![Reference
[1] Prashanth. S U et al, “IoT Based Smart Street Lighting System,” International Journal of
Engineering Research & Technology (IJERT), Volume 10, No. 08,2022.
[2] D.K. Saini et al, "Auto Streetlight Control with Detecting Vehicle Movement," Advances in
Energy Technology , Springer, Singapore, pp. 279-288, 2022.
[3] N. Sravani et al., "Street Light Controlling and Monitoring of Fault Detection using LoRa,"
International Journal for Modern trends in science and technology, vol. 7, no. 12, pp.242-245,
2022.
[4] Ashok Kumar Nanduri et al, “IoT based Automatic Damaged Street Light Fault Detection
Management System,” (IJACSA) International Journal of Advanced Computer Science and
Applications, Vol. 11, No. 8, 2020.
[5] C. Subramani et al., "Energy Efficiency and Pay-Back Calculation on Street Lighting
Systems," The 11th National conference on mathematical Technique and Application, AIP Conf.
proc., Vol.2310, no. 1, 2019.](https://image.slidesharecdn.com/projectreview-1-240603122412-311d8c7c/85/Auto-fault-detection-and-location-of-street-light-management-9-320.jpg)
Auto fault detection and location of street light management
- 1. AUTOMATED STREET LIGHT MANAGEMENT SYSTEM Sathish C - 412720106012 Mr. S. Hari Ramakrishnan Sathish N - 412720106013 Saravanan M - 412720106305 Sharan R - 412720106306 T E A M M E M B E R S : S U P E R V I S O R :
- 2. Need for the project The project aims to enhance street light maintenance efficiency by automating fault detection and location tracking. It addresses issues like energy wastage due to faulty lights and delays in repair. Automated fault detection reduces manual inspection efforts and ensures timely repairs. Location tracking helps pinpoint the exact faulty street lights, optimizing maintenance routes. By improving street light reliability, the project enhances public safety and reduces accidents. It also contributes to energy conservation efforts by minimizing unnecessary power consumption.
- 3. title Author description Year IoT Based Smart Street Lighting System Prashanth. S U Rakshanraj. J A. Maria Chirstina Blessy This paper present Using Node MCU, IR sensor, LDR Sensor. The LDR Sensor Detect Status Of Street Light. The primary objective of this project is to conserve energy by elevating the light intensity solely upon detecting the movement of an object 2022 Auto Streetlight Control with Detecting Vehicle Movement D.K. Saini The aim of this paper is to reduce the amount of power lost in streets in the name of street lights. To achieve this, the street lights should illuminate in the presence of any object or vehicle during the night, while remaining switched off during the daytime. 2022 literature survey
- 4. title Author description Year Street Light Controlling and Monitoring of Fault Detection using LoRa N. Sravani Y. Latha G. Nirmala This paper presents using LoRa By Using LCD, LDR, Solar Panel, Think Speak And LoRa Module. This project Enhancing Swiftly identifying faults is a critical task.nd Based on the characteristics of the application,this study employs two separate model technique. 2021 IoT based Automatic Damaged Street Light Fault Detection Management System Ashok Kumar Nanduri Siva Kumar This paper presents by using GSM, LDR, LED and GPS. The goal of the project is to provide control and identification of the damaged street light automatically. Within this system, it verifies the operational status of the street light, determining whether it is switched ON or OFF. 2020 literature survey
- 5. Disadvantage of existing system One disadvantage of the current street light management system compared to auto fault detection and location tracking is that the current system often relies on manual inspection to identify faults or outages. This manual process can be time- consuming, inefficient, and prone to errors, leading to delays in addressing issues and potentially longer periods of darkness on the streets. In contrast, auto fault detection and location tracking systems can quickly identify problems and pinpoint their exact location, allowing for faster response times and improved overall maintenance efficiency.
- 6. Objective of the project The main objective of auto fault detection and location tracking of street lights is to enhance efficiency and reliability in the management and maintenance of street lighting infrastructure. By automatically detecting faults and precisely locating their positions, this system aims to reduce downtime, improve response times for repairs, minimize energy wastage, and ultimately ensure well-lit and safe streets for the community.
- 8. ESP32: The ESP32 is a microcontroller that Will be utilized for collect data from the sensors and send it to the Blynk app. Blynk app: The Blynk app is a mobile app that Will be utilized for display the data collected by the ESP32 and to allow maintenance personnel to interact with the system. LDR: The LDR is a light sensor that Will be utilized for detect street light faults. GPS: The GPS module Will be utilized for track the location of maintenance personnel. RFID reader: The RFID reader Will be utilized for verify that maintenance personnel have visited the site of a fault. Battery: The battery Will be utilized for power the system when there is no grid power available.
- 9. Reference [1] Prashanth. S U et al, “IoT Based Smart Street Lighting System,” International Journal of Engineering Research & Technology (IJERT), Volume 10, No. 08,2022. [2] D.K. Saini et al, "Auto Streetlight Control with Detecting Vehicle Movement," Advances in Energy Technology , Springer, Singapore, pp. 279-288, 2022. [3] N. Sravani et al., "Street Light Controlling and Monitoring of Fault Detection using LoRa," International Journal for Modern trends in science and technology, vol. 7, no. 12, pp.242-245, 2022. [4] Ashok Kumar Nanduri et al, “IoT based Automatic Damaged Street Light Fault Detection Management System,” (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 11, No. 8, 2020. [5] C. Subramani et al., "Energy Efficiency and Pay-Back Calculation on Street Lighting Systems," The 11th National conference on mathematical Technique and Application, AIP Conf. proc., Vol.2310, no. 1, 2019.
- 10. Thank you