ML Based Smart Energy Meter Observing & Bill Supervision Using Raspberry Pi

DOI

10.2991/ahis.k.210913.001How to use a DOI?

Keywords

Raspberry pi, IOT, power consumption, Things Speak

Abstract

Nowadays the power consumption is increasing unknowingly in our houses and Some faulty devices will consume more energy than what it is taken. So, to overcome those defects a system is being proposed that will provide the information about the power consumption and faulty loads by the system and also, to know the power consumption and billing amount in the cloud in graphical representation. This system can reduce the time and also make the entire process into a smart one. By using this system manual calculations will be avoided. A novel process was developed based on Raspberry pi microcontroller to identify and monitor the power consumption, faults, bill supervision. A data will be measured automatically and passed to the cloud server protocol through IOT module. The data will be sent to cloud by the help of current transformer and potential transformer. The terms like power consumption, bill supervision in cloud (ThingSpeak) can be seen anywhere in the country. The system will keep track of power consumption and bill supervision. Then whole data will be updated to cloud (ThingSpeak) for instant of time. The data will be updated to cloud for every 180 seconds. Internet is necessary for the system to update collected data to cloud (ThingSpeak).

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - V. Amala Rani
AU  - T. Thaj Mary Delsy
AU  - D. Marshiana
AU  - N. Praveen
AU  - P. Kartheek
PY  - 2021
DA  - 2021/09/13
TI  - ML Based Smart Energy Meter Observing & Bill Supervision Using Raspberry Pi
BT  - Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021)
PB  - Atlantis Press
SP  - 1
EP  - 5
SN  - 2589-4900
UR  - https://doi.org/10.2991/ahis.k.210913.001
DO  - 10.2991/ahis.k.210913.001
ID  - Rani2021
ER  -