Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
Volume-3 | Issue-2
Light Weight CNN based Robust Image Watermarking Scheme for Security
Volume-3 | Issue-2
Principle of 6G Wireless Networks: Vision, Challenges and Applications
Volume-3 | Issue-4
PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
Volume-3 | Issue-3
Is Internet becoming a Major Contributor for Global warming - The Online Carbon Footprint
Volume-2 | Issue-4
Augmented Reality in Education
Volume-2 | Issue-4
A Study on Various Task-Work Allocation Algorithms in Swarm Robotics
Volume-2 | Issue-2
IoT based Biotelemetry for Smart Health Care Monitoring System
Volume-2 | Issue-3
Tungsten DiSulphide FBG Sensor for Temperature Monitoring in Float Glass Manufacturing
Volume-2 | Issue-4
GUI based Industrial Monitoring and Control System
Volume-3 | Issue-2
AUTOMATION USING IOT IN GREENHOUSE ENVIRONMENT
Volume-1 | Issue-1
Principle of 6G Wireless Networks: Vision, Challenges and Applications
Volume-3 | Issue-4
Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
Volume-3 | Issue-2
Light Weight CNN based Robust Image Watermarking Scheme for Security
Volume-3 | Issue-2
VIRTUAL REALITY GAMING TECHNOLOGY FOR MENTAL STIMULATION AND THERAPY
Volume-1 | Issue-1
Design of Digital Image Watermarking Technique with Two Stage Vector Extraction in Transform Domain
Volume-3 | Issue-3
Analysis of Natural Language Processing in the FinTech Models of Mid-21st Century
Volume-4 | Issue-3
PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
Volume-3 | Issue-3
Image Augmentation based on GAN deep learning approach with Textual Content Descriptors
Volume-3 | Issue-3
Comparative Analysis for Personality Prediction by Digital Footprints in Social Media
Volume-3 | Issue-2
Volume - 4 | Issue - 4 | December 2022
Published
01 February, 2023
Many industries require a certain amount of electrical power. Prepaid metering, with its unique performance in the Internet of Things (IoT), tends to be an efficient power management system by providing cost-effective prepaid electricity services to the industrial sector. Errors can occur at any stage of the energy billing process, including errors in electromechanical meters, human errors during meter reading, and errors in processing paid and unpaid bills. A prepaid energy meter is the solution to these problems. In this work, prepaid energy meters were developed to reduce energy consumption in the industry. The introduction of this prepaid meter will contribute to improving energy management, saving energy, and eliminating fraudulent billing. Automated billing systems track consumption in real time, eliminating the possibility of fraudulent billing and consumption disputes. A prepaid energy meter was developed using current and voltage sensors, and the energy meter was tested with a load connected to a 220 V power supply. Energy meters are connected to the cloud to create a user alert system.
KeywordsPrepaid energy meter IoT energy management automated billing system alert system
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