Safe Route Planning for Disastrous Zones

Our final year project will utilize the concepts of image enhancement, cascade detection, image stabilization, and safe pathfinding to develop a unique and comprehensive algorithm. The algorithm will be written in Python and implemented on a specially designed computer application. Through this appl

Project Title

Safe Route Planning for Disastrous Zones

Project Area of Specialization

Computer Science

Project Summary

Our final year project will utilize the concepts of image enhancement, cascade detection, image stabilization, and safe pathfinding to develop a unique and comprehensive algorithm. The algorithm will be written in Python and implemented on a specially designed computer application. Through this application, we will be able to analyze any disaster struck area compare it with a reference image from before the catastrophe, and identify all the civilians in the region as well as all the hurdles and obstacles in the region to quickly formulate a safe route, in real-time, for disaster relief teams to efficiently conduct their rescue operations.

Project Objectives

The main objectives of our final year project are as follows:

• Provide optimal identification of distressed citizens in affected areas to ensure their timely assistance by rescue services.
• Effectively recognize any obstacles, hurdles, and carnage in the devastated regions to assist relief operations in their navigation of the perilous landscape.
• Formulate the safest routes in disaster zones to facilitate the relief and rescue operations by enhancing their mobility and potentially minimizing loss of life.    
• Promote the use of disaster drones because they offer humanitarian agencies a range of possibilities in relation to crisis mapping, search and rescue, and cargo transport and relief drops.

Project Implementation Method

The implementation of our final year project has been divided into the following different phases:

• Surveillance and video recording of the disaster zones with the help of a quadcopter drone.
• Transmission of recorded data to a computer application over 5.8 GHz data link system with a range of 3 Km.
• Using image stabilization methods to remove any blurriness and frame to frame jitters in the images.
• Implementing image enhancement techniques and use cascade detection, to recognize vulnerable individuals in the disaster zones.
• Implementing OSD from our APM module to display the GPS locations of various roads, buildings, debris and other destruction.

Using safe pathfinding techniques to formulate a safe path, in real time, to aide in the relief efforts.

Benefits of the Project

The benefits of our final year project are as follows:

• Provision of a live stream of the current situation on the ground, via the timely deployment of the disaster drone to the affected area, allowing the rescue services to plan accordingly.
• Timely identification of distressed individuals in the disaster zone that are in need to assistance, resulting in their aid and abetment by the rescue services.
• Recognition of various roads, buildings, carnage, and other such blockades allowing disaster relief services to better maneuver themselves through the region.
• Formulation of a safe path that will allow rescue services to easily navigate the impacted region, enhancing their mobility and minimizing the loss of life.

Technical Details of Final Deliverable

Our proposed algorithm will utilize the concepts of digital image processing using Python. As the disaster zone drone is recording the video graphic data of the affected area it will utilize a 5.8 GHz data link transmission system that has a 3-kilometer range to transmit the collected information, in real-time, to the rescue services that they will receive on a specifically designed computer application. Once received, the computer application will call on our algorithm to compare the video frames with reference images from before said area was affected. The algorithm will initially employ the functions of color mapping and image stabilization to remove any potential errors that may occur during the differencing process because of the difference in brightness or blurriness in the images. Once the differencing process is complete, the pathfinding element of our algorithm will formulate a path in real-time which will be displayed on the computer application which we will design. This path will potentially have the least amount of obstacles to easily facilitate the mobility of rescue teams in their relief efforts. 

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Health

Other Industries

Security

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com