https://github.com/yessasvini23/enviroguard-ai-real-time_-hazard-detection-_-_ai-assistant
Imagine a world where AI actively monitors your environment, detecting fire, smoke, pollution, and wildlife hazards in real time. EnviroGuard AI combines computer vision, IoT sensors, and AI-driven insights to provide instant alerts and natural language interaction.
https://github.com/yessasvini23/enviroguard-ai-real-time_-hazard-detection-_-_ai-assistant
geminiai gtts huggingfacemodel iot-application langchain opencv whisper
Last synced: 7 months ago
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Imagine a world where AI actively monitors your environment, detecting fire, smoke, pollution, and wildlife hazards in real time. EnviroGuard AI combines computer vision, IoT sensors, and AI-driven insights to provide instant alerts and natural language interaction.
- Host: GitHub
- URL: https://github.com/yessasvini23/enviroguard-ai-real-time_-hazard-detection-_-_ai-assistant
- Owner: yessasvini23
- License: mit
- Created: 2025-04-02T18:48:44.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-04-03T05:43:28.000Z (7 months ago)
- Last Synced: 2025-04-09T16:14:10.421Z (7 months ago)
- Topics: geminiai, gtts, huggingfacemodel, iot-application, langchain, opencv, whisper
- Language: Python
- Homepage:
- Size: 17.4 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# EnviroGuard AI - Real-time Hazard Detection & AI Assistant
## 🌍 Overview
**EnviroGuard AI** is an advanced **real-time environmental monitoring system** that leverages **computer vision, AI, and IoT sensors** to detect hazards like **fire, smoke, pollution, and wildlife intrusions**. It also features **interactive AI-driven insights** via natural language processing, making it a powerful tool for **smart cities, industrial safety, and environmental conservation**.
## 🚀 Features
- 🔥 **Real-time hazard detection** (fire, smoke, air quality, wildlife recognition)
- 🤖 **AI-powered Q&A** (Ask about environmental conditions, pollution levels, etc.)
- 🎙 **Voice alerts & interaction** (STT & TTS for accessibility)
- 🌡 **IoT sensor integration** (Air quality, temperature, gas sensors)
- 📊 **Historical data analysis** (Track environmental changes over time)
- 🌐 **Web & mobile-friendly interface** (For easy access & monitoring)
## 🛠 Technology Stack
| Component | Technology Used |
| ------------------------ | ------------------------------------- |
| **Computer Vision** | OpenCV, YOLO, ViT, TensorFlow/PyTorch |
| **AI & NLP** | LangChain, Gemini AI |
| **Voice Processing** | gTTS, Whisper |
| **IoT Integration** | MQTT, Raspberry Pi, NodeMCU |
| **Web/Mobile Interface** | Gradio, Streamlit, FastAPI |
| **Cloud & Storage** | AWS, Firebase, GCP |
## 📌 Installation
1. **Clone the repository**:
```bash
git clone https://github.com/yourusername/EnviroGuard-AI.git
cd EnviroGuard-AI
```
2. **Install dependencies**:
```bash
pip install -r requirements.txt
```
3. **Run the application**:
```bash
python main.py
```
## 🏗 System Architecture
1. **Input Sources**:
- Video feeds (CCTV, drones, mobile cameras)
- IoT sensors (air quality, temperature, gas detection)
- User queries (text/voice interactions)
2. **Processing Modules**:
- **Computer Vision Models** for hazard detection
- **AI-powered Q&A** using LangChain & Gemini AI
- **Sensor Fusion** to combine vision & IoT data
3. **Output & Alerts**:
- **Web Dashboard & Mobile App** for real-time monitoring
- **Voice & text-based alerts** for hazards
- **Geospatial hazard mapping** for visualization
## 🔥 Use Cases
- **Smart Cities:** Automated environmental monitoring & emergency alerts
- **Industrial Safety:** Fire & pollution detection in factories & plants
- **Wildlife Conservation:** Detecting endangered species & intrusions
- **Public Health:** Real-time air quality tracking & pollution insights
## ⚡ Challenges & Solutions
- **Latency in detection:** Optimized AI models for faster processing
- **Multi-modal data fusion:** Seamless integration of video, sensors, and NLP
- **Deployment on Edge Devices:** Lightweight models for Raspberry Pi/Jetson Nano
## 🚧 Roadmap
- ✅ Wildlife detection enhancement using YOLOv8
- 🔜 Mobile app deployment for remote monitoring
- 🔜 AI-driven preventive hazard alerts
## 📜 License
This project is licensed under the [MIT License](LICENSE).
## Deplpyment
https://www.veed.io/view/f291da0b-059b-4313-8b44-674f527c3509?panel=share
## 📬 Contact
For questions, suggestions, or collaborations, reach out:
- 📧 Email: [yessasvini.s@gmail.com](mailto\:yessasvini.s@gmail.com)
- 🐙 GitHub: yessasvini23
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### 🚀 *EnviroGuard AI - Smart Vision for a Safer Planet*