Original price was: ₹ 7,500.00.₹ 6,000.00Current price is: ₹ 6,000.00.
The Smart Traffic Light System is designed to improve the flow of traffic by dynamically adjusting the timing of traffic lights based on real-time traffic data. By using sensors at each intersection, the system can determine the number of vehicles waiting at each signal and adjust the light cycle to alleviate congestion. The system is built using a Raspberry Pi, ultrasonic sensors to detect vehicles, and cameras to monitor traffic. The Raspberry Pi processes the sensor data and sends commands to a set of traffic lights to control their timings. One key aspect of the system is its ability to analyze data to predict peak traffic times and make traffic flow smoother. The system uses machine learning algorithms to learn traffic patterns over time and optimize the light timing for different times of day. For example, during rush hour, the system can extend green lights for roads with more traffic. On the other hand, during off-peak hours, it minimizes wait times for all road users. This system offers several advantages, including a reduction in traffic congestion, shorter wait times, and lower emissions from idling vehicles. Additionally, the system can be integrated with cloud services, allowing remote monitoring and adjustments for traffic authorities. This project can be implemented in smart cities to enhance urban mobility, reduce environmental impacts, and increase road safety. The ability to adjust traffic light timings in real-time based on current road conditions makes this project highly beneficial for improving overall traffic management.
The Smart Traffic Light System is designed to improve the flow of traffic by dynamically adjusting the timing of traffic lights based on real-time traffic data. By using sensors at each intersection, the system can determine the number of vehicles waiting at each signal and adjust the light cycle to alleviate congestion. The system is built using a Raspberry Pi, ultrasonic sensors to detect vehicles, and cameras to monitor traffic. The Raspberry Pi processes the sensor data and sends commands to a set of traffic lights to control their timings. One key aspect of the system is its ability to analyze data to predict peak traffic times and make traffic flow smoother. The system uses machine learning algorithms to learn traffic patterns over time and optimize the light timing for different times of day. For example, during rush hour, the system can extend green lights for roads with more traffic. On the other hand, during off-peak hours, it minimizes wait times for all road users. This system offers several advantages, including a reduction in traffic congestion, shorter wait times, and lower emissions from idling vehicles. Additionally, the system can be integrated with cloud services, allowing remote monitoring and adjustments for traffic authorities. This project can be implemented in smart cities to enhance urban mobility, reduce environmental impacts, and increase road safety. The ability to adjust traffic light timings in real-time based on current road conditions makes this project highly beneficial for improving overall traffic management.
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