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Title	An Energy Efficient Evolutionary Approach For Smart City-Based Iot Applications
ID_Doc	7989
Authors	Das R.P.; Samal T.K.; Luhach A.K.
Year	2023
Published	Mathematical Problems in Engineering, 2023
DOI	http://dx.doi.org/10.1155/2023/9937949
Abstract	Internet of Things (IoT) has been used in smart cities, agriculture, weather forecasting, smart grids, and waste management. The IoT has huge potential but needs refinement. The paper focuses on lowering IoT sensor power consumption to improve network life. This work selects the best IoT cluster header (CH) to maximize energy consumption. The suggested technique uses particle swarm optimization (PSO) with artificial neural networks (ANNs). The optimal CH in an IoT network cluster was identified by taking into account the number of active nodes, the load, the residual energy, and the cost function. This work compares the suggested method with artificial bee colony, genetic, and adaptive gravity search algorithms. The hybrid solution beats conventional methods. © 2023 Rashmi Prava Das et al.
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