The problem GreenMindAi solves

-Problems Solved:

1.Uncontrolled Waste Disposal: In India, irresponsible waste disposal leads to garbage piles in public spaces.
Environmental Pollution: Poor waste management contributes to air, water, and soil pollution.

2.Public Health Risks: Accumulated waste increases the risk of diseases in communities.

3.Resource Wastage: Valuable recyclables are lost due to improper disposal.

4.Inefficient Waste Monitoring: Current systems lack reliable tracking of waste disposal and cleanup.

5.Lack of Government Attention: Waste issues often go unnoticed due to insufficient reporting.

-Solutions Provided:

1.AI-Powered Waste Scanning: Scans waste to identify its type, quantity, and AI confidence level, storing this data with the user’s location for monitoring.

2.Reward System: Users earn points for reporting waste, which can be redeemed for rewards, encouraging responsible disposal.

3.Leaderboard Page: Ranks users based on their waste reporting activities, promoting competition.

4.Photo Verification: Users upload real-time photos after collection, which the system verifies for accuracy.
Government Reporting Tool: Serves as a reporting system, highlighting issues for prompt government action.

5.Data Showcase: Displays real-time waste data, allowing tracking by users and authorities.

6.Efficient Cleanup Tracking: Location verification ensures reported waste is cleaned up, improving accountability.

-Drawbacks and its Solution:

1.Real-Time Image Capture: Users must take live photos of waste to prevent altered or outdated submissions.

2.Preventing Image Reuse: The system captures the user’s current location to stop repeated uploads, using tools like GeoComply for accurate tracking.

-Note:We have excluded the real-time capture and location features from this demo. Including these features would prevent us from uploading multiple images and limit our ability to showcase the website's functionality effectively.

Challenges we ran into

-Challenges Faced During Development:

1.AI Model Accuracy: Ensuring that the AI model accurately identifies and categorizes different types of waste was a significant challenge. We focused on improving its recognition capabilities and confidence levels through rigorous testing and feedback.
2.Integration of Location Services: Accurately capturing and verifying user locations while avoiding spoofing or manipulation by VPNs presented a challenge. We needed to implement reliable location tracking systems that could work effectively in various environments.
3.Image Upload Limitations: Managing the upload of multiple images efficiently while ensuring the system processes them correctly required careful planning and implementation to avoid bottlenecks.
4.User Engagement: Designing an intuitive interface that encourages user participation was crucial. We faced challenges in gamifying the experience to motivate users without making it overly complicated.