pages 1-6

Enhanced Streetlight Management: Using IoT and ESP32 for Automated Fault Detection

Swati Bhisikar 1
Prabodh Jagtap 1
Shilpa Sonawane 1
Hrushikesh Sawant 2
Prerana Pisal 3
1
 
Rajarshi Shahu College of Engineering,Dept. of Electronics and Telecommunication,Pune,India
2
 
Vishwakarma Institute of Information Technology,Dept. of Information Technology,Pune,India
3
 
Rajarshi Shahu College of Engineering,Dept. of Automation and Robotics,Pune,India
Publication typeProceedings Article
Publication date2024-08-22
Abstract
The core focus of this paper is to implement a cutting-edge system for intelligent streetlight management, leveraging an automotive monitoring system to identify and rectify any faults within the streetlight infrastructure. Rapid response of the proposed fault detection system will help save the time of the linemen, which is wasted in manually detecting the faults at streetlights, and will help to reduce the workload of the linemen. Also, most of the time, the detection of the problem mainly depends on the grievances of the local people. Thus, this causes delays in the maintenance of the streetlights, wastage of power, and problems for the local people. So, to reduce such problems, we have developed an automatic detection system for streetlight faults. During nighttime, this system will detect faults such as whether the lamp is ON or OFF, or if a wire cut is in the circuit. As the fault is detected, the information will be provided to the authorized person; the information will contain the type of fault that occurred in the streetlight system.
Found 
Found 

Top-30

Journals

1
Sensors
1 publication, 100%
1

Publishers

1
MDPI
1 publication, 100%
1
  • We do not take into account publications without a DOI.
  • Statistics recalculated weekly.

Are you a researcher?

Create a profile to get free access to personal recommendations for colleagues and new articles.
Metrics
1
Share