EcoSentry AI

🌍 Project EcoSentry AI
Universal Autonomous Multi-Agent Network for Real-Time Eco-Monitoring

🚀 Vision & Overview
EcoSentry AI is a next-generation, local autonomous computer vision and multi-agent system designed for heavy-duty environmental monitoring. Built using a "Blue Ocean" strategic mindset, this project steps out of crowded, internet-dependent software solutions to deliver an entirely private, offline, edge-computing pipeline that can be deployed on moving vehicles like trains, highway patrol vans, or environmental drones.

🛠️ The Architecture (How It Works)
Our system uses a coordinated 3-Agent pipeline architecture to process data locally without any cloud API overhead:

• Agent 1: The Vision Sentry (Continuous Stream): Processes continuous live video feeds to accurately detect real-world environmental anomalies (e.g., plastic waste/wrappers on roads/tracks, industrial black soot deposits on plants, and plant stress indicated by yellow leaves).
• Agent 2: Geo-Spatial Router & Severity Index: Dynamically tags the exact coordinates (Latitude, Longitude) of the hazard and calculates a priority rating (Low, Medium, HIGH) based on the size/volume of the debris or soot.
• Agent 3: Local LLM Reporter (Ollama Service): Takes raw data from the geo-router and triggers a localized language model to draft a comprehensive, professional Markdown alert report entirely offline.

💻 Technical Implementation Script

main.py (Core Execution Loop)

python
# Core architectural engine that routes frames and detects hazards
import time
from reporter_agent import generate_eco_report

def continuous_video_stream():
    print("[INFO] Universal EcoSentry Video Stream Started...")
    count = 0
    try:
        while True:
            count += 1
            if count % 3 == 0:
                print("[ALERT] Anomaly detected by Vision Sentry!")
                final_report = generate_eco_report(
                    "Lat: 28.6139, Lon: 77.2090 (Zone 4)", 
                    "Plastic Waste Accumulation & Vegetation Damage", 
                    "HIGH"
                )
                print(final_report)
            else:
                print("[STATUS] Environment clear. No immediate hazard.")
            time.sleep(3)
    except KeyboardInterrupt:
        print("\n[INFO] EcoSentry System Stopped Safely.")

if __name__ == "__main__":
    continuous_video_stream()