Energy-efficient event detection in 3D wireless sensor networks

Abstract

Event detection techniques are crucial for environmental monitoring and object tracking applications in wireless sensor networks. Event detection requires sensor readings to be collected from multiple sensors, and as sensors have limited resources, their readings should be retrieved efficiently. Existing aggregation-based event detection methods, however, require all sensors in the network to transmit their readings, which results in high energy consumption for the network. We propose an energy-efficient event detection technique for estimating the state of the whole environment based on only some of the sensor readings and use a contour map to represent the outline of the environment. To detect events in 3D environments, we modify an existing 2D contour mapping algorithm, extending it for 3D environments. By simulation, we show how our event detection technique is more energy-efficient than existing solutions that take readings from all sensors. We evaluated our method from the point of energy efficiency and found that it improves the energy efficiency of event detection in 3D wireless sensor networks.