technological advancements with drones having a longer battery life, increased payload capacity, and improved autonomous capabilities. Governments around the world are coming up with regulations to enable safe and efficient drone operations. Consumers and businesses are also increasingly interested in drone delivery, as it offers the potential for faster, more convenient, and affordable deliveries. As per estimates, is expected to reach $1.97 billion in 2023 and grow at a CAGR of 42.65% to reach $11.66 billion by 2028.
AMAZON On Christmas Day in 2013, Jeff Bezos promised drone deliveries at scale. Amazon is preparing to expand the program beyond the US for the first time, having announced plans to launch in the UK and Italy by the end of next year. Amazon unveiled the MK30, its next-generation delivery drone, in November 2022.
Amazon's Prime Air drones are able to fly up to 15 miles at speeds of up to 60 miles per hour. Prime Air launched in two cities in the United States in 2022: Lockeford, California, and College Station, Texas. Amazon to start drone delivery service in Italy and UK by 2024 They can carry packages weighing up to 5 pounds.
WALMART Walmart completed over 6,000 drone deliveries in 2022. The company currently operates 36 drone delivery hubs across seven states in the US, including Arizona, Arkansas, Florida, North Carolina, Texas, Utah, and Virginia. Walmart's drone delivery partners can deliver
6 | www.geospatialworld.net | November-December 2023
packages up to 6 miles away from their hubs. Drone deliveries typically take less than 30 minutes to complete. Customers can order a wide variety of items for drone delivery, including groceries, household essentials, and even fragile items like eggs.
ZIPLINE Delivers medical supplies to remote and underserved communities. Has been operating drone delivery programs in Rwanda, Ghana, and United States. In 2023, Zipline announced that it would be expanding its drone delivery program to Nigeria. Zipline has flown over 40 million miles autonomously.
Zipline's drone delivery service has delivered over 30 million medical products to over 2 million people. Zipline's drone delivery service has reduced the time it takes to deliver essential medical supplies to remote and underserved communities from days or weeks to minutes. Drone delivery service is 7x faster than traditional automobile deliveries.
DJI (DA-JIANG INNOVATIONS) DJI, the world's leading drone manufacturer, officially entered the drone delivery market in 2022 with the launch of its FlyCart 30 delivery drone. Supports two kinds of payload mode: Cargo/container and crane/winch. In 2022, DJI conducted a pilot project in China to deliver packages to customers using the FlyCart 30. The project was successful. In 2023, DJI announced a partnership with the Rwandan government to deliver medical supplies to remote hospitals and clinics using the FlyCart 30. DJI is also working with e-commerce giant JD.com and the logistics company DHL, to deploy drone delivery services using the FlyCart 30.
MATTERNET Has enabled over 20,000 commercial drone flights to date Focused on delivering medical supplies and other essential goods to urban areas. Operational in Switzerland, the United States, and other countries.
Launched the world's longest urban drone delivery route and receiving FAA Production Certification for its M2 drone delivery system. Expanding its partnership with UPS to launch new drone delivery services in the United States.
Partnering with Labor Berlin, a medical laboratory in Germany, to deliver diagnostic samples by drone. Exploring other applications in e-commerce and logistics.
November-December 2023 | www.geospatialworld.net | 7
INTERVIEW
Over the Cloud
The Next Tech Revolution In an exclusive interview, Maj. Gen (Retd.) Clint Crosier, Director of Aerospace & Satellite, Amazon Web Services (AWS) shares insights on the ongoing shift towards cloud, era of AI & ML, on-board processing, in-orbit computing sustainability initiatives on Earth as well space, and more. “What mechanized manufacturing proved to be for the industrial revolution, Cloud will be to the digital revolution. Companies, organizations, and governments that don't take advantage of the advanced technology available with the cloud simply won't stay competitive or relevant over time”, says Clint Crosier. New space ecosystem today is evolving at an exponential pace, especially with trends such as sensor miniaturization, faster analytics, rapid connectivity, IoT and extensive downstream capabilities. Where do you think is the sector headed and what would be the role of geospatial in it? The reason we have rapid connectivity and faster analytics is because of high performance computing, Artificial Intelligence, Machine Learning, and global cloud infrastructure. All of these are very much connected. Coming to future trends, there are a few things. First and foremost, we see a continued movement of space and geospatial organizations and companies to the cloud. 8 | www.geospatialworld.net | November-December 2023
Three years ago, I would hear from companies that they don’t really know what value the cloud provides. And then, within a year they recognized the value that it offers. Now the sentiment has shifted towards swiftly moving to the cloud. This is going to continue. Interconnectivity is the other trend. The history of space in the realm of geospatial has been that satellites only communicated with one ground station. Satellites in Geo orbit didn't communicate with satellites in LEO (lower Earth orbit). This led to a stovepipe set of capabilities. Now, increasingly users, such as those who travel around the world, don’t really care which network they are on, or which system. They just want everything up & running and functioning. Same is the case with space. AWS is working with companies to create the connectivity layer to enable IoT on earth. AI has proven to be extremely valuable, and Generative AI built on top of it will lead to an exponential leap. There are immense possibilities for using Gen AI, whether it is new concepts for spacecrafts and rocket design, or coming up with faster ways to train large language models on geospatial data to identify things that the human eye can't pick up. Going forward, these would be some of the key industry trends, and cloud plays a big role in all of these.
What I love about AWS Ground Station is that it is basically built on the fundamental premise of the cloud. Instead of spending your limited funding and your limited capital on building out infrastructure, use that instead on your actual mission and let AWS provide you global infrastructure. That's the basic premise of the cloud. When you've got a small company that's guarding their limited resources preciously, they don't want to have to build the infrastructure of a ground station network instead. So customers can take advantage of the AWS Ground Station pay as you go model, pay only for what they use, and then instead of that large capital outlay, you can put that back in the exquisite nature of your sensor or your data distribution capability. And so that's the value of Ground Station as a service.
What is the AWS vision for a more sustainable world ahead? AWS and Amazon are absolutely committed to sustainability. Through the Amazon Climate Pledge, we support climate and sustainability. When we look at AWS
and we look at space and geospatial, I think there's two interesting things. The use of space to support sustainability Earth is the first. There are companies such as Orbital Sidekick who use geospatial data and AWS to monitor oil and gas pipelines around the world to detect and monitor any emissions from leaks or damage, especially methane gas exposure. This is an important focus for the energy industry.. In India, there’s a company called SatSure that uses Earth Observation data and Amazon SageMaker to help farmers identify changing conditions . In the UK, we work with a company called SatelliteVu that uses geospatial data to identify thermal emissions from manmade structures. Digital Earth Africa uses artificial intelligence and machine learning on geospatial data to improve food security and agriculture production in underrepresented regions of the world. They tell us that with the help of AWS Cloud, their analysis predictions get up to 800% faster. Space geospatial and cloud capabilities are together enhancing sustainability of Earth.
AWS has been a pioneer in this new paradigm of Ground station as a service. How do you see it as beneficial to startups, especially in the emerging markets? November-December 2023 | www.geospatialworld.net | 9
INTERVIEW
In terms of secure communications and capability, one of the things that I am really proud of with AWS is security – its number one in everything that we do. There's no other cloud organization in the world with the size and scope of what we can commit in terms of global resources and expertise. We are going to continue to see satellite communications move to the cloud for virtualization to take advantage of the built-in security on the AWS network.
There’s a need to ensure that we keep the space sustainable by not polluting the orbit with unnecessary debris. For this, we work with companies such as LeoLabs that have built their entire space traffic management and space collision avoidance capability on AWS to provide real-time monitoring of objects in orbit. We are also working with companies such as Astroscale in Japan who use AWS to identify ways to keep satellites in orbit longer, and being able to maneuver them when they run out of life to avoid the possibilities of debris. Active debris mitigation capabilities are crucial for space sustainability.
Earth Observation and Satellite Communications are the two biggest markets in the New Space economy. Do you think, going forward with plethora of space data on the Cloud, there would cloud be a constant need for the future of secure and encrypted communications everywhere?
The biggest telecom organizations around the world virtualize their networks on AWS to boost innovation, reduce costs, and to improve resiliency and redundancy. This is already happening with terrestrial communications. The same trend would continue as we move towards satellite communications. Last year, Thaicom, one of the largest Satcom providers in Asia, announced they are working with AWS to develop its cloud-based TV broadcast distribution platform. They are virtualizing their network software-defined capabilities so they can increase innovation, decrease cost, and increase resiliency of their customer base and network architecture. Earlier this year, we signed an agreement with Eutelsat OneWeb. Eutelsat OneWeb is going to move their mission operation centers to a virtual cloud-based network, and we're collaborating to improve delivery of satellite communications capability and cloud edge computing edge services.
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It is often said that data is the new oil. While that may or may not be the case, but it certainly is an invaluable asset for space-based applications, systems and solutions. With petabytes of data on the Cloud, what would be the role of AI and ML in the future of analytics? We have seen that AI and Cloud go hand-in-hand and grow together. The two are inextricably linked. AI and ML gets more powerful due to Cloud and vice-versa. So I think you're going to see those continue to grow together. When we look at space and geospatial, a lot of studies point out that there would be five to ten times more satellites in orbit over the next decade. This would also lead to an almost infinite increase in data and bandwidth that's coming down. Only way to make sense of that data is via AI, ML, and advanced data analytics. The idea is to take that data, turn it into information, and convert that information into knowledge, allowing us to make real-time decisions.
Cloud, AI, ML, and advanced allow us to turn raw data into quality insights that decision-makers and civilian and military leaders around the globe can use to make decisions that affect people's lives. started conducting experiments processing images from onboard scientific experiments.
Timing would be equally critical. We can't afford to wait for say a week a day, or even an hour to process that data. Cloud, AI, ML, and advanced allow us to turn raw data into quality insights that decision-makers and civilian and military leaders around the globe can use to make decisions that affect people's lives.
before. The increased processing speed helps NASA JPL make faster decisions on the health and safety of the rover and prepare for the next day’s activities.
We see in-orbit processing, edge computing, and the scramble towards quantum communications. What would be their impact in the coming years, and how do they align with the AWS future roadmap? They align very well. Over the last decade, we have been working on extending the cloud coverage. The basic vision of AWS is that we would bring the cloud to your data or applications, rather than other way around.
We will also be into satellite servicing and space robotics. If we look at the Artemis Accords that aims to put a man back on the moon, and also the first woman, along with creating a lunar infrastructure and cislunar economy.
And that's essentially the birth of edge computing. We want to help customers reduce latency, increase efficiency, and provide the cloud when and where they need it most. That's the key. Our customers have missions spanning space, aerospace, and geospatial. For instance, when we talk about missions such as the NASA Perseverance Rover, it spans a 300 million mile journey and processes hundreds of images from Mars each day. By using AWS, NASA Jet Propulsion Laboratory (JPL) is able to process this data faster than ever
For the growing missions in the LEO economy, we will be building satellites and launching them in space.
For all of this, we cannot afford to push all that data to the earth, process it in the terrestrial cloud and then push it back into space. There is need to move the cloud where our customers need it and they would be requiring it in space. We did two interesting things over the past two years. One of them is on-orbit testing using a AWS Snowcone, an edge computing device that does ML and computation. It’s designed to be rugged and lightweight. The device underwent a sevenmonth NASA space flight certification, process shock testing, vibration testing, the whole nine yards. After that it got certified for launch on a rocket to the International Space Station (ISS). Once it was installed on the ISS, AWS and Axiom Space
Together, we tested how the device allows us to process data on the space station, instead of pushing all that data through limited bandwidth, limited pipes back to the earth. As a result, we saw significant increase in the ability to do on-orbit experimentation, science, research and development more quickly and efficiently. Next we built our own purposebuilt hardware software package, and we partnered with industry partners D-Orbit, and Unibap to conduct a software experiment on an orbiting satellite. When pushing satellite data to the Earth and processing it, inevitably some of the images are unusable because of cloud cover, or the images aren’t the required ones. By pre-processing images onboard the satellite instead, we discovered it’s possible to eliminate downlinking that unusable data. We found out that 100% of mission could be met with 42% less bandwidth for the downlink. That again increases the efficiency of what satellites can do, allowing customers to fetch more data, which again needs more cloudbased AI and ML. This space data processing cycle, is an important one that relies on the cloud. Interviewed by Aditya Chaturvedi
November-December 2023 | www.geospatialworld.net | 11
ON THE COVER
At the Vanguard
4D Imaging Radar and Next-Gen Mobility Overcoming some of the conventional limitations of LiDAR, 4D Radars will play a big role in the transition to future mobility. By Jae-Eun Lee, CEO of bitsensing
We may produce at will, from a sending station, an electrical effect in any particular region of the globe; we may determine the relative position or course of a moving object, such as a vessel at sea, the distance traversed by the same, or its speed. ~ Nikola Tesla, 1900 ~
T
he famed inventor wrote these prophetic words more than hundred years back in an article titled The Problem of Increasing Human Energy, published in Century Illustrated
Monthly Magazine. This statement effectively predicted the advent of radar, a technology already undergoing extensive experimentation in the late nineteenth century by German physicist Heinrich Hertz.
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The first practical radar system was finally invented in 1935 by British scientist Robert WatsonWatt, and the technology would go on to play a pivotal role in the Second World War.
Radar has a wide variety of applications such as mapping terrain and monitoring of movement on the ground or in the sky, ocean and outer space. Indeed, some historians hail the United Kingdom’s radar chain defense line as the key technology that helped win the Battle of Britain in 1940, which ultimately contributed to the liberation of Europe from Nazi Germany. That’s how important the invention of radar was, and its importance has only increased over the years. Today, radar has a wide variety of applications such as mapping terrain and monitoring of movement on the ground or in the sky, ocean and outer space. This technology is critical to modern society, as without it, we would not be able to track satellites, navigate ships and airplanes in bad weather or make accurate
weather predictions. It’s hard to say where we would be now without radar technology – we may never have even made it to space. Radar has undergone many changes since 1935. Explained in simple terms, radar is a type of sensor that uses radio waves to determine the relative distance, angle and radial velocity of another object. Original radar evolved as a pulsed system, but this technology was greatly improved upon with phased array antennas. The 1950s saw the innovation of imaging radar, which not only gives positional and directional information but is also capable of displaying an image of the target object. In later years, digital signal processors, electronic beam steering and advanced computational methods enhanced the capabilities of imaging radar, allowing its application in a range of practical uses. Recently, we have witnessed the evolution of 4D imaging radar, made possible thanks to advancements in semiconductor technology that allow for multiple ‘cascading’ microchips to be connected to each other.
British scientist Robert Watson-Watt
4D imaging radar uses a Multiple Input Multiple Output (MIMO) antenna array and echolocation to accurately map 3D environments by detecting and resolving angles in both vertical and horizontal planes. November-December 2023 | www.geospatialworld.net | 13
ON THE COVER
This new radar technology uses time-of-flight measurements in its calculations (hence “4D”), but doesn’t actually include time in its imaging output. 4D radar is a cutting edge technology that already boasts a US$2.55 billion market size as of 2022 and is expected to grow by a CAGR of around 20% by 2032, according to a report by Emergen Research.
Advent of Automotive Radar Imaging radar is also notably used in the industry, especially as automotive technology rapidly advances and gets smarter. The technology has been evolving for a long time, and is now mature enough to be installed in mass-produced cars. It can improve automobile safety in a number of ways, including blind spot detection, lane change assistance, parking assistance, adaptive cruise control, and more. However, 4D imaging radar is just getting started and is still undergoing testing by automotive companies. 4D imaging radar technology came into limelight in 2015, when heavy fog in South Korea caused a massive 100-car pileup with two deaths. This tragedy might have been prevented – or at least minimized – if the cars were all equipped with advanced radar systems. 4D radar may still be an evolving technology, but it has the potential to advance more rapidly than other sensors. 4D imaging radar may be the key technology that finally leads us to realize fully autonomous driving vehicles. Autonomous mobility technology is a field of incredible
opportunity. The market value of the global industry is expected to reach over US$2.35 trillion by 2032, according to calculations by Precedence Research. To meet this incredibly high demand, the global automotive 4D imaging radar market size is expected to skyrocket by a 93.4% CAGR by 2028, according to Business Research Insights.
Imaging Radar as GameChanger? Imaging radar is already in use across many industries for applications such as monitoring and mapping coastal topography, agriculture, land use, storms and other areas of environmental concern. Other applications include 3D measurements, medical microwave tomography and patrolling dangerous locations. Within the automotive industry, imaging radar has helped us move toward autonomous driving. Driving automation capability is categorized by levels: we have already achieved Level 2 “partial” driving automation, which still requires a human operator to monitor the driving environment, and more recently Level
14 | www.geospatialworld.net | November-December 2023
3 “conditional” automation, which allows the vehicle to drive itself but still requires human override capabilities. Levels 4 and 5 driving automation, in which vehicles drive alone without human intervention, are still a ways off in the future and require more research and development of new technologies like 4D radar. In the past, autonomous driving R&D was largely focused on LiDAR sensors, a different range measurement technology that uses laser beams. However, the advent of 4D imaging radar now makes it possible to overcome some of LiDAR’s drawbacks – while it can detect objects very accurately, it is unreliable in adverse weather conditions. 4D radar has no such limitation, and it can detect additional data that LiDAR is less effective at or incapable of, such as relative speed, distance, azimuth and height of an object above the road. And since 4D radar achieves all of this without using any cameras, it is not reliant on lighting and can “see through” objects, giving
The advent of 4D imaging radar makes it possible to overcome some of LiDAR’s drawbacks – while it can detect objects very accurately, it is unreliable in adverse weather conditions. the vehicle complete information about its environment. In addition to its obvious uses for autonomous driving, 4D radar can also be applied to safety features inside the car by monitoring the interior at all times. Some possibilities include monitoring occupant position and vital signs, and classifying child and adult occupants. This data can then be shared with other systems in the car to optimize security systems, seat belt tension, airbag deployment, etc.
Challenges Restrictive global frequency regulations are a major obstacles holding back the development of Level 4 and 5 autonomous mobility. In order to progress past Level 3, we will need increasingly higher resolution which is not possible with currently allowed frequencies. This is one reason why industries are not actively investing in its development. A primary challenge automotive manufacturers face is the high cost of mass-producing 4D imaging radar systems. The price point really needs to be brought down. There is a current movement to replace existing RF PCB-based antennas with 3D antennas. Although mass-production of 3D antennas still requires further innovation, they are expected to replace the more expensive RF PCB antennas in the near future. Overall optimization of hard-
ware and semiconductors to integrate with multiple channels will also help bring costs down. Furthermore, mass production is only feasible if other systems are developed and integrated with the radar, such as a system that efficiently evaluates performance during the manufacturing process, and another that evaluates software performance on the road. It is a very complex process. Imaging radar can also be limited by blind spots at very close range due to ground reflection and DC noise caused by radar’s modulation and demodulation characteristics. Prevalence of blind spots depends largely on the mounting height of the radar system.
Future of Imaging Radar In the near future, it will be possible to integrate multiple radars to improve detection performance with centralized processing. Simultaneous Localization and Mapping (SLAM) and Synthetic Aperture Radar (SAR) technologies and multiple frequency bands can be applied to improve detection performance of imaging radars. To fully realize autonomous driving, it will be necessary to develop low-level sensor fusion algorithms that integrate 4D imaging radar with other sensors in the vehicle for centralized processing. This development will allow raw data from multiple sensors to be fused and acted on simultaneously on a millisecond by millisecond basis – just like a human driver does
when operating a vehicle. The resolution of imaging radars also must increase for Level 5 autonomy to become a reality. Fully autonomous driving can only be realized once perfect object classification is achieved using a higher resolution point cloud, which requires a wider aperture. This will require more transmit and receive channels on a vehicle’s windshield or front grill than what is currently possible. Utilizing higher frequencies will be necessary to reach the required resolutions. We need to start with global frequency regulation and open up those bands for utilization. It will take about 10 years for this to come to fruition. While imaging radar is in early stages, it is progressing rapidly. Once mass production begins, existing driver assistance functions can be upgraded while the combination of imaging radar with conventional radar will enable seamless long and short-range detection without blind spots. As the level of autonomous driving gradually increases, the paradigm of mobility will completely change and autonomous driving will seep into our everyday lives.
Jae-Eun Lee
Jae-Eun Lee, Founder & CEO, bitsening pioneered 77GHz radar in South Korea and successfully led it to mass production. Previously, he was Senior Research Engineer at Mando Corporation, one of the largest global automotive component supplier.
November-December 2023 | www.geospatialworld.net | 15
ON THE COVER
Steering A the Future
t the centre of today and tomorrow’s smart mobility solutions are digital, high-definition (HD) maps.
HD map are the bedrock upon which the future of connected and autonomous vehicles is built. They empower vehicles to perceive and comprehend the world with unparalleled accuracy. By Abhijit Sengupta, Senior Director & Head of Business, India and Southeast Asia, HERE Technologies
Just as a precise blueprint is fundamental to constructing a skyscraper, HD maps are crucial to understanding ground truth – from guiding automated vehicles, to constructing digital twins for urban planning, and optimising transportation and logistics. As per research estimates, the global HD map market for the automated vehicle market is expected to generate INR 308 billion by 2025. It is further projected to reach INR 5.5 trillion by 2035, growing at a CAGR of 33.4% from 2025 to 2035. HD maps are highly accurate, dynamic representations of the real world, augmented with a wealth of information. They provide a digital replica of the environment, capturing details down to centimetre precision. As driving gets more automated, HD Maps will provide the added intelligence to automated vehicles to help them address lateral and longitudinal control, apply contextual awareness to the surrounding environment, and process local road rules to enable safer and more proactive driving decisions. With automated vehicles and advanced driver assistance systems (ADAS) getting more prevalent, the value of HD maps cannot be overstated.
Enhancing Safety through Precision For automated vehicles to operate safely and efficiently, they require a high-fidelity map that can be updated with input from numerous sources as quickly as possible. Having an HD map that supports ADAS and highly automated driving (HAD) systems means that vehicles are equipped ahead of time with precise information about the road network to help them navigate safely through complex scenarios. In other words, an HD map and its continuously updated data layers provide automated vehicles with an extended view, beyond the on-board sensors, to “see” and “understand” the world around them. For example, when an automated vehicle approaches a busy intersection, an HD map provides not only the layout of the roads and traffic signals, but also critical information about the surrounding and the rules specific to that intersection. This empowers the vehicle to plan its movements, predict the actions of other vehicles, and ensure a smooth passage. Today, HD maps play a central role for the most advanced automated vehicle systems in the market. The BMW 7-Series’ SAE (Society of Automotive Engineers) Level 2 “hands-free” automated system – currently available in the U.S. and Canada, and from the end of 2023 in Germany in the new BMW 5-Series – drives ‘on-map’ instead of ‘on-lane’. This means it depends upon a
The future of smart mobility is about creating an interconnected ecosystem where vehicles can communicate with each other and their environment.
In the case of India where the country grapples with significant traffic congestion in its urban centres, an HD map can offer the foundation for real-time traffic updates, allowing commuters to plan their routes better and avoid congested areas.
high-quality HD map for attributes such as geometry, lane positioning and predicting road traffic signs in time. The sensors act as an extra layer so that the safety load is shared between the sensors and the map. The HD map is the primary input for creating the driving path of the vehicle with the sensors as a backup.
Fostering a Seamless Collaborative Ecosystem The future of smart mobility extends beyond individual vehicles; it's about creating an interconnected ecosystem where vehicles can communicate with each other and their environment via a common language that brings together various stakeholders, including automotive manufacturers, software developers, infrastructure planners, and city authorities. This common language is underpinned by an HD map. It provides a standardised and detailed representation of the environment. This data sharing will in turn create a collaborative environment where vehicles can work together to ensure a smoother flow of traffic and enhance overall road safety.
Empowering Location-based Services Urban planning and development can also rely on an HD map for detailed geographic and infrastructure information. Understanding traffic flow, population density, and infrastructure needs will assist in creating sustainable, smarter and more efficient urban environments. HD maps can also be integrated into various mobility services, such as ride-sharing and delivery platforms to optimise their operations. By utilising precise location data and traffic insights, these services can enhance efficiency, reduce travel times, and ultimately deliver a superior customer experience. Investors will also recognise the immense potential and impact of these services on various industries, prompting financial support and fuelling further innovation. According to research, the global smart mobility market is set to reach INR 33.6 trillion by 2032 and growing at a compound annual growth rate of 23.6% between 2022 and 2032. The availability of HD maps will act as a catalyst for innovation and investment, further contributing to this expanding industry.
Encouraging Electric Vehicle Adoption According to McKinsey, 70 per
November-December 2023 | www.geospatialworld.net | 17
ON THE COVER
cent of primary car owners in India have expressed their interest in considering an electric car for their next vehicle purchase – surpassing the global average of 52 per cent. Moreover, electric two- and three-wheelers are also attractive options in the service industry for ride-hailing and food deliveries to bring down carbon emissions and improve air quality in the country. As the transition to EVs unfold in India, data continues to play a huge role. Indian consumers who are considering an electric car next are also concerned about technology-enabled safety, charging time, and the availability of charging points. HD maps provide data on the road conditions that can impact
vehicle wear and tear, allowing EV owners to take advantage of predictive maintenance. With that in mind, an HD map is a feature that could lead to higher EV adoption. EV manufacturers should consider integrating locations of charging points, power capacity and availability statuses with an HD map that has historical and real-time data – such as precise elevation and terrain information, weather conditions and traffic patterns – to help EV drivers better plan their route. This brings about an enhanced efficiency and overall EV driving experience that could boost the country’s appetite for EVs. In India, the government has plans to make driver assistance
HD maps provide data on the road conditions that can impact vehicle wear and tear, allowing EV owners to take advantage of predictive maintenance. 18 | www.geospatialworld.net | November-December 2023
features such as adaptive cruise control, brake assist and lane keep assist a mandatory feature in all passenger and commercial vehicles. These features are supported by HD maps, which further helps automakers comply with strict regulations and legal requirements. As we journey into the future, the role of HD maps will only become more significant. Advancements in technology, such as 5G connectivity and artificial intelligence, will further elevate the capabilities of HD maps, enhancing real-time updates and predictive analysis. HD maps are not just lines on a digital canvas; they represent a paradigm shift, a revolution that will redefine the way we move in this new era of smart mobility.
Abhijit Sengupta
Abhijit Sengupta is Senior Director and Head of Business, Southeast Asia & India at HERE Technologies. Based out of Singapore, Abhijit brings over two decades of experience in Sales and Business Development, Product Management and Product Operations.
13-16 May 2024, Rotterdam
Geospatial Transition
POWERING THE WORLD ECONOMY Witness the various facets of the ongoing transition of the geospatial industry and its existing and potential value in the world economy.
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INTERVIEW
Geolocation The Golden Thread in Logistics Founded in 2015 in Paris, Stuart is a smart logistics company that aims to make urban last-mile delivery sustainable, innovative, and customer-friendly. Flexibility and efficiency are two of its cornerstones. Currently, it operates across six European countries with offices in Paris, Madrid, London, Barcelona, Lyon, and Lisbon. In the last three years, it has expanded to Italy, Poland, and Portugal. The company has a diverse network of partners, ranging from restaurants to software solution providers and marketplaces. Slerp, Tesco, Co-op, and Carrefour are some of its key partners. “Technology allows us to re-look at mobility in a completely different sense, from autonomous cars to drones and robotics. Since we are primarily a tech-enabled logistics platform, it’s essential for us to understand the needs of the end customer,” says Cornelia Raportaru, CEO, Stuart, in an exclusive interview with Geospatial World. What do you think are the key trends in last- mile delivery? Smart technology is really fundamental for the last mile. If we look at things linked from tracking to smarter dispatching and routing, these are often not visible but are really transformative for the industry.
all about finding the right partners that can integrate key experiences for the customers.
It changes how effectively a package gets moved from point A to point B. We have increasingly noticed that everyone appreciates a more hybrid fleet model.
As of now, there are a lot of players in this segment across different verticals, so perhaps, there would be more consolidation in the future. Post-Covid, there have been a lot of transformations. With hybrid work, there’s more demand for precise delivery. The focus has shifted from speed – delivery within minutes – towards precision.
For instance, there are restaurants that would use their own fleet and also the fleets and facilities of solution providers. Ultimately, it’s
At the end of the day, customer expectations often is to receive a particular package at a pre-designated hour of the day.
20 | www.geospatialworld.net | November-December 2023
Delivery automation, robots, and drones are some of the other game-changing innovations. A lot of companies are actively testing and experimenting with these. While I don’t think it could be scalable within the next year, the future is not that far when it comes to the sweeping power of automation. The conscious shift towards sustainable delivery is another key trend, though there’s some tension on who is going to pay for it. Over the next five years, as it becomes mandatory, we will start seeing a change in policy regulations in big cities as well.
What do you think is the role of geospatial and location intelligence in streamlining logistics and making them more resilient? Geolocation is the key across different industries. For us, a lot of last- mile urban delivery has the geolocation component, which is absolutely critical. It allows us to find the extra value in the ecosystem, extract it, and then share it with our courier partners, clients, and customers. Layering of data and traffic is another thing that we look at. For proper economical optimization, we need to check the distribution network and see which package is going where, and whether we need to stack them or start collecting on the courier routes. All of it requires very detailed geolocation. Datasets around weather patterns and events are also very important, especially for the European countries where we operate. There could be some challenges, such as layering all that information, contextualis ing it with location, and then sharing it with couriers. Today Gen.AI is in vogue. But before that comes Machine Learning. We use a lot of smart Machine Learning algorithms to address these issues. We will continue to incorporate AI to boost value for ou r customers and clients.
How is advanced technology and digitalization reshaping mobility? At the end of the day, we are in the process of transforming transpor-
The element of sustainable mobility and shared last-mile delivery will be a big one in years to come. This will lead to a new level of cooperation and collaboration. tation in many different ways. Part of this includes the climate pressure and the change in urban city regulations and planning. Technology allows us to re-look at mobility in a completely different sense, from autonomous cars to drone delivery, robotic delivery, etc. Since we are primarily a tech-enabled logistics platform, it’s essential for us to understand the needs of the end customer. For the next 24 months, there will still be a lot of focus on green vehicles and de-congestion. The element of sustainable mobility and shared last-mile delivery will be a big one in years to come. This will lead to a new level of cooperation and collaboration. Many retailers and restaurants may be required to share their transportation types instead of thinking solely from their own brand perspective. A lot of the efficiency and additional features would come from capacity sharing.
Tell us about the future focus of Stuart ? These are very exciting times. It’s my seventh month as the CEO, and our steady focus is on being the default partner for same- day urban delivery across all verticals. We are a market leader in the same- day delivery segment in grocery and food.
At the same time, we have developed an infrastructure that's very locally focused. For example, if we focus on London, there are different neighbourhoods with varying dynamics. We want to ensure that what is accessible to big brands can actually be reused for smaller retailers as well because they often don’t have many options. Post- pandemic, they are getting squeezed. We are looking at newer alternatives and developing infrastructure to connect and partner with them. It may require a different level of investment, but we are up for that challenge.
Any plans to expand in markets outside Europe? We are very focused on our European markets and on the journey towards being ultra-local. There’s a lot of space for us to grow within the six countries we operate. As of now, that's where the focus lies. That being said, we are always open to options to venture into markets where some of our strategic clients ask us to go with them because they don't seem to be able to find the same level of quality in the local market. While we explore options as they come, we remain very focused on our core European footprint. Interviewed by Aditya Chaturvedi
November-December 2023 | www.geospatialworld.net | 21
IN-FOCUS
Modernizing Railway Infra With population explosion and freight traffic expected to double by 2050, the dependency on railways is only going to rise further, which is why safety and security expectations are higher than ever. By Nibedita Mohanta
R
ecently, India witnessed three railway accidents, out of which one is the worst of its kind in over two decades, claiming more than 300 lives. The reason behind the train mishaps is stated to be signal error and fires.
These accidents not only take a human toll but huge expenses go into repairing the tracks, and developing new coaches. Indian Railways also has to foot the bill due to rerouting of goods and passenger trains while repair and rescue work is underway.
According to the National Crime Records Bureau's 2022 report there were more than 100,000 train-related deaths in India between 2017 and 2021. In 2021, more than 16,000 people were killed in nearly 18,000 railway accidents in India.
It’s not just India that is accident prone. According to data from the Federal Railroad Administration in the US, in 2022 there were more than 1,000 train derailments. The average per year figure between 2005 and 2021 comes out to be
22 | www.geospatialworld.net | November-December 2023
1,475. In 2022, the US registered 950 deaths and around 6,400 non-fatal injuries on the railroads. One of the major reason for train accidents in large parts of the world is aging railway tracks and infrastructure, followed by maintenance issues, and outdated equipment. Often same tracks are used for goods and passenger trains, which means overutilization of the railway lines, leaving not enough time for routine maintenance work to be carried out.
Role of GIS Indian Railways plans to map all the railway assets in the country and develop a dedicated GIS portal. To map the assets they have signed MoU with ISRO to use their satellite imagery and maps.
How Digital Twin can help
After the development of GIS portal, planning for enhancement/ augmentation of various facilities such as new lines, doubling/ multiple lines, traffic facilities etc. can be done more efficiently.
condition and understand environmental constraints,” he adds.
With the help of satellite images it will easy for them to regularly monitor the tracks and spot encroachments around the stations and other areas. GIS will provide valuable information during the life cycle of assets for efficient management, maximising throughput, ensuring safety and minimising disruption/delays to traffic. The use of maps within the transport industry is growing significantly. Location is vital to many of the operations that railways/metro needs to carry out, hence, the use of GIS is the optimal means for centralizing and coordinating these activities. “With an accurate GIS database of land and assets, users can derive effective plans for land management, asset mapping and maintenance, including encroachment and lease information management,” says Agendra Kumar, MD, Esri India. “Indian Railways is one of the biggest landowners in the country. With GIS maps, decision makers and stakeholders will know what assets they own, their current
U nderstand existing conditions I mprove and accelerate design and construction workflows I ncrease asset reliability and performance V isually enhance collaboration
Safe, efficient operations depend on accurate, real-time information. GIS can help visualize events as they unfold, deliver greater insights to respond fast to any incident. This is essential in coordinating across divisions and contractors to ensure the most efficient use of time while ensuring the safety of maintenance crews and optimizing efficiency. GIS will also be a critical element in case of disaster management, rescue planning, and implementation by helping to locate the accident site, provide essential information to rescue team, nearby hospitals, fire stations, etc. and alarm other approaching trains, finding optimum routes between resources locations and the site.
along with advanced sensor intelligence and Digital Twins which provide. Opportunities to reshape how infrastructure is planned, designed, built, and operated. With the availability and demand of large volume and variety of data, managing and updating it can be overwhelming for rail professionals, whether in project delivery or operations. To help engineers, designers, asset managers, inspectors, and other specialists, the global rail industry is embracing digital workflows on existing and future networks and routes. During operations, combining
Digital Simulation With the population explosion and freight traffic expected to double by 2050, the dependency on railways is only going to rise further, which is why safety and security expectations are higher than ever. To minimise accidents and ensure better utilisation of resources, railway infrastructure needs to be modernized. This is where geospatial applications, location intelligence, and simulative 3D models play a vital role, November-December 2023 | www.geospatialworld.net | 23
Image courtesy: Siemens Mobility
IN-FOCUS
The data collection process is built around a Trimble MX9 mobile mapping system that can be installed on trains, trolleys, and cars, as needed.
data from continuous surveys, photogrammetry, LiDAR, walked inspections and/or remote sensors, Digital Twins help optimize rail maintenance strategies to reduce costs and improve overall safety and reliability.
tion for LTR Jakarta Phase 1, the first light train line.
Bentley Systems offers Digital Twin solution that spans the entire rail asset lifecycle, enabling users to make more informed decisions and deliver improved outcomes.
WIKA used Bentley's ContextCapture to generate a 3D reality, using aerial photos, terrestrial laser scanning, and mixed reality technology to establish digital twin for smart inspection. Bentley helped WIKA save up to 41% in costs and complete the inspection twice as fast as conventional methods.
The company helped Indonesia's LTR Jakarta Phase 1 resolve traffic congestion. To address the problem the owner planned regular structural health monitoring but soon they realised the need to accelerate information exchange among the stakeholders to effectively manage asset performance and maintenance.
In order to maintain reliability and safety, Europe's many rail networks are undergoing a massive digital modernization using the Digital Twins model. Siemens Mobility has taken up the task of digitalizing planning, construction and operation of rail assets, which includes signalling and structures along all the lines.
To solve the problem PT Wijaya Karya (Persero) Tbk (WIKA) offered a digital inspection solu-
Large infrastructure projects demand up-to-date data and information and because the
24 | www.geospatialworld.net | November-December 2023
available information is outdated, Siemens is facing the problem in planning accurately, and traditional surveying methods are time consuming and tedious. “Rich data is great, very detailed and thanks to mobile mapping, we can capture it quickly. But AI is really the key to unlocking the power of data because it allows us to work with these large datasets in an efficient way,” states Carolin Baier, head of Digital Twin & Digitalisation Domestic Market Germany for Siemens Mobility.
Proper Monitoring The 2004 Tsunami in Sri Lanka led to the worst rail accident in modern history. Overloaded carriage of Queen of the Sea Line rail was hit by two powerful waves, drowning eight packed train compartments, leading to 1700 deaths.
Reliable and secure communication plays a crucial role between authorities and train operators, in terms of emergency situations monitoring train movements, detecting problems, and alerting train operators. This is where satellite communication come into play. Besides satellite commmunication also provides passengers with access to internet and other services while on board trains. “A data-based maintenance strategy is vital for giving rail asset owners and managers the tools they need to understand the real behavior of their assets. Otherwise, they’re relying on best guesses, no matter how proactive. The data illustrates the physical, geometrical and structural condition of the infrastructure and enables preventative maintenance and repairs based on facts,” says Bruno
Fileno, Business Development Senior Manager at Topcon Positioning Systems. “Keeping track geometry under close surveillance is particularly important in preventing accidents, as it has a direct impact on the 3D position of the rolling stock that uses the track. This means that personnel can quickly spot any potential issues and make the necessary changes to avoid collisions,” he adds. Space-based applications and services such as weather forecasts provide accurate and timely information about weather conditions. The United States has a form of GPS-based advanced rail control system for monitoring and control train movements, and preventing accidents caused by human error or miscommunication. The system
In order to maintain reliability and safety, Europe's many rail networks are undergoing a massive digital modernization using the Digital Twins model. can automatically enforce speed limits, stop trains at red signals, and prevent collisions between trains. The United States Federal Railroad Administration (FRA) mandated the implementation of PTC on all major rail lines, and the system has been deployed extensively throughout the country. This has led to significant improvements in rail safety, reducing the risk of accidents and derailments. Safe and reliable train systems rely on a mix of human efficiency, swiftness, quick response, methodological approach, constant upgrades, and technology interventions.
Image courtesy: Siemens Mobility
There are examples worthy of emulation that blend speed and efficiency with utmost safety standards. Japan’s high-speed shinkansesn, plying passengers since 1964, has never had an accident. Swiss Railways is also known for its efficiency and adherence to the highest standards of safety.
Nibedita Mohanta Skilled technicians at Siemens Mobility are putting digital twin techniques to work for Germany's Deutsche Bahn rail network modernization program.
Assistant Editor, Geospatial World Nibedita@geospatialworld.net November-December 2023 | www.geospatialworld.net | 25
INTERVIEW
Pivot to Smart Mobility Via Space A conversation on the growing need of space-data to pivot to a new connected age 26 | www.geospatialworld.net | November-December 2023
“Space-based approach allows persistently mapping any geography, including remote or evolving areas unmappable by other means. The data thrown down from space systems will become the eyes and ears of smart mobility”, says Andrew Peterson, CEO and Co-Founder, Array Labs, in an exclusive interview with Geospatial World.
Could you delineate the key trends that are driving the future of mobility? The future of mobility is unfolding along three intertwined paths: shift to EVs, incremental march towards autonomous driving, and the rapid growth of computerized, network connected-cars. While we are on the cusp of all three seismic shifts, today’s realities temper our excitement. Adoption of EVs is starting to look like an S-curve, with early adopters having already electrified. And the switch to electric powertrains poses new labor and supply chain challenges. Then, obviously, we have also seen that reaching true autonomy is staggeringly difficult, technologically, financially, and societally speaking. True connectivity has proven to pose quite a challenge for most OEMs not named Tesla. Array Labs aims to support these paradigm shifts by contributing to both upstream development and downstream applications. Upstream, we believe our digital surface and terrain models can assist supply chain players in sourcing and processing essential materials, such as lithium, nickel, and graphite. Our frequent remap capability could also help companies track and monitor assets across a far-flung, global network of sites and facilities. We also think our data could be helpful for energy infrastructure players looking to deploy new charging stations, energy storage plants etc.
We are laser-focused on creating mapping data and intelligence from our highly differentiated satellite swarms and 3D data products, which will enable automated and autonomous vehicles. These maps are not just for the vehicles of tomorrow but are increasingly relevant today as they help Level 4 robotaxis and autonomous Class 8 trucks with planning, perception, and localization. Lightweight versions of these maps also enhance driver assistance systems, underpin EV range estimation, and optimize logistics. That’s what we are calling Phase 1 of our mobility engagement roadmap – developing workflows for preprocessed, lightweight 3D data layers that our customers can directly ingest. We will deliver this data to OEMs, tech developers, auto suppliers, and logistics companies that are already proficient with point clouds, and capable of that nuanced analysis that will turn our data feed into actionable navigation information for their autonomous systems that is impossible for them to obtain from anywhere else.
How crucial will geospatial and space data be in building durable, sustainable infrastructure for the era of autonomous mobility? Advanced mobility fundamentally requires understanding the physical world. That means accurate, frequently updated geospatial data is absolutely crucial. What we are providing is a critical layer of intelligence that autonomous systems need to operate in our living, changing physical world. Space-based approach allows persistently mapping any geography, including remote or evolving areas un-mappable by other means. We believe our data will become a new source of ground truth for current and next-gen autonomous systems to operate reliably (nearly) anywhere. We are focused on providing the high-fidelity data that is essential for these systems. Our technology ensures that the infrastructure supporting autonomous mobility is robust, with an ever-vigilant eye from space that keeps the terrestrial data it relies on current and comprehensive.
November-December 2023 | www.geospatialworld.net | 27
INTERVIEW
Providing geospatial data is about creating a living digital infrastructure that can support logistics, urban development, and evolution towards autonomous transport. Transportation is considered a sector slow to advanced tech adoption, but now EO data, 5G connectivity, and AI & ML algorithms are veritably refueling it. How do you think the sector would look like in years to come, and do you foresee a closer synergy between New Space and Smart Mobility? I anticipate a deepening relationship between the space and mobility sectors. That said, we know that the transition to a new mobility paradigm is neither inevitable nor without challenges. It requires significant investment, has long lead times, and needs deep, cross-cutting integration.
ears of smart mobility. For instance, 5G networks will rely on satellite systems to extend their coverage beyond urban areas, and EO data will be crucial for the environmental monitoring that informs smart city planning and management. I foresee a future where the barrier between space and terrestrial mobility continues to dissolve. Our approach to providing geospatial data is about creating a living digital infrastructure that can support current logistics, urban development, and the incremental evolution towards autonomous transport. It's about recognizing the constraints and still finding ways to deliver value now, ensuring that when the world is ready to take the next step, the data foundation we have built will support it robustly, scalably, and sustainably.
We are engineers at heart. We deeply appreciate the levels of reliability, robustness, and resiliency that a technology must have to be considered “auto-grade.” Moving fast and breaking things doesn’t cut it in mobility.
Array Maps envisions building a 3D map of the entire globe for the age of connected and autonomous vehicles. Please tell us more about it? Array Labs’ vision is highly ambitious but grounded in the realities of today’s technology and market readiness. We are not developing anything that’s still in a basic research phase – or still being tinkered with in a lab. Everything we are working on has already been proven out on orbit, and flown in space.
Though, auto players aren’t necessarily laggards in tech adoption and digital transformation. Array Labs sees space as a critical enabler of this transformation. The data thrown down from space systems will become the eyes and
Our breakthrough is an innovative satellite architecture that effectively simulates a massive radar aperture. Array’s satellites will fly in formation. Our distributed radars will work in conjunction to image the same place on
28 | www.geospatialworld.net | November-December 2023
Earth from many different angles simultaneously. On the back end, our cloud infrastructure and image formation algorithms will automatically pull down radar readings and build a 3D point cloud of the planet – and then turn that data into incredible intelligence about our world on a daily basis We can map massive swaths of the planet in one satellite pass at an unprecedented resolution: 20cm by 20cm by 5cm. That last axis, denoting vertical resolution, is a paradigm shift for remote sensing from space. Furthermore, our first cluster will also have enormous capacity, as it will be technically capable of capturing 2 million square kilometers per day. We aren’t just creating static maps, but developing a dynamic mapping system that captures and processes changes on Earth's surface. To start, in 2026, we will be capable of re-mapping key areas of interest (aka, the areas of Earth where 95% of humans live) every 10 to 14 days. When it comes to 3D maps, previous approaches have missed the mark in coverage, refresh rate, or affordability. We overcome these constraints by pioneering an entirely new distributed model. What we’re bringing to the table is aerial LiDAR-grade imaging capabilities, at the scale and speed of a global satellite constellation. This would be of interest to the automotive, mapping, insurance, and self-driving industries, among others. Interviewed by Aditya Chaturvedi
INNOVATION UNLEASHED
S DEL O M LE T W OA I L A B AV
Fundamental Quality. Redefined.
insid
e
Imaging and LiDAR. Integrated.
SPECIAL FEATURE
Aerial LiDAR data taken from about 300m. It has a point density in excess of 500 pts/m2.
LiDAR Data O Quandary
ver the past two decades, remote sensing acquisition and processing has undergone a meteoric change, in terms of quality, versatility, and portability, as well as cost.
Then and Now Operationalizing Big Data LiDAR datasets across multiple workforces and domains require overcoming this functionality bottleneck. However, relying upon the creation of ever bigger workstations is not a scalable solution. While there has been some notable work in distributed computing, the majority of approaches are inherently problematic, as they rely upon the traditional consideration of these datasets as tiled entities. By Debra F. Laefer, Ph.D. 30 | www.geospatialworld.net | November-December 2023
Around 2003, there was no real-time processing and no option for multi-sensor units. In contrast, today’s equipment is not just userfriendly but often has an integrated Global Positioning System (GPS). Presently, there are many reliable terrestrial units under $20,000, most of which are either lightweight hand-held units or sufficiently compact to fit in a backpack. This generation of
Photon LiDAR is yet another development to watch. It has the potential to bolster the ability to produce better point clouds but without consideration as to the data’s operationalization. Furthermore, a lot of commercially viable tools long adopted by the industry cannot ingest and render the billions of points that may be acquired within a single scan. Ultimately, the data acquisition trajectory is only likely to steepen given the move to more national scans such as the 3DEP by the United States’ government and the inclusion of LiDAR like capabilities in the last four iPhone releases.
equipment has revolutionized not only equipment accessibility but spawned a dataset explosion.
Challenges & Opportunities Previously, the problem was highcost equipment and logistical difficulties. Now that those have been overcome, the newer challenges are associated with data storage and management. Storage is not just an issue of repository space but having sufficient RAM to enable processing without repeatedly accessing the hard-drive. Problematically, our ability to produce data has far outstripped our ability to host and manipulate it even on a high-end processor.
Photon LiDAR is yet another development to watch. While it has not yet to enter the market widely, it has the potential to bolster the ability to produce better point clouds but without consideration as to the data’s operationalization. Operationalizing Big Data LiDAR datasets across multiple workforces and domains requires overcoming this functionality bottleneck. However, relying upon the creation of ever bigger workstations is not a scalable solution. While there has been some notable work in distributed computing, the majority of approaches are inherently problematic, as they rely upon the traditional consideration of these datasets as tiled entities. While chunking data based on spatial location and a maximum dataset size worked well historically, those point clouds had data densities of only a few points per square meter, which meant that
a tile’s spatial extent could span several kilometers. Consequently, spatial discontinuity at a tile’s edge was rarely a problem, as most features of interest could be easily contained within a single tile. However, today's datasets of more than a billion points per square kilometer necessitate either extreme degradation of the data, which defeats the purpose of high-resolution scanning, or vastly shrinking a tile’s spatial extent. Tiles with smaller spatial extents increase the probability that features of interest such as parking lots, buildings etc will cross multiple tiles. This is quite problematic. To date, we lack a commercial or otherwise widely available solution to address LiDAR data management across multiple machines. This is especially true in a sharednothing distributed computing environment, which has been identified as the most promising direction for large-scale point cloud management.
Bespoke Approach An alternative approach has been per-point processing and storage, where each point is considered independently of all others. This has been shown to work well for applications such as shadow casting and solar potential estimation. The approach has the advantages of
November-December 2023 | www.geospatialworld.net | 31
SPECIAL FEATURE
being extremely parallelizable and providing the opportunity to store processed results directly with the point itself (both interim and final results), which allow those products to be more easily reusable. However, per point processing contravenes the traditional mindset of neighborhood data grouping to inform both segmentation and object detection. So, in reality, per point storage and processing is best suited for a subset of applications related to line-of-site and situations where the need for those applications in known a priori, which is often not the case with general data collections, such as that which occurs in national scans.
Pressing Need To overcome all of these difficulties, the community of practice should be further exploring the rich area of data indexing both as a native data storage mechanism (as has been done with approaches such as 3D r-trees, octrees, and k-d trees), but also as a one-time expense for data organization, in which neighboring or proximal points can be stored more efficiently in the memory of a single desktop computer.
This approach has the potential to vastly extend the capabilities of existing hardware. The implications of such a strategy are significant as this would vastly reduce the hardware-based impediments to the exploitation of existing datasets and, in turn, enable many more individuals and organizations to more easily and effectively work with modern and future datasets.
Looking Forward This data operationalization problem is critical not just with respect to increasing data densities, but with respect to the meta data affiliated with each data point. As an example, laser scanning data of 20 years ago generally had an x-, y-, and z-coordinate, and an intensity value. Common commercial equipment now provides a red, green, and blue value taken from the integrated camera. Furthermore, high-end commercial equipment can know provide information such as multiple returns, the times of the output and return signals, the fullwave version of the return signals, the pulse of the outbound signal, and the location of the platform, at the moment of acquisition. Current
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photon laser scanners already record each photon return, as well with their affiliated energy level. Critically, the next generation datasets may include a wide range of other information from the atmospheric to the atomic depending upon future sensor integration. For example, if hyperspectral data were available, for each pixel there would be a radiance response for wavelength collected along the spectral range. This could add hundreds of pieces of data to each and every point in a point cloud. This would necessarily transform our gigabyte data to terabyte data and our terabyte data to petabyte data. Before we become victims of our own success in data acquisition, we should really consider how we are going to work with these datasets so that we can benefit from them.
Debra F. Laefer
Dr. Debra F. Laefer, a distinguished researcher, started her career at North Carolina State University, later becoming a Professor at University College Dublin. Currently a Professor at NYU, her groundbreaking work merges civil engineering and computer science, recognized globally.
CASE STUDY
LightBox Provides Data for Alabama’s Cadastral Maps Introduction Founded in 1915, the Alabama Department of Conservation and Natural Resources (DCNR) takes care of the state's natural resources and conservation efforts. Its branches include state land, parks, wildlife, and aquatic resources. The department also issues hunting and fishing licenses for people residing in the state. Spanning more than a thousand square kilometers, Alabama has great land resources. However, the challenge presents itself as taking care of such a huge landmass requires complex mechanisms that are often inaccurate or incomplete. Ashley Peters, a GIS specialist in the State Lands Division of the DCNR, and her team primarily deal with managing wildland trust properties and other trust lands. This requires a large amount of land parcel data which must be accurate enough to be trustworthy. Corroborating this data with the official cadaster data is another
major task that takes weeks when done manually.
Challenges A bsence of state-wide cadastral and parcel data L imited federal land data with no information on land owner
The state-wide data is crucial for projects such as managing species databases and drawing deeds to make land purchases. Inaccuracy in data can result in huge monetary losses and even civil liabilities.
Solution After being introduced to LightBox at a GIS conference, the DCNR assessed the cost of bringing the company and its GIS platform on board. Once deemed viable, the state decided to adopt LightBox’s data GIS platform, LandVision, and their statewide parcel dataset. The department realized the increase in efficiency as the need to go county to county to collect GIS data was diminished through LightBox. The manual method was even more challenging given some counties lacked the basic geospatial and land data, especially in the more rural Black Belt in Alabama. LightBox made accessing parcel
C ounty websites as the only source of reliable data A ll data was processed manually which decreased the efficiency
data easier as well as resolving issues in less time as compared to without the platform. The other branches of the department soon followed suit by adopting LightBox data into their daily workflows. Due to this, DCNR became one of the few Alabama agencies in the USA with access to state-wide parcel data.
Conclusion Complete access to land parcel data is crucial for any department that is working to develop and maintain land records in the state or county. A platform such as LightBox can greatly handle this concern and make it more efficient with less effort.
November-December 2023 | www.geospatialworld.net | 33
CITY SPOTLIGHT
Innovative Smart Mobility Projects to Watch Out In order to ease congestion and reduce emissions, mega cities from New York to Tokyo are experimenting with novel mobility approaches and smart tech solutions. By Sachin Awana
W
ith 65% of the world population projected to live in cities by 2050, aging infrastructure and the stress of climate change, and rising population brings forward the need for next-gen smart mobility transportation. In the 1960s, there were two megacities with more than 10 million population. By 2050, there would be around 50 such cities, most of them in the developing world. High-rises and great density
concentration brings forth the need for better public transportation in majority of metropolitan cities. This would require increased reliance on smart mobility solutions. Behind the veil of smart mobility, the connotation ascribed to innovative, optimal, futuristic paradigms, which is redefining the way people live and commute, there lies the convergence of geospatial with frontier technologies such as AI, 5G and IoT. All of it hinges on fast and real-time
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data analytics. When it comes to smart mobility solutions, location Intelligence plays a critical role in creating wellversed mobility solutions. “Location intelligence is key to building mobility infrastructure of the future as it enables effective planning, be it for electric vehicle charging or hydrogen supply. It also helps to plan better and build supply in areas affected by demographic change,” says Henning
Source: Department of Civil and Environmental Engineering, University of Wisconsin Madison
Hollburg, Founder & Managing Director, Targomo.
Novel Solutions Countries around the world are piloting novel projects and test programs to gauge the nature and feasibility of their social environmental impact. This gets all the more crucial at a time when urban congestion and global warming are afflicting urban spheres globally. When it comes to fast-paced technology adoption, some countries are at the forefront, while others are expected to follow suit. As technology adoption accelerates, the gap would be gradually overcome. The front-runners in this space are technologically advanced countries such as Japan, Singapore, United States of America (USA), Hong Kong, South Korea, China, and United Arab Emirates (UAE).
Taking the example of New York, Tokyo, and Hong Kong, what stands out is the railway network which acts as the backbone of public transport. Furthermore, buses and shared vehicles make up the other important parts that help keep these cities afloat. Shared Mobility, Autonomous Driving, and Vehicle Electrification are some of the other emerging mobility trends. A report by McKinsey highlights “In 50 metropolitan areas around the world, home to 500 million people, integrated mobility systems could produce benefits, such as improved safety and reduced pollution, worth up to $600 billion.” This becomes a focal point in enhancing smart mobility practices and technology to aid better life-
style amongst the citizens as well as keep sustainability in check. “Smart Mobility technologies give a lot of power to urban mobile options and push them on the path to work better for not just consumers but also the environment, by being aware of the best possible solutions to the existing problems and being prepared for the challenges ahead,” says -Amit Gupta, CEO, Yulu.
Let’s have a look at innovative mobility approaches of five countries: Singapore Being a city state, Singapore has been pioneering various facets of public living; from housing to business districts. However, the business powerhouse has one major problem – land scarcity. With a growing population, the demand
November-December 2023 | www.geospatialworld.net | 35
CITY SPOTLIGHT Tokyo, Japan Tokyo, the world’s biggest megapolis with more than 30 million residents, has one of the most efficient and innovative transportation systems in the world. However, Japan is coping with declining birth-rate, aging citizenry and dwindling population.
on housing and transportation faces a challenge like no other.
this could be our reality in the not-so-distant future.”
The Singaporean government has identified Smart Urban Mobility as one of their strategic national projects to enhance reliability, comfort, and public convenience in their transportation methods.
“In June 2018, MOT and ST Engineering started on-road testing of autonomous shuttles along a 1km road at Tanjong Beach, Sentosa. In 2019, this was extended to cover a 5km route.
Another aspect of Singapore’s leap in mobility transition has been self-driving vehicles. The government has been conducting self-driving shuttle trials to assess the feasibility of the autonomous technology in terms of longevity and safety.
The trial allowed visitors to book these autonomous shuttles as and when they require them, using their smartphones,” Singaporean government agency states.
The government has also developed a special research and test circuit for autonomous driving called CETRAN that spans 1.8 hectares and collects data such as traffic behaviour, rule adherence, and road design optimization of these vehicles. The government of Singapore is looking into the feasibility of On-demand self-driving public buses. According to the authorities, this would enable anyone to book a ride at their doorstep to the desired train station or other bus stop. “A real-time, demand-driven intelligent transport system like 36 | www.geospatialworld.net | November-December 2023
To curb these problems in the long run, an initiative called the Smart Mobility Challenge was launched by the Ministry of Land, Infrastructure, Transport and Tourism and the Ministry of Economy, Trade and Industry. This project supports local government and private efforts to solve regional challenges and revitalize regional economies through the introduction of transport services equipped with technologies such as IoT, AI, and automated driving, as well as, catalysing datasharing for greater interoperability.
New York City, New York Being the financial district of the world, New York City is a one-ofits-kind metropolitan ridden with traffic and mobility problems. NYC has some of the largest network of public transit, yet, the city often faces traffic jams and overcrowded bus and rails. New York City has 6,000 miles of streets that must accommodate more than 5,000 public buses, 13,000 taxis, 60,000 for-hire vehicles, and millions of commuters daily. The problem gets more compounded on roads where vehicles face unbound congestion. To curb these issues, the Department of Transportation (DOT) established Midtown in Motion, a technology-enabled traffic management system that uses real-time traffic information from a variety of sources to monitor and respond to various traffic conditions. The system incorporates microwave sensors, traffic video cameras and tag readers to gather traffic
flow information, which is then transmitted wirelessly to the DOT’s Traffic Management Center (TMC). As vehicles sit bottlenecked in traffic, they emit a range of greenhouse gases and particulate matter associated with air pollution. Midtown in Motion mitigates this effect by reducing vehicle idle times, helping to keep New York City’s air clean, according to a report by Hellman Electric. These technologies save the average commuter nearly 15 minutes a day in the city while also helping the environment. New York City has also launched a program to gather crucial data in road vehicles to aid better traffic management through automated sensing hardware and computer algorithms which are proven to reduce time-intensive jams of people and vehicles in priority intersections. “Municipal Testbeds will be designated throughout New York State for testing and validating smart cities solutions developed
by Technology Companies. Under this pilot, Technology Companies will be eligible to apply to implement their smart cities solutions for projects proposed by Municipal Testbeds,” states a New York government report. Automated data collection can be run through existing CCTV feeds or site-mounted sensors to collect continuous counts and other data in an accurate, flexible, and lowercost method. The project will drive greater understanding of travel trends and improve safety.
London, United Kingdom The UK government has realised the true potential of smart mobility, and has been bringing out policies to aid the same. One case for furthering next-gen mobility is the Smart Mobility Living Lab (SMLL) initiative, wherein public and private roads are being used to develop and validate new mobility and transport technologies in a real-world connected environment. The aim of SMLL is to create the future innovative ideas into a sensible reality. It provides solutions to major problems, especially in the autonomous vehicle sector that faces crude barriers in the real-world situation. By providing facilities to test in real-life situation or simulate through software, the cause of smart mobility gets realised in a shorter time period. “The concept of SMLL was co-created by an industry-government joint initiative as part of a multi-million pound, on-going
November-December 2023 | www.geospatialworld.net | 37
HONG KONG SMART MOBILITY CITY SPOTLIGHT
Current Status HONG KONG SMART MOBILITY 10.6 million Over
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Location intelligence is key to building mobility infrastructure of the future as it enables effective planning, be it for electric vehicle charging or hydrogen supply. 38 | www.geospatialworld.net | November-December 2023
Sachin Awana Sub Editor, Geospatial World Sachin@geospatialworld.net
INTERVIEW
Predictive Intelligence for a More Sustainable World In an exclusive conversation, Hasan Al Hosani, Managing Director of Bayanat, shares his views on the evolution of geospatial analytics over the decades, multi-sectoral use-cases, criticality of predictive intelligence, and more. Bayanat has established itself as a key provider of geospatial data analytics across sectors, ranging from smart mobility to logistics and supply chain. How do you see the evolution of geospatial data marketplace over the years, and where is the future headed? The evolution of technology over the years has been remarkable. It continues to defy what humans once thought was possible. Bayanat started as a mapping and surveying company and has
transitioned into an AI-powered geospatial analytics firm. We provide solutions and predictive capabilities to organizations in government, environment, energy and resources, as well as smart cities and transportation. A lot of the work we do now was unimaginable a few years ago. This underscores the pace of innovation, especially in the past few decades. Currently, geospatial intelligence, AI, and Big Data analytics
are becoming increasingly crucial across all industries to provide greater insights that inform important decisions. As we look at the evolution of the geospatial data marketplace holistically — and as the pace of progress quickens and the world continues to evolve — our reliance upon geospatial data and technological advancements to provide decision-makers with more comprehensive data will surely increase.
November-December 2023 | www.geospatialworld.net | 39
INTERVIEW
One area that will undoubtedly improve in the near future is increased accuracy of data visualization– this includes high-definition maps, 3D models, and digital twins. Bayanat is working to enhance the geographic user interface to bolster simulations and enable users to make predictions with an even greater degree of certainty. This will simplify the process and make it easier for users to understand, resulting in more accurate, efficient, and faster decision-making times. Looking at where we are now, geospatial mapping is accurate within 20 meters or so. Looking ahead, if an autonomous car needs to switch lanes at a very precise time, the geospatial data needs to be accurate within 50 centimeters. This level of accuracy is crucial for technological advancements to seamlessly integrate and improve our lives and will benefit all industries, including environment, urban planning, smart mobility, satellite, and sensor capabilities, as well as location-based services.
AI is reshaping multiple sectors and verticals. What do you think would be its impact on on-demand geospatial Data-as-a-Service paradigm? AI’s impact on geospatial Data-asa-Service (DaaS), like all industries, has been and continues to be profound. When combined, DaaS and AI can significantly impact businesses and organizations — from the way we extract insights from geospatial data, to improving accuracy of analytics. AI creates the pathway for
We are focused on growth and innovation in three key areas, including AI/ML, satellite technology, and location-based services. more accurate and timely decision making in a wide range of fields, from agriculture and urban planning to disaster management and environmental conservation. As AI continues to evolve, its impact on geospatial DaaS is likely to become even more significant. As the geospatial DaaS industry experiences this significant growth, it will offer more cost-efficiency and broader accessibility to geospatial insights — benefiting those who leverage the technology in novel applications driven by wider and more frequent availability of data from multiple sources. We aim to accelerate the use of AI in geospatial DaaS, ultimately transforming data products into information and providing recurring DaaS to our clients in the fields of critical infrastructure, oil and gas, municipal administration, environment, and security.
Bayanat has industry partners all across, from associations, academia, to satellite imagery providers. What are some of the key areas that you would focus on in the next five years? At Bayanat, we are always keen to find the right partners that can give
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us the right momentum. We look at where technology stands today and, with that partner, consider how we can take it to the next level. Bayanat’s vision for the next five years revolves around leveraging advanced technologies, refining data collection methods, and expanding our services to align both with evolving market demands and to support the UAE’s vision of becoming a global geospatial leader by 2031. We are focused on growth and innovation in three key areas, including AI/ ML, satellite technology, and location-based services. The first is about creating scalable Big Data platforms in order to harness the full potential of AI, which will play a pivotal role in enabling more efficient and effective geospatial data analysis. AI allows organizations to streamline decision-making processes and deliver enhanced solutions across industries faster than ever. In situations where time is of the essence, having AI capabilities that uplevel decision-making capabilities is crucial. Second, with the expected launch of new satellites and ongoing improvements in sensor capabilities, Bayanat is poised to collect geospatial data with unprecedented accuracy and detail. Advancements in satellite and sensor capabilities will impact several industries, from security to environment to land-use and urban management. Lastly, we expect continued growth in location-based services, particularly in navigation and logistics. I mentioned earlier that increased visual
the development of in-country satellite manufacturing capabilities. We plan to expand on this seed program to develop a state-ofthe-art multi-sensor constellation. This comprehensive approach positions us to meet the evolving demands of the space sector effectively and set the trends the industry will then follow.
accuracy will be incredibly important in realizing this growth. Bayanat is developing solutions that optimize route planning, resource allocation, and asset tracking, which can be used for advancements in autonomous vehicles and growing smart cities.
What do you think are the defining trends in the space sector, and how do you see Bayanat’s vision with it in a rapidly changing sector? Space sector is rapidly changing and constantly evolving with the advent of the new space era. We are constantly evolving to keep up with market demands and technological advances. Towards this, we prioritize strategic partnerships to augment and enhance our existing solutions and ensure that we remain at the cutting edge of innovations as well as set the trends that the industry
will follow. An example of a partnership is our work with the UAE Space Agency, which has been a great champion for us, supporting our work to bring these advancements into the UAE. Another would be our partnership with Yahsat and ICEYE, where we announced a comprehensive Space Program and Earth Observation capabilities aimed at building national satellite remote sensing capabilities within the UAE. One of the ambitions of this partnership is to develop a constellation of at least five Synthetic Aperture Radar (SAR) low earth orbit (LEO) satellites. This constellation will provide a consistent data stream, enabling end-to-end solutions for SAR applications. The program is a stepping-stone towards realizing a broader space ecosystem in the UAE, including
How crucial can predictive intelligence be to ensure global sustainability goals? We envision AI and predictive intelligence playing a growing role in global sustainability efforts – which is why we have invested heavily in partnerships and technology that work towards sustainability goals. Geospatial intelligence and mapping can provide real-time data on traffic patterns, population density, and other factors that are used to optimize existing transportation networks, urban planning expansion, and resource allocation and management. In fact, even Mira Aerospace’s (JV between Bayanat and UAVOS) High-Altitude Pseudo Satellite, which gathers much of this valuable and actionable geospatial data, harnesses solar power to reduce the need for fuel powered generators – minimizing carbon emissions compared to traditional satellites. Our dedication to sustainability extends across the products and services we offer, from mobility solutions to marine and ocean exploration to urban planning. Interviewed by Meenal Dhande
November-December 2023 | www.geospatialworld.net | 41
CASE STUDY
Bridge with BIM Introduction The Liaozi Grand Bridge belongs to the National Expressway G69 in China, also known as the Chengkai Expressway, located in Liaozi Township in Chengkou County, where the terrain is steep and complicated. The Chengkai Expressway is a super project with a total length of 129.3 km, a bridge-to-tunnel ratio of 81%, and a total investment of 23.4 billion RMB. After its opening, Chongqing will achieve expressway access to every county, which is of great significance in assisting rural revitalization in the area. The Liaozi Grand Bridge is one of the iconic projects on Chengkai Expressway. The total length of the bridge is 330.812m, crossing the Qianhe Gorge, it is a typical bridge in mountainous and hilly areas.
The main bridge is a medium-bearing steel box arch bridge with a calculated span of 252m, which is the first non-coating high-performance weather-resistant steel box arch bridge in China, and for the first time, it adopts the single arch rib which requires aerial horizontal and vertical composite rotation construction. In this project, China Railway Changjiang Transport Design Group Co., Ltd. is mainly responsible for digital design and 3D construction simulation.
Challenge The Liaozi Grand Bridge is located in the Qinling Mountain Canyon area. Due to the steep terrain, it is difficult to build temporary construction roads and bring materials and machinery to the site.
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Project Details Project Name Liaozi Grand Bridge Project Designer China Railway Changjiang Transport Design Group Co., Ltd. Location Chengkou County Total Length of Expressway 129.3km Bridge-to-Tunnel Ratio 81% Total Investment 23.4 billion RMB Total Length of the Bridge 330.812m Design Cost Saved 1.5 million RMB Time Saved 35 Days Management Costs Saved 20 million RMB
Solutions at a Glance U AV Aerial Survey Carried out C ontextCapture used to process survey data E stablished high-precision 3D Model P oint clouds, Live scanning provided realistic terrain model B ridge model fused with 3D model in Microstation F used model provided layout for the bridge Both sides of the bridge arch abutment on the steep terrain, poor traffic conditions. The bridge deck is 127 meters away from the river surface, and the highest part of the arch ribs is 186 meters away from the river, which is equivalent to the height of a 60-storey building, making the construction difficult.
Solution ContextCapture was used to process the UAV aerial survey data to establish a high-precision 3D real-world model, create a terrain model of the bridge site, present different surfaces in the form of contour lines or triangulation grids, and create effective elevation with slope analyses. The efficiency and accuracy of the work is substantially improved by using high-precision orthophotos, point clouds or live scanning to generate a realistic terrain model of the bridge site and the project construction at various times during the construction process. In MicroStation, the bridge model is fused with the real model,
and at the same time, the terrain in the real model is modified according to the excavation and filling information, so that the two are integrated, and the fused model can be used for the layout of the bridge scheme, the roaming display of the bridge, the observation of the approach slopes, and the construction simulation based on the real view, which are all the basic data for the operation behind.
Outcome In this project, UAV mapping technology was used to capture complex terrain (mountainous areas with high slopes) accurately and quickly, and to create a digital model of the ground surface. By combining this with geological survey data and BIM, a geological model was constructed. The integrated terrain and geological model was applied to bridge alignment, bridge location selection, bridge layout, etc., which visually represented the project site, improved the efficiency of design optimization, and reduced travel time to and from the site by approximately 25 days.
The use of Bentley parametric modelling shortened the bridge design time by 300 hours, saving 1.5 million RMB in design costs; the new workflow combined with the use of Bentley technology, facilitated the completion of the design project 35 days ahead of schedule. By establishing virtual simulation via MicroStation, it was discovered in advance that there would be collisions with the mountain during the rotation construction. In actual construction, the vertical rotation angle of the arch rib was increased to avoid collision. Problems can be detected earlier than traditional design, effectively ensuring the success of the rotation construction. The savings in management costs and risk losses are about 20 million RMB, which brings huge economic and social benefits.
Yiming Tang Engineer, Intelligent Transportation Institute China Railway Changjiang Transport Design Group Co., Ltd.
November-December 2023 | www.geospatialworld.net | 43
IN-FOCUS
Predictive Fleet Maintenance Harmonizing Viability with Sustainability With ambitious net-zero emission targets and the race towards cleaner mobility such as EVs, analyzing troves of data using AI, ML etc is essential to balance profitability with larger sustainability goals. By Giorgio Sarno, Senior Data Scientist, Stratio Automotive
T
he world is swiftly shifting from combustion engines to alternative means of transportation, fueled by environmental concerns and unstable oil prices. Greenhouse gas emissions from transportation account for about 29% of total U.S. greenhouse gas emissions, making it the 44 | www.geospatialworld.net | November-December 2023
largest contributor to GHG emissions according to the Environmenal Protection Agency. Meanwhile, the European Commission’s stated ambition to make all new city buses 100% zero emission from 2030, and to reduce bus and truck CO2 emissions by 90% by 2040, is moving sustainability rapidly up the priority agenda for manufacturers and operators alike. Public transport companies are undoubtedly among the most responsible in helping to limit global climate change. However, public transport providers must still turn a profit to remain economically viable whilst pivoting their vehicle strategy to reach these goals. The upfront investment required to operate a lower-emission vehicle fleet can be very high. With bus companies already facing financial challenges due to falling passenger numbers, skyrock-
Furthermore, with high upfront and repair costs for EVs, fleet reliability and vehicle availability will be critical to the successful rollout of electric buses. They need to be operating at all times by ensuring operations are planned efficiently and that there are no faults that require the vehicle to be taken off the road. The life cycle of battery packs and other components, such as motors, inverters and chargers, must be extended as much as possible. In order to effectively utilize the investment and successfully adjust their operations in a way that does not negatively impact the bottom line, public transport companies will need a deeper strategic understanding of the EV transition. Thankfully, the availability of predictive maintenance technologies that leverage data, AI, and Machine Learning capabilities can help transportation companies bring about a smoother and more profitable EV transition.
eting costs, and the end of emergency government funding following Covid, this is a hard step to take. Though multiple bus companies such as First Bus and National Express West Midlands, are already making considerable investments in electric buses, the changeover to electric vehicles will be costly and inefficient without a proven strategy for bus operators to follow. The European Commission outlined that it will be up to manufacturers to decide which technologies they use to achieve future CO2 standards. However, choosing between battery and hydrogen fuel cell vehicles is only part of the challenge. The operational landscape for lower emission vehicles such as EVs represent new territory for traditional fleet managers, requiring a totally different skill set relating to life cycle costs, battery maintenance, route management and more.
Leveraging Data EVs produce far more data than internal combustion engine ( ICE ) vehicles. Nearly all of the components have electronic control, which means there are a lot of sensors by default, making it easier to digitize the entire vehicle with more granularity. This offers an opportunity for fleet managers to put the right tools in place to leverage vehicle data to increase the efficiency and reliability of operations. The best way to leverage the data collected from EVs is to turn it into intelligence that will maximize uptime and dependability of operations. Fleet management is important, but without an advanced maintenance strategy in place, and without visibility over the state-of-health of key components, managers won’t be able to reap the opportunities for efficiency and reliability that a fully electric fleet represents. By integrating predictive solutions that collect and analyze vehicle data during regular operation fleet managers are able to establish the true remaining useful life (RUL) of components and use the information to intelligently schedule vehicle servicing in order to extend operational life. November-December 2023 | www.geospatialworld.net | 45
IN-FOCUS
Efficiency Gains There are significant efficiency gains and cost-saving opportunities for operators looking to transition to EVs which will help to bridge the crucial gap between sustainability and profitability. However, a successful and cost-efficient electrification requires a plan to leverage the opportunity that comes with additional data and transform it into extended vehicle uptime, utilization, and useful life for EVs.
Moreover, by gaining real-time, actionable insight into the internal faults of electric buses, maintenance managers can diagnose malfunctions remotely. Vehicles stay on the road for longer, maintenance becomes more predictable and less expensive and breakdowns happen less frequently, preventing costly downtime and service disruption. EV batteries give us the best example of the benefits of increasing the lifespan of components. Accounting for around 40% of the total vehicle cost, it’s imperative to extend the battery’s life cycle in order to ensure a profitable electrification. Calculations must be made to account for the degradation of the battery over time and the impact this has on range, as well as a range of out of control factors such as weather, traffic, route and load which can alter the distance a bus can travel on one charge. Without this understanding and visibility, it will be impos-
sible to plan for a smooth, efficient and cost-effective service. But predictive battery analytics can provide an accurate, comprehensive view of the battery health evolution of an EV bus, allowing for effective route planning and charging requirements, as well as operation optimization metrics to extend the lifespan of the batteries. By leveraging State of Charge (SoC) and Depth of Discharge (DoD) data, fleet managers can understand if the operation profile can be changed to maximise battery life. This means that the initial investment is spread over a longer period of time, enabling a more efficient planning of maintenance operations and charging sessions so as to minimize downtime and increase service reliability - as well as reducing the total cost of ownership of electric buses. This type of analysis is fundamental for an operationally successful and profitable EV fleet deployment.
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Expertise and visibility are also a factor, as EVs are still new tech and unfamiliar to workshops worldwide. Partnering with a predictive maintenance solution accelerates capability building, as platforms embed industry knowledge and best-practices that may take years to acquire successfully. With the EU's climate goals setting the bar high for the speed at which operators are expected to switch to zero-emission vehicles, it is essential for all operators to look into solutions that can make this transition successful by turning EV data into intelligence and accelerating the achievement of cost neutrality. Any organization considering transitioning to EVs should prioritize implementing a suitable maintenance strategy to ensure a successful and cost-efficient electrification.
Giorgio Sarno
Giorgio is a Data Scientist at Stratio, where they specialize in anomaly detection and develops ML models for predictive maintenance in the automotive industry. Prior to this, Giorgio founded KNOTS, a data science company.
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