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@article{160715,
        author = {Anurima Majumdar and Saumyadeep Bhattacharyya and Antara Ghosal and Palasri Dhar and Suparna Biswas and Asmita Chakraborty and Romik Halder and Ankita Roy},
        title = {An App Controlled Intelligent Electricity Meter based on AI and ML },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {1},
        pages = {1053-1057},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=160715},
        abstract = {The aim of this project is to build a real-time IoT and ML based app controlled smart electricity meter for calibrating the energy used in individual appliances. This is a low-cost setup that takes advantage of the IoT and ML technologies for generating an easy-to-understand real-time auto generated electricity consumption along with predicted payable amount.This system allows customers to constantly monitor and get their predicted future energy usage including their payable bills. Using Arduino UNO, NodeMCU and ACS712-30Amp Current sensor this smart electricity meter is proposed. This technology focuses on the efficient use of electricity to reduce the excessive electrical power consumption. In the remote monitoring hardware, the real-time processed data will be displayed in a customized dashboard which will work with appropriate algorithm to determine the accumulated unit of usage.In case of abnormal or high consumption of electricity an alert notification will be provided. Reduction in electricity usage leads to decrement in the demand for fossil fuels which lowers the level of carbon dioxide in the atmosphere.},
        keywords = {Smart Electricity Meter; Machine Learning;Internet of Things; Android Application;App Controlled;Home Automation;Home Metering System; Real-time Electricity Bill},
        month = {},
        }