S4Systems

Tuesday 12th January 2016
Quartet for S4 systems

Glasgow, St Andrews, Liverpool and London Universities combine to work on unifying science for smarter sensor based systems.

Professor Muffy Calder, head of the College of Science and Engineering at the University of Glasgow and Professor of Formal Methods in Computing Science, will lead the project.

Noting that sensors are becoming ever more common place in all kinds of devices, she said: “By the end of the project the team will have answered a number of fundamental questions about how to design, deploy and reason about sensor based systems, developing new principles, techniques and tools, alongside simulations and physical sensor testbeds for experimentation.

They will also demonstrate the applicability and effectiveness of the new techniques across a range of applications”. The project is supported by a grant from the Engineering and Physical Sciences Research Council and will run until 2021.

The team from Glasgow consists three  women STEM exemplars  of Professory Muff Calder,  Alice Miller and Oana Andrei.  From St Andrews comes  Professor Simon Dobson (right) and Lei Fang.

 The Liverpool  the team comprises (left) Michael Fisher  with (two further STEM exemplars)  Clare Dixon  (below left) joined by Professor Julie McCann from London (below right).

S4 will be driven and validated by end-user and experimental applications involving the following organisations: ABB, British Geological Survey, CENSIS, Freescale, Jacobs, Rolls-Royce, Scottish Canals, Thales, Topolytics, Transport Scotland.

Sensor systems are embedding everywhere: in transportation and lighting, to smart tags and flooded fields, providing information and aiding real-time decision-making and actuation. Smart cities, IoT, big data, autonomous vehicles will all depend on robust sensor systems that can be trusted to deliver useful, timely and reliable information.

Extracting information is far from straightforward: sensors are noisy, they de-calibrate get  misplaced, moved, compromised, and  degrade over time, both individually and as a collective networks. Uncertainty pervades the physical and digital environments in which the systems operate. There is increasing need to add more autonomy and intelligence, yet we understand very little about programming in the face of such pervasive uncertainty that cannot be engineered away. 

How can we be sure that a sensor system does what we intend, in a range of dynamic environments? How make such a system “smarter”? How connect the stochastic nature of environments, to the continuous nature of physical systems, and the discrete nature of software? Currently we cannot answer these questions because we are missing a science of sensor system software. 

The S4 programme will develop a unifying science, across the breadth of mathematics, computer science and engineering, that will let developers engineer for  uncertainty and ensure that the systems and the information provided is resilient, responsive, reliable, statistically sound and robust. 

The vision is smarter sensor based systems in which scientists and policy makers can ask deeper questions and be confident in obtaining reliable answers, so the programme will deliver new principles and techniques for the development and deployment of verifiable, reliable, autonomous sensor systems operating in uncertain, multiple and multi-scale environments.

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