Smart Energy Management System Using IoT for Real-Time Monitoring and Theft Detection
The internet of things technology has developed almost all the sectors including energy management. In traditional energy management system meters are used to recording the number of units and electricity used but they are unable to provide the real time information or updates or any theft of electricity. By focusing this problem, we have developed a system which is able to overcome all the problems in traditional electric management system. It monitors the energy usage and real time theft detection of electricity as it cost lot of money. In our system we have used a current sensor which continuously checks the electricity flow. The microcontroller measures the actual energy usage as well as expected values. It compares both the values. If a big difference found, then it could mean the theft of electricity. So, the GSM module is used to send the alert to the user hence they can take required action. The Wi-Fi module sends the data over the cloud for data analytics. Also, user can see the real time data from the cloud platform. Hence user can track the energy usage and get timely alerts so that user can be aware of energy consumption or energy theft. The system is developed by setting up hardware parts as well as integration with software. The system can be operated or monitored from remote place, as Wi-Fi module connects the system with the internet. System can detect the unusual activities like theft of electricity by analyzing the data. Using the IoT technology for energy management, it can become cost effective as well as smart solution of energy management to avoid any theft. Hence it can overcome the loss.
Authors
- Ravindra Raman Cholla (ORCID: https://orcid.org/0000-0003-3311-2407)
- Rajermani Thinakaran (ORCID: https://orcid.org/0000-0002-9525-8471)
- Vikram Neerugatti (ORCID: https://orcid.org/0000-0002-2203-7002)
- KK Rao
- Somasekar Jalari
Institutions
- Jain University (IN)
- INTI International University (MY)
Publication Details
- Published
- 2024-11-07
- DOI
- https://doi.org/10.1109/icitda64560.2024.10809967
- Citations
- 1
- Primary Topic
- IoT-based Smart Home Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.21