A Method to Construct an Indoor Air Pollution Monitoring System Based on a Wireless Sensor Network

Abstract

Wireless Sensors Networks (WSNs) are currently receiving much research interest due to their wide-ranging use is a number of different fields. In the current study, a system based on a WSN is proposed that can monitor indoor air pollution in several public spaces, such as subway stations, offices, schools, and hospitals. The proposed system uses integrated sensors in mobile phones, moving from a stationary nodes model to a mobile nodes model. The main objective of building this system is to provide full coverage of the target area. To achieve this goal, the system is simulated by MATLAB and the following algorithms are applied: Particle Swarm Optimization (PSO) to maximize the coverage in the region of interest (RoI), Voronoi Diagram (VD) to detect holes in the coverage, and finally the Point in Polygon (PiP) algorithm to heal the holes in the coverage. The application of the algorithms mentioned above has been very effective as PSO has increased the coverage rate of the monitoring area to 100%. The VD allowed us to define the exact location of coverage holes whilew the Point in Polygon algorithm allowed us to heal the holes and find the remaining sensors in order to improve network coverage. This enabled us to achieve full coverage of the monitoring area.

SchoolAIR: A Citizen Science IoT Framework Using Low-Cost Sensing for Indoor Air Quality Management

“…The use of real-time sensors and IoT to monitor IAQ parameters is widely spread among the scientific community [ 14 , 15 , 16 , 17 ]. Low-cost sensors have a high potential in environmental monitoring applications, providing data with a high temporal and spatial resolution at affordable costs.…”