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Energy Harvesting Wireless Sensor Networks

EPSRC awards £600,000 for new research

Congratulations to Dr Miguel Rodrigues, Dr Yiannis Andreopoulos and Dr John Mitchell from the department whose EPSRC research proposal (EP/K033166/1) in partnership with the University of Cambridge has received funding. The full title of their proposal is "Efficient Energy Management in Energy Harvesting Wireless Sensor Networks: An Approach Based on Distributed Compressive Sensing." UCL is the lead institution and will receive approximately £600,000.

Dr. Miguel Rodrigues, Dr. Ioannis Andreopoulos and Dr. John Mitchell have been awarded £595,848.15 from the EPSRC to investigate new sensing schemes to unlock energy neutrality in energy harvesting wireless sensor networks, in collaboration with the Cambridge University Computer Laboratory. The grant total is £878,448.15 over 36 months.

Future deployments of wireless sensor networks infrastructures are expected to be equipped with energy harvesters to substantially increase their autonomy and lifetime. However, it is also widely recognized that the existing gap between the sensors’ energy harvesting supply and the sensors’ energy demand is not likely to close in the near future due to limitations in current energy harvesting technology, together with the surge in demand for more data-intensive applications. Hence, perpetually operating wireless sensor networks are currently impossible to realize for data intensive applications.

With the continuous improvement of energy efficiency representing a major drive in wireless sensor networks research, the major objective of this project is to develop transformative sensing mechanisms, which can be used in conjunction with current or upcoming energy harvesting capabilities, in order to enable the deployment of energy neutral wireless sensor networks with data gathering rates that are substantially higher than the current state-of-the-art.

The theoretical foundations of the proposed research are the emerging paradigms of compressive sensing and distributed compressive sensing as well as energy- and information-optimal data acquisition and transmission protocols. These three elements offer the means to tightly couple energy demand to the energy supply in wireless sensor networks in order to achieve the breakthroughs in data gathering capability.

The proposed research is also supported by various partners, which include the Cambridge Innovation and Knowledge Centre for Smart Infrastructure and Construction, Thales, Fujitsu Laboratories of Europe, STMicroelectronics and AquaMW.