Internet of Things Based System for Health Monitoring for Distribution Transformer
Electricity distribution from substations to residences and businesses depends on distributed transformers. However, a number of things, including overload, overheating, and outside elements like moisture and dust, can harm them. For distributed transformers to remain operational and prevent damage, health monitoring is crucial. Using sensors to assess vital variables like voltage, current, temperature, and humidity is one approach to keep an eye on the condition of distributed transformers. To find any possible issues, the data from these sensors can be gathered and analysed. If an issue is found, it can be fixed before the transformer is harmed. A system employing Node MCU and Arduino was suggested in a study for the health monitoring of distributed transformers. An open-source platform called Node MCU makes use of the ESP8266 microcontroller. Interactive projects are developed on the open-source Arduino electronics platform. The suggested system gathers data from the sensors and transmits it to an Arduino using a Node MCU. The data is subsequently transmitted from the Arduino via the internet to a cloud server. The data can be stored on the cloud server, which can also analyse it to find any potential issues. An alert can be provided to the user if a problem is found. This technology offers a simple and affordable solution to keep track of the condition of distributed transformers. It can aid in avoiding damage and ensuring the ongoing functionality of these crucial devices.
Authors
- Arshi Naim (ORCID: https://orcid.org/0000-0003-1325-6964)
- Mohammad Nadeem Ahmed
- Muhammad Shahid Dildar
- Mohammad Rashid Hussain (ORCID: https://orcid.org/0000-0001-5035-274X)
- Angel Swastik Duggal (ORCID: https://orcid.org/0000-0003-1070-1882)
- B. Arun Kumar
Institutions
- Lovely Professional University (IN)
- King Khalid University (SA)
Publication Details
- Published
- 2024-11-22
- DOI
- https://doi.org/10.1109/aece62803.2024.10911075
- Citations
- 2
- Primary Topic
- Fire Detection and Safety Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.73