Utpal-Mishra/Omdena-Tanzania-OpenDevEd

OpenDevEd: AI-Driven Temperature Analysis for Educational Environments in Tanzania # AI-Driven Temperature Analysis for Educational Environments in Tanzania This repository contains details and outcomes from the collaborative project between Omdena and OpenDevEd, which focused on developing an AI-driven predictive model to analyze indoor classroom temperatures in Tanzanian schools. ## Table of Contents 1. Problem Statement 2. Impact of the Problem 3. Goal 4. Approach 5. Project Phases 6. Implementation 7. Metrics for Success 8. Future Work 9. License 10. Contact ## Problem Statement In countries with a hot climate, such as Tanzania, many schools experience classroom conditions characterized by extreme temperatures, which can severely impede the learning process and pose significant health risks to students. The primary challenge lies in the need for more detailed, actionable data regarding specific classroom features that influence indoor temperatures, such as roofing materials and the presence or absence of ceiling boards. Traditional methods for monitoring and improving these conditions often fall short because they need to provide the precise, localized information necessary for effective intervention. ## Impact of the Problem 1. **Ineffective Learning Environments:** High temperatures hinder student concentration and learning effectiveness. 2. **Health Risks:** Extreme temperatures can lead to heat-related illnesses among students and staff. 3. **Inadequate Resource Allocation:** Without accurate data, resources may be misallocated, failing to address the most critical needs. 4. **Barriers to Policy Implementation:** Insufficient data hampers policymakers' ability to implement effective strategies for improving classroom environments. ## Goal The primary goal of this project is to develop an AI-driven predictive model using satellite imagery and environmental data to estimate indoor classroom temperatures in Tanzanian schools, enhancing learning environments and health safety. The model determines temperature conditions based on observabl …