System Architecture

Data Collection Layer

The platform integrates multiple data sources:

class EnvironmentalDataCollector:
    def __init__(self):
        self.satellite_processor = SatelliteImageryProcessor()
        self.sensor_network = GroundSensorNetwork()
        self.drone_system = DroneDataCollector()
        self.weather_monitor = WeatherDataIntegrator()

    def collect_environmental_data(self):
        return {
            'satellite_data': self.satellite_processor.get_latest_imagery(),
            'ground_metrics': self.sensor_network.collect_readings(),
            'aerial_survey': self.drone_system.get_survey_data(),
            'weather_conditions': self.weather_monitor.get_current_data()
        }

AI Analysis Engine

System Architecture features

Our core AI system processes environmental data to:

• Assess forest health and biodiversity levels

• Predict potential threats and areas requiring intervention

• Optimize reforestation strategies

Conservation Management class ForestRecoveryManager:
    def __init__(self):
        self.health_analyzer = ForestHealthAnalytics()
        self.species_tracker = BiodiversityMonitor()
        self.recovery_planner = ReforestationOptimizer()
        
    def generate_recovery_plan(self, forest_area):
        health_assessment = self.health_analyzer.assess_area(forest_area)
        biodiversity_data = self.species_tracker.analyze_distribution()
        
        return self.recovery_planner.create_optimal_plan(
            health_assessment,
            biodiversity_data
        )

Blockchain Integration

Blockchain technology provides:

• Transparent tracking of reforestation progress

• Verification of conservation outcomes

• Secure funding distribution for projects

• Carbon credit certification and trading