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Energy-efficient data gathering in randomly deployed and asynchronized sensor networks employing probabilistic duty cycling and compressive sensing


Background: Wireless Sensors Network (WSN) is a network that consists of spatially distributed autonomous sensors that monitor environmental conditions such as temperature humidity vibrations sound pressure etc. Prominent applications of WSNs are: Environmental monitoring seismic detection acoustic detection military surveillance inventory tracking and medical monitoring etc. Each sensor belonging to the network also known as node monitors the conditions and relays this information to the main node. The network may consist of hundreds to thousands of such sensors that are energized by external power source or independent batteries embedded on each sensor. Therefore substantial amount of power is used in the operation of a WSN. Technology Description: An energy-efficient data aggregation scheme for Wireless Sensors Networks has been developed. The technology targets the two main issues of WSN- data compression and sleep scheduling. The scheme is based on the integration of compressive sensing and probabilistic sleeping of nodes which makes the overall system energy efficient. Applications: 1) Agriculture 2) Military 3) Environment monitoring 4) Suspicious activity detection 5) Livestock


1) Significantly reduces energy consumption 2) Complicated sleep scheduling and synchronization techniques are not required

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