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Data Transmission Reduction in Wireless Sensor Network for Spatial Event Detection

Wireless sensor networks have found many applications in detecting events such as security threats, natural hazards, or technical malfunctions. An essential requirement for event detection systems is the long lifetime of battery-powered sensor nodes. This paper introduces a new method for prolonging the wireless sensor network’s lifetime by reducing data transmissions between neighboring sensor nodes that cooperate in event detection. The proposed method allows sensor nodes to decide whether they need to exchange sensor readings for correctly detecting events. The sensor node takes into account the detection algorithm and verifies whether its current sensor readings can impact the event detection performed by another node. The data are transmitted only when they are found to be necessary for event detection. The proposed method was implemented in a wireless sensor network to detect the instability of cargo boxes during transportation. Experimental evaluation confirmed that the proposed method significantly extends the network lifetime and ensures the accurate detection of events. It was also shown that the introduced method is more effective in reducing data transmissions than the state-of-the-art event-triggered transmission and dual prediction algorithms.
- University of Silesia Poland
- Institute of Computer Science Poland
- University of Silesia Poland
- Polish Academy of Sciences Poland
lifetime, Chemical technology, cargo monitoring, TP1-1185, 003, Article, event detection, wireless sensor network, Electric Power Supplies, energy consumption, transmission reduction, Wireless Technology, Algorithms
lifetime, Chemical technology, cargo monitoring, TP1-1185, 003, Article, event detection, wireless sensor network, Electric Power Supplies, energy consumption, transmission reduction, Wireless Technology, Algorithms
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).8 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
