Scopus Indexed Publications

Paper Details


Title
Electric Energy Meter System Integrated with Machine Learning and Conducted by Artificial Intelligence of Things-AioT
Author
Nimai Chandra Das, Md Sazzad Sarkar, Md Ziaul Haque Zim,
Email
Abstract
The field of electric power distribution is still in its infancy, and state of the art solutions from modern technology is not easily adapted. IoT and AI could also be bringing a wind of change, but hitherto in large amounts of electrical power users and distributors hooked in to humans is to see the vitality meter and abandoning the bills to the claimant of that home monthly. Most defects of this infrastructure are that human reliance to filter the meter of every house and abandoning the bills. So ever, further bill amounts or notice from power distributors after paying bills are basic blunders. To defeat this kind of inaccuracy this paper considers the creation of a smart energy meter device. Considering power consumption, cost efficiency, speed, and importance on the performance we used ESP8266 based nodeMCU and AVR microcontroller based Arduino development board. The task of nodeMCU gives notification and shows current pursuing with costs through the online page. In this exploration, we complete the accuracy of meter perusing with the help of an LCD that shows which prone to KWh, voltage, current and power factor perusing. The main convenience of this system doesn't lose any data caused by power interrupt, where others AVR based system fails to save the delivery data before turning off the power.

Keywords
Artificial Intelligence of Things (AIoT) , ESP8266 , nodeMCU , AVR microcontroller , Arduino
Journal or Conference Name
IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)
Publication Year
2021
Indexing
scopus