2690-6791ISSN (Online)
2769-786XISSN (Print)
Volume 14 , Issue 2 , PP: 36-43, 2025 | Cite this article as | XML | Html | PDF | Full Length Article
Mohammed Arif Nadhom Obaid Al-agar 1 , Zaynab Saeed Hameed 2 , Israa Ali Al-Neami 3 , Sergey Drominko 4 , Erina Kovachiskaya 5
Doi: https://doi.org/10.54216/JISIoT.140204
Wireless sensor networks have been identified as one of the most important technologies. A vast amount of research and development has been devoted to this area in the past decade. Nowadays, they have been applied in various fields including environment monitoring, smart building, medical care, and etc. With the advances in electronics, wireless communications, and sensor technology, more and more new opportunities have been created for the research in wireless sensor networks. However, the successful implementation of WSN faces many challenges, such as limited power, limited memory, and limited computing capability. Among them, limited power is the most critical restriction because it is usually impossible for the battery-powered sensor nodes to be recharged. Therefore, one of the main areas of interest for wireless sensor network research is how to reduce power consumption. The proposed system classifies sensor nodes into two operational modes, optimizes node deployment, and finds optimal node placements using a genetic algorithm (GA) to minimize the energy consumption of the WSN. The system's successful testing on a simulated WSN meant for radiation site identification revealed its potential for practical real-world applications.
Power Consumption , Genetic Algorithm (GA) , Battery-Powered Sensors , Energy Efficiency
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