Project Title : Smart Street Lights

Overview

This project focuses on creating smart street lights that automatically adjust brightness based on object detection and environmental conditions, promoting energy efficiency and safety.

Problem Statement

Traditional streetlights consume excessive energy by staying at full brightness throughout the night, even when not needed. This project aims to address this issue by making streetlights smarter, incorporating IoT-based solutions for enhanced control and monitoring.

Importance in IoT-Based Systems

IoT-enabled smart street lights are a cornerstone of modern smart cities. They:

• Enhance energy efficiency by automating lighting based on environmental data.
• Reduce operational costs with remote monitoring and control.
• Improve public safety through real-time detection and analysis of environmental conditions.
• Lay the foundation for integration with other smart city systems, like traffic monitoring and emergency response.

Features

• Motion Detection: IR sensors detect objects and adjust brightness.
• Environmental Monitoring: Measures atmospheric temperature and humidity.
• Energy Efficiency: Lights glow only during darkness or at night.
• Object Velocity Measurement: Calculates the speed of passing objects.

Project Journey

The journey of creating this project was both challenging and rewarding:

1. Brainstorming Ideas: After several discussions, we finalized the idea of developing an energy-efficient street light system using IoT and sensors.
2. Finding Efficient Sensors: We conducted extensive research to select cost-effective yet reliable components, such as the DHT11 for temperature measurement and MQ-135 for AQI detection.
3. 48+ Hours of Hard Work: We dedicated countless hours working on the breadboard, ensuring proper connections and functionality of all components.
4. Debugging for 5+ Hours: Overcoming multiple issues, we fine-tuned the sensors and microcontroller code for accurate and stable performance.
5. Final Assembly: After successful testing, we completed the soldering process to make the system robust and portable.

Components Used

• Microcontroller: Arduino Uno
• Sensors:
  • IR sensor for motion detection
  • LDR sensor for detecting darkness / night
  • DHT22 for temperature and humidity measurement
• Lighting: LED lights
• Other Components: Resistors, jumper wires, breadboard, PCBs, Soldering Kit, OLED display, power supply

Setup Instructions

Hardware Connections

1. IR Sensor: Connect the output pin to a digital pin on the Arduino, VCC to 5V, and GND to ground.
2. LDR Sensor: Connect the output pin to a digital pin on the Arduino, VCC to 5V, and GND to ground.
3. DHT22 Sensor: Connect the data pin to a digital pin on the Arduino, VCC to 5V, and GND to ground.
4. LEDs: Connect the positive leg to PWM pins on the Arduino via resistors and the negative leg to GND.
5. Ensure proper connections and double-check the circuit before powering it on.

About the Code

• The code initializes the sensors, reads their data, and controls the LED brightness based on object detection within the range and environmental parameters.
• Load the provided finalcode.ino file into the Arduino IDE, compile it, and upload it to the Arduino.

Testing the System

1. Test the motion detection functionality using the IR sensor.
2. Verify the temperature and humidity readings by comparing them with a standard device.
3. Observe the LED brightness adjustments under different conditions.

Future Applications

• Integration with smart city infrastructure.
• Real-time monitoring and analytics through IoT platforms.
• Solar-powered operation for greater energy savings.
• Use in highways and industrial areas for enhanced safety and visibility.

Project Images

[Circuit Images]

Contributions

By:
Moksha Choksi
Dhanika Kothari

This project is a result of collaborative efforts, dedication, passion and innovation. We welcome collaborations from like-minded individuals and organizations to explore new possibilities and create a sustainable future!