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Wireless Sensor Networks (WSNs) consist of small nodes with sensing, computation, and wireless communication capabilities. Wireless Sensor Network (WSN) is a promising data mining solution for precision agriculture. Instrumented with wireless sensors, it will become available to monitor the plants for real time, such as air temperature, soil water content, and nutrition stress. This real time information...
Intrusion detection is prominently important for civil and military applications in wireless sensor networks (WSNs). It is defined as the mechanism to detect moving intruder(s) by single-sensing or jointly-sensing detection. To date, related works focus on the problem of network configuration for detecting intruder(s) within a pre-specified time/distance threshold by assuming a straight line intrusion...
The main objective of sensor deployment problem in Wireless Sensor Network (WSN) is to use minimum number of sensor nodes with given sensing range that can cover any target in the coverage area to monitor the environment. The optimal sensor deployment enables accurate sensing information on target behavior with minimum sensing range and number of sensor nodes. The target coverage terrain in a locality...
The Voronoi diagram is the one of most fundamentals in computation geometry. The coverage control, especially the barrier coverage, will benefit from this diagram. Using the Voronoi diagram, the coverage holes can be detected in short time. In the lax demands which only include the influence of two neighbor sensors, the minimal exposure track based on the Voronoi can approach the optimal. But, because...
Deployment of sensors and routing inside an irregular region is one of the most fundamental challenges of Wireless Sensor Networks. The performance of an effective and efficient sensor network is highly related to the proper configuration and design of the network and effective communication between the sensors deployed. In real scenario, the area that needs to cover, may suffer from natural geographical...
A test-scale wireless chemical sensor network (WCSN) has been deployed within a controlled environmental chamber (EC). The combined signals from the WCSN were used to initiate a controllable response to the detected chemical event. When a particular sensor response pattern was obtained, a purging cycle was initiated. Sensor data were continuously checked against user-defined action limits, to determine...
Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for acquiring sparse or compressible signals. Instead of taking N periodic samples, we measure M ?? N inner products with random vectors and then recover the signal via a sparsity-seeking optimization or greedy algorithm. A new framework for CS based on unions of subspaces can improve signal recovery by including dependencies between...
In this paper, asymmetrical write-assist cell virtual ground biasing and positive feedback sensing keeper schemes are proposed to improve the read static noise margin (RSNM), write margin (WM), and operation speed of a single-ended read/write 8T SRAM cell. A 4 Kbit SRAM implemented in 90 nm CMOS technology achieves 1 uW/bit average power consumption at 6 MHz, Vmin of 410 mV at 6 MHz, and 234 MHz maximum...
The high cost of communication vis-a-vis computation cost necessitates efficient aggregation in wireless sensor networks. This paper proposes and evaluates two different clustering techniques, FAMNN and DBA. The first approach based on adaptive resonance theory whereas the second approach is based on density based clustering of data. The first technique, FAMNN is based on fuzzy ART and fuzzy ARTMAP...
For monitoring critical applications, the K-coverage configuration is extensively exploited to ensure that each location is covered by at least K active sensor nodes. The well-known K-coverage eligibility (KE) algorithm ensures that a monitored area is K-covered, but incurs a considerably high computation cost. Several approximate algorithms accomplish the K-coverage configuration at low cost, but...
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