Wearable and Autonomous Computing for Future Smart Cities: A Platform Grant

Lead Research Organisation: University of Southampton
Department Name: Sch of Electronics and Computer Sci

Abstract

The focus of this Platform Grant is the combination of wearable systems networked with smart city and building management systems, and the processing of the collected data. The Platform will cover infrastructure and devices and will require innovation in hardware and software in order to realise the goal of a people centred smart city. The topic of the Platform and the underpinning research themes require a multidisciplinary approach that can be provided by the unique expertise of the research group in the Department of Electronics and Computer Science at the University of Southampton.

Applications of the technologies will enable effective collection, communication, and processing of this data that, in turn, will enable applications such as crowdsensing activities or allow, for example, the provisioning of ultra-personalised services for users to enrich their experience as they navigate their environment, and engage in work and leisure. Such a capability would allow them to purchase personalised services (e.g. healthcare, entertainment, fashion), enable participatory sensing initiatives to support smart city applications (e.g. real-time traffic updates, pollution monitoring), or help coordinate evacuations during major disasters. Combining wearable sensors with intelligent building management systems can provide distributed sensing of the environment within the building as well as monitoring user activity and wellbeing in order to improve the effectiveness and efficiency of building services (e.g. heating, and ventilation). Such a capability will also become an important research tool to aid in our understanding of building occupant behaviour.

Key research challenges exist in developing user-friendly ubiquitous energy-constrained wearable systems and interfacing these reliably and securely with external networks. Wearable sensors and devices will place individuals at the centre of the smart city and enable a step change in the level of interaction possible. It is essential to develop robust, agile algorithms and mechanisms that can cope with potential failures that may arise in the sensors and networks. Combining AI with sensors enables intelligent interacting agents that can form multi-agent systems exceptionally capable of solving problems and interpreting information. Such developments will underpin autonomous systems, benefit the burgeoning Internet of Things (IoT) and enable the next generation of smart city applications. A flexible funding Platform underpinning the group in these crucial areas of expertise will enable pioneering work and the pursuit of emerging opportunities.

Planned Impact

The development of robust and reliable networked wearable sensors across a smart city environment will benefit individuals, society and the economy in a number of ways. For example, the development of new wearable sensors will facilitate improved health that when combined with a smart city infrastructure could facilitate real-time health monitoring beyond the normally defined ambient assisted living environment (i.e. the home) and into the city. This will enable data to be gathered under a much wider range of scenarios, further improving the provision of healthcare services. Wearable sensors for monitoring the environment and networking these within a smart city infrastructure will enable a step change the amount and variety of data captured as well as facilitating increasingly popular new methods for gathering data such as crowd sourced sensing activities (e.g. in pollution monitoring). The impact in both of these examples will be further enhanced by the combination with AI to form multi-agent systems that can interpret the data and, where applicable, recommend actions. It will facilitate the interaction of the individual with their surroundings, enabling the provision of ultra-personalised services. The ability to act on the gathered data and provide, or highlight, highly informed opportunities for individuals to purchase goods and services will lead to new commercial opportunities.

The work will benefit both software and hardware designers and developers by defining and informing the next generation of smart city and wearable systems. There is the potential to expand the use and capability of existing smart city networks and infrastructure but also to drive improvements in underpinning electronic and systems design in both wearable and smart city domains. Applying low energy based solutions to devices, circuits, sensors and communications will both improve existing products and enable new opportunities. This is a particular requirement for wearable devices and the wider Internet of Things where the supply of energy is a practical constraint in the majority of potential applications. Improved energy efficiency in computation, sensing and communication between the wearable and smart city infrastructure is central to our vision. Specific industrial beneficiaries include the project partners ARM who are heavily involved in designed electronic systems for IoT applications. For example, Southampton has a strong relationship with ARM through its ARM-ECS Research Centre (Director: BAH, Technical Manager: GM), as recognised by the award of "University Research Group of the Year" in the National Microelectronics Institute (NMI) Industry Awards 2015. We have discussed this proposal with senior colleagues at ARM, and they have shown strong interest in supporting the project through staff time for technical discussions and membership of the project's advisory board, and internships for researchers. Other relevant companies include Phillips, Texas instruments, Intel and Microsoft all of whom are known to be researching low energy systems and applications such as ICT based healthcare solutions. Project partner Mayflower have developed a control system for streetlights based upon a wireless network providing an example infrastructure for the smart city environment. This research will enable improved utilisation of such assets and the company are supporting the research with hardware modules to expedite advances and ensure relevance. NquiringMinds Ltd will find new applications and case studies for their Trusted Data Exchange and InterliNQ: IOT Hub products.
 
Description Substantial progress has been made in a number of aspects relating to the application of wearable electronics in a smart city environment. In particular, the design of flexible textiles based antennas for communication and power transfer has been developed and several examples of systems working at up to 5G frequencies have been demonstrated. Wearable pollution sensing gas sensors have also been demonstrated.
Exploitation Route Building wireless e-textile systems that monitor and interact with their surroundings.
Sectors Electronics,Environment,Healthcare,Leisure Activities, including Sports, Recreation and Tourism

 
Description Flexible Hybrid Thermoelectric Materials
Amount £609,079 (GBP)
Funding ID EP/T026219/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 10/2020 
End 09/2023
 
Title Data Supporting the Article: Dual-Polarized Wearable Antenna/Rectenna for Full-Duplex and MIMO Simultaneous Wireless Information and Power Transfer (SWIPT) 
Description Dataset supporting the Article "Data Supporting the Dual-Polarized Wearable Antenna/Rectenna for Full-Duplex and MIMO Simultaneous Wireless Information and Power Transfer (SWIPT)" in the IEEE Open Journal of Antennas and Propagation. Article DOI 10.1109/OJAP.2021.3098939 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://eprints.soton.ac.uk/451110/
 
Title Data suppporting "Acetonitrile-free organic electrolyte for textile supercapacitor applications" 
Description Dataset supporting the article: "Acetonitrile-free organic electrolyte for textile supercapacitor applications", published in Journal of the Electrochemical Society 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://eprints.soton.ac.uk/450866/
 
Title Dataset supporting the journal article "Pragmatic Memory-System Support for Intermittent Computing using Emerging Non-Volatile Memory" 
Description Sivert T. Sliper, William Wang, Nikos Nikoleris, (2022) Pragmatic Memory-System Support for Intermittent Computing using Emerging Non-Volatile Memory. (Accepted/In press) In: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 14 p All files are in csv or ods format, both of which can be opened in spreadsheet programs like Libre Office Sheet or proprietary alternatives such as Microsoft Excel. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://eprints.soton.ac.uk/456087/
 
Title Millimeter Wave Power Transmission for Compact and Large-Area Wearable IoT Devices based on a Higher-Order Mode Wearable Antenna Data 
Description Data supporting the article "Millimeter Wave Power Transmission for Compact and Large-Area Wearable IoT Devices based on a Higher-Order Mode Wearable Antenna" in the IEEE Internet of Things Journal. Article DOI 10.1109/JIOT.2021.3107594 Dataset includes the direct comaprison of mmWave and UHF power transmission, the DC power tables, and the simualted and measured antenna radiation properties. 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://eprints.soton.ac.uk/451111/
 
Title Millimeter Wave Power Transmission for Compact and Large-Area Wearable IoT Devices based on a Higher-Order Mode Wearable Antenna Data 
Description Data supporting the article "Millimeter Wave Power Transmission for Compact and Large-Area Wearable IoT Devices based on a Higher-Order Mode Wearable Antenna" in the IEEE Internet of Things Journal. Article DOI 10.1109/JIOT.2021.3107594 Dataset includes the direct comaprison of mmWave and UHF power transmission, the DC power tables, and the simualted and measured antenna radiation properties. 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://eprints.soton.ac.uk/451111/
 
Title UHF RFID Ice Detection and Monitoring Data 
Description Data supporting the article "Wireless Ice Detection and Monitoring usingFlexible UHF RFID Tags" submitted for publication in the IEEE Sensors Journal. Article DOI 10.1109/JSEN.2021.3087326 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://eprints.soton.ac.uk/451109/