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Wireless Sensor Networks—Node Localization for Various Industry Problems

Fast and effective monitoring following airborne releases of toxic substances is critical to mitigate risks to threatened population areas. Electrically powered systems in industrial settings require monitoring of emitted electromagnetic fields to determine the status of the equipment and ensure their safe operation. In situations such as these, wireless sensor nodes (WSNs) at fixed predetermined locations provide monitoring to ensure safety. A challenging algorithmic problem is determining the locations to place these WSNs while meeting several criteria: (1) to provide complete coverage of the domain; (2) to create a topology with problem-dependent node densities; and (3) to minimize the number of WSNs. This paper presents a novel approach, advancing front mesh generation with constrained Delaunay triangulation and smoothing (AFECETS) that addresses these criteria. A unique aspect of AFECETS is the ability to determine WSN locations for areas of high interest (hospitals, schools, and high population density areas) that require higher density of nodes for monitoring environmental conditions, a feature that is difficult to find in other research work. The AFECETS algorithm was tested on several arbitrary shaped domains. AFECETS simulation results show that the algorithm provides significant reduction in the number of nodes, in some cases over 40%, compared with an advancing front mesh generation algorithm; maintains and improves optimal spacing between nodes; and produces simulation run times suitable for real-time applications.