The Smart Street Lighting System presented in this project aims at delivering advanced technology to enhance the efficiency and sustainability of urban street lighting. By integrating Light Dependent Resistors (LDRs), Arduino Uno microcontrollers, Infrared (IR) sensors, and Light Emitting Diodes (LEDs), this innovative solution responds intelligently to environmental conditions, ensuring optimal lighting levels while conserving energy.
Demo.mp4
The Smart Street Lighting System represents a significant departure from traditional fixed-brightness streetlights. It employs Light Dependent Resistors (LDRs) and Arduino Uno microcontrollers to continuously monitor ambient light, dynamically adjusting brightness, initially set at 15% efficiency. This adaptive approach enhances safety and minimizes energy consumption during well-lit periods.
Strategically positioned Infrared (IR) sensors detect movement, activating LEDs to provide intense illumination around 90% in response. This enhances safety and conserves energy by avoiding unnecessary full-scale lighting when streets are empty.
This project offers a cost-effective, eco-friendly urban lighting solution, showcasing substantial energy savings and reduced light pollution. Future enhancements will focus on energy efficiency, data analytics for traffic optimization, and IoT integration for improved city services, ultimately making urban lighting smarter, data-driven, and responsive to community needs.
- LDR Sensor
- IR Sensor
- Bluetooth Module (HC-05)
- Arduino Uno R3
- MIT App Inventor.
Dashboard.mp4
As part of our initiative, we utilized Node-RED, an accessible yet potent tool, to develop a unique dashboard. This dashboard serves as a centralized hub for displaying vital data, particularly concerning our power consumption. People can view this information in real-time, aiding them in making informed decisions and optimizing resource utilization. This not only enhances data clarity but also enhances overall efficiency. It's akin to having an intelligent assistant for decision-making and effective resource management, contributing to our initiatives.
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Energy Efficiency: We'll integrate advanced sensors to dynamically adjust streetlight brightness in response to traffic and environmental conditions, improving energy efficiency and safety
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Data Analytics: Data collection and analysis from smart streetlights provide insights into traffic patterns and pedestrian activity. This informs efficient traffic management and urban infrastructure planning
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IoT Integration: We'll extend the project with additional IoT devices, including environmental sensors, cameras, and Wi-Fi. This interconnected system will elevate city services, spanning air quality monitoring, security, and enhanced connectivity for residents
These developments will make our smart street lighting project more sustainable, data-driven, and responsive to the needs of our community.
Ministry/Organization Name/Student Innovation: Ministry of Power
PS Code: SIH1300
Problem Statement Title: Automated Public Lighting
Team Name: Electrobuzz
Team Leader Name: Yash Bhavnani
Institute Code (AISHE): 3012
Institute Name: Veermata Jijabai Technological Institute
Theme Name: Hardware
Members:
- Yash Bhavnani (Team Leader)
- Poorva Gaikar
- Kshitij Patil
- Manan Shanghvi
- Vansh Panchal
- Dhruv Vanjari