An Enhanced Perimeter Coverage Based Density Control Algorithm for Wireless Sensor Network

2007 ◽  
Author(s):  
Shao-feng Jiang ◽  
Ming-hua Yang ◽  
Han-tao Song ◽  
Jie-min Wang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Control Algorithm ◽  
Wireless Sensor ◽  
Density Control ◽  
Perimeter Coverage

Home intelligent lighting control system based on wireless sensor

2020 ◽  
Vol 18 (5) ◽  
pp. 1231-1240
Author(s):  
Lianyu Wang
Keyword(s):  
Control System ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Control Algorithm ◽  
Wireless Sensor ◽  
Light Control ◽  
Content Type ◽  
Lighting Control ◽  
System Requirements ◽  
Further Development

Purpose Intelligent lighting control system can control lights to go off when people leave, which has been widely concerned by researchers. Design/methodology/approach In this study, an intelligent lighting control system based on wireless sensor network was designed. First, the hardware and software designs of the system were described briefly. Then, the lighting control algorithm was analyzed emphatically. Considering the illumination and uniformity of light, an intelligent lighting control algorithm based on gradient descent was designed. Findings In the system test, it was found that the system had a good through-wall communication function, and the communication distance could fully meet the system requirements and run normally. In the test of the lighting control algorithm, it was found that the user’s satisfaction on uniformity in different scenarios was close to 1, and the satisfaction on illumination could also meet the user’s needs, which verified the reliability of the lighting control algorithm. Originality/value This study provides some theoretical supports for the better application of wireless sensor network in intelligent light control system, which is conducive to the further development of light control system.

scholarly journals Design of Solar Power Management Circuit Based on Wireless Sensor Network

2017 ◽  
Vol 13 (12) ◽  
pp. 67
Author(s):  
Jianying Shi ◽  
Yanbin Xu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Power Management ◽  
Control Algorithm ◽  
Solar Power ◽  
Discharge Power ◽  
Wireless Sensor ◽  
Battery Charge ◽  
Point Tracking ◽  
Solar Battery

<p class="0abstract">To explore the design of solar power management circuit, the fuzzy logic control algorithm based on MPPT (max power point tracking), which has fast control speed and good environment robustness, is adopted as the control algorithm. In addition, the MPPT solar battery charge and discharge power management circuit is designed and successfully applied in the on-line measurement projects of dielectric loss of wireless sensor network in Jilin Province LG Electronics Company. The results show that the charging efficiency of solar battery charge and discharge power management circuit can reach above 80%, and the current of static power management circuit is less than 1mA. In different light intensities, the dynamic power management is intelligently carried out. At last, it is concluded that the stability and reliability of circuit are quite high.</p>

scholarly journals Research on coverage control algorithm based on wireless sensor network

2020 ◽  
Vol 309 ◽  
pp. 03003
Author(s):  
Jie Zhou ◽  
Mengying Xu ◽  
Yi Lu ◽  
Rui Yang
Keyword(s):  
Wireless Sensor Network ◽  
Environmental Monitoring ◽  
Sensor Network ◽  
Control Algorithm ◽  
Cluster Head ◽  
Coverage Rate ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Coverage Control ◽  
Fuzzy Genetic

Wireless sensor network has many sensor nodes with characteristics of limited cost, collecting data, good fault tolerance and storage. It has been used in environmental monitoring, health care, military and commercial. Coverage control is a significant issue that needs to be solved in wireless sensor networks. In order to solve the problem of overlapping coverage for environmental monitoring and improve coverage rate, an improved immune fuzzy genetic algorithm (IIFGA) based on cluster head selection is proposed. the mathematical model is systematically described. In the experiments, ant colony optimization (ACO) and simulated annealing (SA) are given to compare the performance of IIFGA. The experiments show the proposed coverage control algorithm has a higher convergence speed and improve the coverage rate.

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