The project iSense: make sense of nonsense is an European funded project that aims to develop intelligent data processing methods for analyzing and interpreting the data such that faults are detected (and whereas possible anticipated), isolated and identified as soon as possible, and accommodated for in future decisions or actuator actions. The problem becomes more challenging when these sensing/actuation systems are used in a wide range of environments which are not known a priori and, as a result, it is unrealistic to assume the existence of an accurate model for the behavior of various components in the monitored environment. Therefore, this project will focus on cognitive system approaches that can learn characteristics or system dynamics of the monitored environment and adapt their behavior and predict missing or inconsistent data to achieve fault tolerant monitoring and control.

This project will develop the iSense Platform, which will consist of a set of intelligent agents, integrated with the sensors, actuators and feedback control system for making the overall monitoring and control system more robust, adaptive and fault-tolerant to sensor/actuator faults and system faults or abnormalities in the environment. The developed prototype of the iSense Platform will be validated for the intelligent building application domain, however, the formulation, tools and methodologies developed will be transferable to other application domains such as water distribution networks, power transmission and distributions grids and more.


The iSense consortium spans Europe and includes a range of leading universities, research labs and industrial partners. The partners are:

Institution Research Group Country
University of Cyprus KIOS Research Center Cyprus
Politecnico di Milano Information Processing Systems Group Italy
University of Birmingham Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA) United Kingdom
STMicroelectronics Advanced Robotics Lab Italy
Universidad Politecnica de Catalunya Advanced Control Systems Research Group Spain

Tasks in Birmingham

The University of Birmingham's principal task is to develop a set of adaptation and learning algorithms that can be incorporated into the cognitive fault diagnosis and fault tolerant control schemes. The use of adaptation and learning aims to discover and exploit spatial-temporal relations that exist in collected data. These relations, which will be refined online during operation of the intelligent sensing system, will enhance robustness and tolerance to fault events and other unexpected field situations. Neural network ensemble learning, adaptive classification methods and virtual sensor/actuator schemes will be developed in the context of cognitive fault diagnosis.

The official website for the iSense project can be found here.