A Power-Saving Classification Module for The Internet of Things Enclosed Wireless Sensors Embedded in Smart Controllers

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.

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Publication Details

Journal
International Journal of Basic and Applied Sciences
Published
2025-11-15
DOI
https://doi.org/10.14419/q2va4b09
Primary Topic
Energy Efficient Wireless Sensor Networks
Type
article
Field-Weighted Citation Impact
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article

A Power-Saving Classification Module for The Internet of Things Enclosed Wireless Sensors Embedded in Smart Controllers

Sanjeevikumar Padmanaban, R. Gayathri, R. Poornima, B. Suganthi et al.
International Journal of Basic and Applied Sciences
Energy Efficient Wireless Sensor Networks
article

A Power-Saving Classification Module for The Internet of Things Enclosed Wireless Sensors Embedded in Smart Controllers

Sanjeevikumar Padmanaban, R. Gayathri, R. Poornima, B. Suganthi, P. Gnanasundari, Prof. Nitin Chakole
article en

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.

International Journal of Basic and Applied SciencesVol. 14(7)
Rama University (IN), Coimbatore Medical College and Hospital (IN), Bangalore University (IN), Karpagam Academy of Higher Education (IN)
Openalex Percentile: Top 60%
Energy Efficient Wireless Sensor Networks
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