WELCOME

The Internet of Things is transforming all aspects of our lives, from entertainment, social engagement, and healthcare, to business, industry, and achieving Net Zero targets. This transformation has been underpinned by advances across the spectrum of electronics and computer science, for example enabling enhanced connectivity, intelligence, battery-life, ambient sensing, and computational ability.

The Centre for IoT and Pervasive Systems (C-IoT) is a hub for Internet of Things research and education in the School of Electronics and Computer Science at the University of Southampton. Established two decades ago as the Pervasive Systems Centre, today’s Centre remains at the forefront of multidisciplinary IoT research. We aim to encourage collaboration, spark new ideas and share learning to advance the next generation of IoT technologies.

We draw on the breadth of expertise within the School of Electronics and Computer Science and the wider University, bringing together specialists in sensor technology, energy harvesting, wireless communication, data management, artificial intelligence, and the many other technologies which contribute to the IoT stack. Our researchers seek solutions to real-world problems, working with partners in industry and academia to maximise impact. We collaborate with companies and other stakeholders from a wide range of sectors including health, manufacturing, construction, energy, defence, automotive and aerospace.

This magazine provides a snapshot of research highlights across the spectrum of our research in IoT, and provides insight into some of the key challenges and accomplishments in this domain.

Professor Geoff Merrett Head of Centre for IoT and Pervasive Systems School of Electronics and Computer Science

Sensor Technologies

Southampton has been at the forefront of sensor research for several decades – before the evolution of the IoT we were advancing technologies in areas such as thick-film printed sensors and micro-electromechanical systems (MEMS) – the microchipbased sensor systems that are now embedded in every smartphone – which have since become integral to the IoT. Our researchers also conducted early work on networking sensors together to gather richer and more robust data, a principle that underpins today’s IoT systems.

While numerous types of sensor are now commercially available and widely used in the IoT, there is still room for innovation and optimisation. Our researchers are continuing to investigate new materials and techniques for sensing, and finding ways to measure the previously unmeasurable.

Sensor technology research comes with a number of considerations and constraints. Sensors must be the right size for their application – this could mean small enough to be embedded into a credit-card sized system, or fabricated at the nanoscale for molecular-level sensing. For mass deployment, they must be cheap to produce and have low power requirements. Because they are likely to be densely deployed, a lower accuracy may be tolerated when compared with other systems. However, in the case of niche, safety-critical applications, cost is less of a consideration and accuracy is paramount.

Flexible, wearable sensors

Southampton has a track record of groundbreaking research into sensors for smart fabrics.

The development of wearable sensors presents particular challenges – they must be very small, flexible, durable and potentially washable, as well as being able to maintain their sensitivity when integrated into a textile.

Our researchers have discovered new ways to tackle these challenges, for example by developing active inks that can be printed onto fabrics, ultra-thin dyes that can be incorporated into textiles, temperature-sensing filaments that can be woven into the structure of a fabric, and methods to encapsulate textile-based gas sensors to improve their durability without affecting their sensitivity.

This field of research opens up a huge range of potential IoT applications, particularly in fields such as fitness and healthcare, helping people maintain their independence in later life, and smart city applications where wearable sensors could enable crowdsourced data on measurables such as air quality.

Printed sensors

Another longstanding area of research at Southampton is the development of sensor systems that use active ‘inks’ to detect or respond to things in the environment. These are fabricated using a screen-printing process, making them much simpler and to produce than traditional integrated circuits, which require expensive cleanroom facilities.

One such process uses a substrate of ceramic, printed with silver as the conducting material, most of which can then be isolated with a layer of glass. The exposed active area is then covered with a printed layer of the active sensing material, which has been mixed with powdered glass and liquid to form an ink. This is then fired at high temperature to produce a sintered structure. Robust, reliable and cheap to produce, these sensors are ideal for environmental and agricultural settings. They have been used to detect salt levels in farmland and could be tailored for many other types of pollution monitoring.

Another example of a screen-printed sensor being developed at Southampton is a motion sensor for use in healthcare. The sensor monitors the respiratory rate of patients – either in hospital or at home – transmitting data to clinicians and enabling them to respond to any significant changes in a patient’s breathing rate.

Sensors for extreme conditions

Our researchers are also expanding the boundaries of what can be measured by designing sensors for harsh conditions – for example, the extreme heat of a jet engine. Although turbine blades will melt at temperatures below 1,400 degrees Celsius, they actually operate at temperatures above this in order to maximise the thermal efficiency and power output of the engine. To make this possible, cooled air is pumped through holes in the blades, creating a layer of insulation between the blade and the hot gas flowing over it. If the air flow fails, the turbine blade will melt, so being able to monitor the temperature of the blade while the plane is in flight would be incredibly useful. However, it is a big challenge, as most electronics will only operate upto around 120 degrees Celsius.

Our researchers are looking for a solution in the form of acoustic sensors. The sensors send acoustic waves over the turbine blade surface to measure the speed of sound. The speed of sound is very temperature dependent, enabling the researchers to infer temperature changes from the measurements. The use of acoustic waves means the actual sensors and electronics can be placed away from the intense heat of the turbine and early results show they have the potential for taking measurements with a high level of precision. https://www.e-textiles.ecs.soton.ac.uk

Other specialist sensors designed specifically for extreme conditions include custom-built, super-robust sensors used to monitor movement and pressure beneath glacial ice.

Nanoscale sensors

Another branch of sensor research is looking at novel ways to detect microscopic targets. Working in the University’s state-of-the-art cleanrooms, researchers are developing sensor systems that take advantage of the properties of zinc oxide nanowires. A cheap, plentiful material with low environmental impact, zinc oxide reacts readily to positive or negative charges. By analysing these reactions it’s possible to identify particular micro or nanoscale targets, such as pollution particles or abnormalities in DNA that could indicate disease. Our researchers are focusing on biomedical applications, but the technology could also be adapted for environmental and other types of sensing.

enable the discovery, sharing and processing of data at the large scale required by the IoT, while reducing the security risks and access issues associated with centralised systems.

A benefit of centralised data stores is that they make it easy to apply machine learning and AI techniques to datasets. However, there is a risk that centralised stores become silos where the data can only be processed by the silo owner, which in turn limits the innovation potential of that data. In addition, central data stores present a greater cyber security risk. To overcome this, our researchers are looking at secure federated approaches to machine learning on IoT data.