Abstract
Energy harvesting from its environmental sources becomes an integral part of green cities. This paper considers a low-energy consumption Wireless Sensor Networks to improve energy utilization in green cities. By this approach, a wireless node can directly harvest energy from its ambient by introducing an energy-harvesting layer on the top of traditional WSN layer. The energy harvesting layer composed of charging points (CPs) that it can harvest energy from ambient renewable energy sources (solar, vibration, light, and electromagnetic wave, etc.) transfer the harvested energy to the underlying WSN layer by wireless energy transfer. Furthermore, in order to conserve battery power in very dense sensor networks, some sensor nodes may be put into the sleep state while other sensor nodes remain active for the sensing and communication tasks. The proposed scheme applies energy informatics to increase the energy efficiency by optimizing energy harvesting time interval and energy consumption of the node for uniform data gathering over the network.
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More From: International Conference on Machine Learning and Intelligent Communications (MLICOM 2018: Machine Learning and Intelligent Communications)
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