An Indoor Positioning and Prewarning System Based on Wireless Sensor Network Routing Algorithm
One of the most important means to position abnormal devices is to efficiently utilize the resources of wireless sensor network (WSN) and make proper analysis of the relevant data. Therefore, this paper constructs an indoor positioning and prewarning system that utilizes energy efficiently and achie...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Hindawi Limited
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/1112c4f31b6a49b8b83d180a4bc87765 |
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| Sumario: | One of the most important means to position abnormal devices is to efficiently utilize the resources of wireless sensor network (WSN) and make proper analysis of the relevant data. Therefore, this paper constructs an indoor positioning and prewarning system that utilizes energy efficiently and achieves a long lifecycle. Firstly, the adjacent round iteration load balancing (ARILB) routing algorithm was proposed, which elects the cluster heads (CHs) by the adjacent round strategy. In this way, the random components were eliminated in CH election. Next, a short-distance multifrequency routing strategy was constructed between CHs to transmit the information to the sink, and a positioning algorithm was designed called ARILB-received signal strength (RSS). The ARILB-RSS positioning algorithm traverses the triangles formed by anchor nodes, forming multiple sets of ranging points; then, the optimal anchor node is recorded, and the path loss factor is iterated to reduce the positioning error. Simulation shows that the network survives 54.5% longer using ARILB than using the distributed energy-efficient clustering (DEEC) algorithm; the packet delivery rate using ARILB was about 139% higher than that of low energy adaptive clustering hierarchy (LEACH) algorithm and 35% higher than that of uneven clustering routing algorithm based on chain-cluster type (URCC) algorithm; ARILB-RSS reduced the ranging error by 14.31% and then the positioning error by 26.79%. |
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