A Power-Saving Classification Module for The Internet of Things Enclosed Wireless Sensors Embedded in Smart Controllers
Year: 2025
Type: article
Abstract: Internet of Things (IoT), combined with wireless sensor network (WSN) devices, interacts with smart controllers within industries or buildings, etc., to accomplish field jobs. The jobs/ tasks are completed based on the controller's decision, power-saving, and sustainable operation intervals. To improve the power savings of such devices, a Control-dependent Process Classification Module (CdPCM) is proposed in this article. This proposed module balances the controller operation time and the number of input controls based on a low-power sustainable feature. The feature identifies the maximum operation time of the controller before reaching the recharging state. In this process, the IoT layers are responsible for commissioning and decommissioning jobs for the low-power operations. Thus, the input controls are relocated from the overloaded controllers to sustain their active state until an alternate controller is reassigned. Thus, the power-saving schedules are allocated for the sensor-based controllers to accomplish the tasks with minimal inactive time. The factor classification based on the above feature is recurrent until the controller operation interval is active, using deep recurrent learning networks. The proposed module improves power saving by 11.22%, reduces the power consumption by 11.03% and idle power loss by 10.67% for the varying job intervals.
DOI: 10.14419/q2va4b09
Institutions: Karpagam Academy of Higher Education, RV University
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4416257301
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