Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Abstract :
Street lighting is a fundamental public utility, yet its maintenance often relies on manual inspection, leading to energy waste and safety risks. This paper presents an IoT-based automatic fault detection system specifically designed for the BSIET campus. By integrating an ESP8266/ESP32 microcontroller with LDR and ACS712 current sensors, the system automates light operation and identifies electrical faults like lamp failure or open circuits in real-time. Data is transmitted to a cloud platform (Blynk/Firebase), enabling instant mobile alerts for maintenance teams. This solution enhances campus security, reduces downtime, and supports energy conservation.
Keywords:
IoT, LDR Sensor, IR Sensor, Arduino, Smart Street Light, Energy Saving.
Cite Article:
""IoT based Automatic Street Light Fault Detection in BSIET Campus."", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 2, page no.a621-a626, February-2026, Available :http://www.ijrti.org/papers/IJRTI2602084.pdf
Downloads:
000104
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator