mukuvi/Aquasense-AI

Addressing Africa's waste and water challenges ## Aquasense AI Discover Aquasense AI: your gateway to transformative technology for public health and environmental sustainability across Africa. Powered by AI, Aquasense is a pioneering conversational platform designed to revolutionize water management ### Structure Welcome to the Aquasense AI! Here’s how it's structured: `backend/`: Contains Python-based backend code using Flask, encompassing API endpoints, database models, and business logic. `frontend/`: Houses JavaScript, React, and Redux frontend code, including UI components in HTML, CSS, and JavaScript. `models/`: Holds trained Generative AI models in Python, crucial for enhancing Aquasense AI's capabilities like visual question answering (VQA). `bot/`: Includes source code for a Telegram bot, facilitating interaction and integration within Telegram groups. ### Problem Being Addressed Africa faces significant challenges with improper waste disposal and water shortages. Improper waste disposal in Nigeria has led to health concerns such as increased cases of diarrhea, particularly in cities like Odukpani and Akamkpa. This also contributes to environmental degradation and biodiversity loss as animals ingest plastics. In Giyani, South Africa, severe water shortages force residents to travel long distances to collect water from shared sources with animals, exacerbated by delays and budget overruns in water infrastructure projects like the Giyani Water Project. ### Proposed Solution Aquasense AI proposes a unified system utilizing AI, IoT sensors, and machine learning to address these challenges: Waste Detection: Utilizing AI and object detection technology, the system allows users to photograph areas with improper waste disposal. Geolocation data is then sent to waste management companies for prompt action, including clean-up and legal measures against illegal dumping. Water Shortage Detection: IoT sensors installed at wells and taps monitor real-time water flow and quality. Machine learning algorithms analy …