SMARTER HOMES, CITIES AND INFRASTRUCTURE

At home, virtual assistants respond to our commands, smart meters automatically transmit readings to energy companies, and intelligent thermostats learn our preferred central heating settings. In the city, real-time transport information, cycle-hire schemes and checkoutfree shops are all enabled by the IoT, and sensor technologies are monitoring essential infrastructure to ensure it is safe and secure.

The possibilities for future uses of IoT in our homes and cities are limitless, and our researchers are investigating ways to make new applications a reality. As well as improving our everyday lives, IoT-based solutions have the potential to address major societal challenges, from caring for an ageing population to meeting climate change goals through greener transport and more efficient energy use.

Developing underpinning technologies for smart cities

One project that has developed IoT systems for smart city applications is Wearable and Autonomous Computing for Future Smart Cities, a five-year project funded by the Engineering and Physical Sciences Research Council (EPSRC). It encompasses all the layers of the IoT stack, from developing sensor and energy harvesting devices through to building effective connected systems and designing intelligent software for data management and autonomous decision making. It is also looking at how humans and smart systems interact and how to advise or incentivise people to take actions that will benefit the system as a whole.

As part of the project the team designed and deployed bicycle-mounted pollution sensors to gather data about Southampton’s air quality. This type of system has benefits over fixed sensor systems, with the potential to deploy many more sensors and to incentivise people to take specific routes for greater geographical coverage.

The data could be used in real time to divert traffic to reduce pollution levels, or to produce routing recommendations for cyclists to help them avoid areas of high pollution. It could also empower citizens to lobby local decision makers to put plans in place to improve air quality. Another stream of this research saw the development of an intelligent waste bin that can sense the weight, temperature and gas emissions of its contents and identify what has been discarded. This technology could be used to gather data on what gets thrown away, encourage people to reduce food waste and prompt the sorting of recyclable materials.

Home-based activity monitoring

Another application of Southampton’s pioneering work on wearable, flexible IoT sensors is activity monitoring to ensure the wellbeing of older people or those with long-term health conditions, while enabling them to live as independently as possible. This involves interpreting data from sensors worn on the body to identify a person’s everyday activities, allowing carers or clinicians to check whether they are eating regularly, moving around in the usual way or taking medication, without the use of intrusive cameras.

Our researchers developed wearable sensors for activity monitoring as part of a large EPSRC-funded project called SPHERE (Sensor Platform for HEalthcare in a Residential Environment). Since then, they have continued to improve the integration of sensors so that they sit invisibly within clothing, achieving the same functionality as wristband sensors.

Smarter, greener transport

The IoT will enable completely new forms of transportation, including connected vehicles that work together for optimum efficiency, and electric autonomous vehicles (AVs) that will make public transport greener and more user friendly. The AV transport systems of the future could be much more flexible, with shuttle bus or ridesharing schemes that can adapt their routes and timetables dynamically according to demand.

Our researchers are tackling some of the inherent challenges associated with autonomous and connected vehicles. Projects include the design of intelligent control systems for teams of connected AVs to enable them to travel with minimum energy consumption while maintaining a safe distance, and designing intelligent agents to help smart car drivers negotiate data use agreements when information is shared between vehicles. Our researchers are also designing AI algorithms to make the best use of the road network, through approaches such as platooning (vehicles travelling as a group) and intersection control, efficient route planning to keep traffic flowing, and the optimisation of ride-sharing schemes.

Another aspect of AV research is the design of smart algorithms that enable automated ride-sharing or smart bus services to operate in the most efficient way. The algorithms take into account people’s individual needs – for example whether they need to arrive at their destination at a specific time or can be more flexible – and can make decisions about which vehicles pick up which people and the routes they take. Work has also been undertaken on how best to incorporate the needs of disabled or older people into smart transport systems.

An important aspect of this research is exploring how people can be incentivised to report their transport needs truthfully in order to optimise the efficiency of the system overall. Southampton is leading the way in the use of game theory – a way of modelling the behaviour of self-interested users, or agents (which could be software or people) within a system – to design systems that incorporate these types of incentives. For example, in an automated taxi service, someone might accept the slight inconvenience of picking up another passenger who wants to go in the same direction in return for a financial discount.

Work is also in the pipeline to examine how to reduce congestion by incentivising people to take alternative routes by offering small financial rewards. The idea is to design a tool that would show different routes and calculate the incentives, enabling people to opt for a reward for taking a longer but less busy route.

Further investigation of incentive mechanisms to optimise smart transportation systems is being undertaken as part of Citizen-Centric AI

“There are lots of smart home-based monitoring systems around, but they tend to stop at the person’s front door. In future they could be extended beyond the home to the smart city environment, using sensors embedded into fabrics so all the person has to do is get dressed.”

Professor Steve Beeby Professor in Smart Electronic Materials and Systems

“Once system and reduce congestion. But it’s a very dynamic IoT network and involves a lot of communications between vehicles. My research includes looking at the formation of platoons at intersections and whether algorithms that work across multiple intersections could remove the need for traffic lights.”

Professor Enrico Gerding Head of Agents, Interaction and Complexity

Systems15 This is a five-year project funded by UK Research and Innovation through a Turing AI Acceleration Fellowship – a prestigious award made as part of the UK government’s AI strategy.

Monitoring the health of critical infrastructure

Southampton has a long history of designing IoT systems to monitor the health of the transport infrastructure. Through the successful spin-out company Perpetuum, for example, sensor and energy harvesting technology designed by our researchers is now deployed in the rail industry for real-time monitoring of train axle bearings, wheels and track. This enables rail companies to plan maintenance according to need, ensuring safety and reliability across the network and reducing costs.

Another focus for infrastructure monitoring research is the electricity grid. With the increasing electrification of transport and the integration of more renewable energies into the grid, getting system-wide data about the condition and capacity of the electricity infrastructure is becoming even more important. However, the grid relies on high-voltage underground cables, and typically once they are laid it’s difficult to find out whether they are working efficiently or at risk of failing. Our researchers are developing smart materials sensors for condition monitoring which could make this possible and help to ensure a more stable and efficient power network.

The deployment of smart sensors along high-voltage cables would enable data to be gathered on their temperature and environmental conditions, which would in turn indicate whether the cable was being underused or overloaded, and whether there were any faults or problems. The sensors themselves are self-powered, generating energy from the temperature gradient created by the heat of the cable. The ultimate aim is to deploy a network of sensors that can share data between themselves, make decisions and communicate to a centralised control system to help the network run more efficiently and reliably.

“The IoT is exciting because if we can put inexpensive sensors that can talk to each other across the power network, it will give us new insights where previously we have only been able to make assumptions – for example whether too much energy is being pushed through highvoltage cables creating a hotspot that could lead to failure, or whether a cable has capacity to carry more power.”

Dr Thomas Andritsch Associate Professor in Electrical Power Engineering

Managing the demand for power

As EVs become the norm, the need to charge batteries will put unprecedented pressure on the power network. Our researchers have designed algorithms that take users’ needs into account to schedule charging in a way that avoids grid overload.

However, as with smart transport, this type of system relies on people being truthful about their needs – for example whether they have to charge their car in time for a daily commute, or whether their schedule is more flexible. Once again our researchers are using game theory to look at how incentives can be used to encourage people to be honest about their needs, by offering financial incentives if they can be more flexible about when they charge their car.

This work is progressing further as part of the Citizen-Centric AI Systems project, which includes work with industry partners, including EA Technology, Siemens Mobility and Jaguar Land Rover, to test new mechanisms in real EV charging systems.

“The aim is that our research will feed into the systems of the future as EVs become more widely used. Working with industry partners means we can make sure it’s possible to deploy it in real systems.”

Professor Sebastian Stein Professor in Agents, Interaction and Complexity

15 https://ccais.soton.ac.uk

Another stream of research is looking at ways to use EV batteries to smooth out fluctuations in electricity supply and demand. When EVs are parked and plugged in they can be used as a huge storage device that can be discharged as well as charged. Drawing on this power could help resolve one of the challenges of using renewable energies – the unpredictable nature of wind and solar supply. Our researchers have examined the possibilities of vehicle-to-grid integration using IoT technology and the design of automated algorithms that can trade with the grid on behalf of consumers.

Making smart energy systems more secure

An emerging trend enabled by smarter energy grids is the evolution of transactive energy, where ‘prosumers’ – consumers who also produce energy, perhaps through solar panels on their roof – sell energy directly to other consumers. The IoT provides the technology to gather information and automate trading decisions, but can also open up new security issues, such as the possibility of forged transactions.

Using blockchain technology our researchers have designed and prototyped an infrastructure for secure and reliable peer-to-peer energy trading. The research was part of BlockIT (Blockchain-empowered Infrastructure for IoT), a project funded by the EPSRC.

Supporting smart city systems

As uptake of smart city systems grows, more and more IoT devices will be deployed, creating huge amounts of data. However, typically the devices themselves won’t have the capacity to process and analyse the data they produce. Issues such as latency and the limits of wireless bandwidth capacity means sending data to the cloud for processing may not always be the ideal solution.

Instead, our researchers are looking into the use of ‘fog’ computing – a layer of infrastructure closer to the ‘edge’ (where the IoT devices are). The fog layer, while not as powerful as the cloud, could take on some of the processing to improve speed and free up bandwidth.

As there is currently no pervasive infrastructure of fog devices, the research is focusing on the use of blockchain to establish an independent and transparent entity to support a federated system through which fog service providers can operate.

As well as being secure and independent, blockchain offers some built-in intelligence, enabling it to allocate fog resources in the most efficient way to the applications that require them.

In addition, algorithms designed by our researchers to manage and process data in dynamic scenarios could contribute to the smooth running of smart city IoT systems. The AI and machine learning techniques were developed as part of Distributed Analytics and Information Science International Technology Alliance (DAIS ITA)16, a joint UK/US governmentfunded project focusing on the use of IoT in fast-changing and resource-constrained environments. The algorithms enable systems to autonomously distribute computational tasks according to system priorities and available resource – for example, diverting capacity to the traffic management system in the event of an incident on the road, and reducing it for less critical applications.

Addressing privacy and security issues

Whether collecting information about people’s daily lives or controlling essential infrastructure, the increasing use of IoT devices creates new privacy and security issues.

Our researchers are developing new ways to put users in control of personal data generated by IoT devices so they can specify which aspects of their data other entities can access and how it can be processed.

In the realm of IoT security, we are working to outsmart hackers by defining, identifying and defending against spatial-temporal propagation attacks – where an adversary accesses one IoT device in order to initiate a cascade of failure across a network over time. This work encompasses a range of applications including smart energy meters, vehicle-to-vehicle communications and sensors in offshore oil systems.

Other developments in IoT security include new techniques to remotely detect whether a device has been tampered with, and ways to identify and patch potential vulnerabilities in industry control systems.