Data Collection Performance in WSNs by Pattern Variation Discovery

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Focusing on the optimization of data collection in Wireless Sensor Networks (WSNs), this book addresses the challenge of minimizing the robot's traveling distance, likening it to the Travelling Salesman Problem with Neighborhoods. It explores the deployment of tiny sensor nodes for monitoring and reporting events, emphasizing the detection of irregularities in sensor data. By introducing a novel approach called pattern variation discovery, it aims to identify abnormal events and faulty sensors through effective modeling of sensor data over time or space.