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Traffic management system for emergency vehicles

IoT-based Traffic Management guides emergency vehicles via LED traffic lights, reducing response time, enhancing safety, and optimizing routes for smart cities.

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Traffic management system for emergency vehicles

IoT-based Traffic Management guides emergency vehicles via LED traffic lights, reducing response time, enhancing safety, and optimizing routes for smart cities.

The problem Traffic management system for emergency vehicles solves

The Traffic Management System for Emergency Vehicles, powered by IoT technology and integrated into the smart city infrastructure, addresses a critical and multifaceted issue that urban areas face - the efficient navigation of emergency vehicles through congested and often unpredictable traffic conditions. This innovative solution tackles several significant problems:

  1. Reducing Response Time:
    One of the most pressing challenges in urban emergency management is the ability to respond swiftly to critical situations. Traffic congestion can significantly delay emergency vehicles, leading to potentially life-threatening consequences. The Traffic Management System shortens response times by providing real-time guidance to emergency vehicles, ensuring they reach their destinations faster and more efficiently.

  2. Enhancing Safety:
    Ensuring the safety of emergency services personnel and the general public is paramount. Traffic congestion can lead to accidents involving emergency vehicles, hindering their ability to arrive at the scene of an emergency. By providing clear directions and notifying other vehicles about the presence of an emergency vehicle, this system minimizes the risk of accidents and enhances overall road safety.

  3. Mitigating Traffic Congestion:
    Traffic congestion is a daily challenge in urban areas. The Traffic Management System not only benefits emergency vehicles but also contributes to reducing traffic jams. By efficiently guiding emergency vehicles through traffic, it ensures that regular commuters experience fewer disruptions, shorter travel times, and less frustration.

Challenges we ran into

  1. All the Dynamic Map API are paid and the using the opensource maps for this tasks provides us with a static map which breaks the code.
  2. A Python program directly sends the directions recieved from the code to the web-server and then esp32 processes and pushes the data into the LED screens.As Hardware is not easily available online to emulate and moreover, these platform do not provide the esp32 to create a webhook connection to the server for free, so we had to resort to free alternatives that require manual intervention than automation.

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