Developing an Automated Forest Fire Detection and Early Warning System Using AI Technology
This Omdena Local Chapter Challenge runs for 5 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world.
You will work on solving a local problem, initiated by Omdena Thimphu, Bhutan Chapter.
The problem
Forest fires are a serious threat to the environment, biodiversity, and livelihoods of people worldwide, and Bhutan is no exception. Every year, forest fires in Bhutan cause significant damage to natural resources, wildlife, and human settlements/life. Traditional forest fire detection methods, such as visual patrols (by anyone), are often ineffective due to the rugged terrain and large forested areas. The delay in detecting and responding to forest fires can lead to the rapid spread and uncontrollable wildfires, which can result in significant environmental and economic losses. The existing forest fire management system in Bhutan relies heavily on human resources and lacks the necessary technological support to prevent and manage forest fires effectively. Therefore, there is a need to develop an automated forest fire detection and early warning system that leverages AI technology to detect fires in real time and provide timely alerts to the relevant authorities for prompt action. The proposed system aims to provide a cost-effective and efficient solution to reduce the number of forest fires in Bhutan and mitigate their impact on the environment and local communities.
The goals
- To design and develop an AI-powered forest fire detection system that can detect fires in real-time.
- To integrate the detection system with a communication system for early warning and timely response.
- To provide a cost-effective solution for forest fire prevention and management in Bhutan.
- To raise awareness among local communities about the importance of forest fire prevention and early response.
- To reduce the number of forest fires in Bhutan and minimize the damage caused by such fires through early detection and timely response.
Why join? The uniqueness of Omdena Local Chapter Challenges
Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.
A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.
And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.
First Omdena Local Chapter Challenge?
Beginner-friendly, but also welcomes experts
Education-focused
Open-source
Duration: 4 to 8 weeks
Your Benefits
Address a significant real-world problem with your skills
Build your project portfolio
Access paid projects (as an Omdena Top Talent)
Get hired at top organizations
Requirements
Good English
Suitable for AI/ Data Science beginners but also more senior collaborators
Learning mindset
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