A Method to Construct an Indoor Air Pollution Monitoring System Based on a Wireless Sensor Network
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, s...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-02-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/19/4/967 |
| _version_ | 1828346686176493568 |
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| author | Ahras Naziha Li Fu Galloua Mohamed Elamine Lingling Wang |
| author_facet | Ahras Naziha Li Fu Galloua Mohamed Elamine Lingling Wang |
| author_sort | Ahras Naziha |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-14T00:30:23Z |
| format | Article |
| id | doaj.art-7d643e00f0374b3abd1b22c60e08dc26 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T00:30:23Z |
| publishDate | 2019-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-7d643e00f0374b3abd1b22c60e08dc262022-12-22T02:22:34ZengMDPI AGSensors1424-82202019-02-0119496710.3390/s19040967s19040967A Method to Construct an Indoor Air Pollution Monitoring System Based on a Wireless Sensor NetworkAhras Naziha0Li Fu1Galloua Mohamed Elamine2Lingling Wang3School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, ChinaSchool of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, ChinaSchool of Computer Science and Engineering, Beihang University, Beijing 100191, ChinaSchool of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, ChinaWireless 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.https://www.mdpi.com/1424-8220/19/4/967wireless sensor networkregion of interestvoronoi diagrampoint in polygoncoveragecoverage hole |
| spellingShingle | Ahras Naziha Li Fu Galloua Mohamed Elamine Lingling Wang A Method to Construct an Indoor Air Pollution Monitoring System Based on a Wireless Sensor Network Sensors wireless sensor network region of interest voronoi diagram point in polygon coverage coverage hole |
| title | A Method to Construct an Indoor Air Pollution Monitoring System Based on a Wireless Sensor Network |
| title_full | A Method to Construct an Indoor Air Pollution Monitoring System Based on a Wireless Sensor Network |
| title_fullStr | A Method to Construct an Indoor Air Pollution Monitoring System Based on a Wireless Sensor Network |
| title_full_unstemmed | A Method to Construct an Indoor Air Pollution Monitoring System Based on a Wireless Sensor Network |
| title_short | A Method to Construct an Indoor Air Pollution Monitoring System Based on a Wireless Sensor Network |
| title_sort | method to construct an indoor air pollution monitoring system based on a wireless sensor network |
| topic | wireless sensor network region of interest voronoi diagram point in polygon coverage coverage hole |
| url | https://www.mdpi.com/1424-8220/19/4/967 |
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