Open AccessNode deployment method of Intelligent smoke sensors across high space using many-objective optimization algorithm
Author(s) -
Pingshan Liu,
Junli Fang,
Hongjun Huang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1883/1/012116
Subject(s) - software deployment , computer science , wireless sensor network , node (physics) , smoke , real time computing , distributed computing , computer network , engineering , structural engineering , waste management , operating system
NB-IoT promotes innovation in the field of wireless sensor networks[7], the problem of deployment and coverage optimization of intelligent smoke sensors based on NB-IoT technology in high space has become a new research trend subsequently. In this article, we study the problem of the node deployment and coverage optimization of intelligent smoke sensors in a tall indoor space environment. Firstly, an intelligent smoke sensor nodes deployment method suitable for tall spaces is designed through the analysis of the tall environment and the particularity of the intelligent smoke sensors. Then we establish a three-dimensional directed coverage perception model. The node coverage range and deployment cost are the objective functions, which need to be optimized. Furthermore, a node deployment approach across specific high space is developed on the basis of multi-objective optimization algorithm to optimize the two objective functions. Compared with existing deployment schemes, the results of simulations demonstrate that our proposed deployment strategies can achieve better Quality of Coverage (QoC) and detection performance while enlarges the monitoring scope.