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IoTMachine LearningComputer Vision
IoT Environmental Monitoring System
Environmental•6 months
The Challenge
The institute needed to monitor air quality, water quality, and wildlife patterns across a 500-square-mile area but lacked the resources for continuous manual monitoring.
The Solution
We deployed a network of IoT sensors and camera traps across the research area, connected via LoRaWAN. The system uses computer vision to identify and count wildlife species, and machine learning models to predict pollution events and ecological changes.
Technology Stack
LoRaWANTensorFlowYOLOInfluxDBGrafanaPythonReact DashboardAWS IoT
Results
Monitoring Coverage
24/7 automated
Data Collection Points
15x increase
Wildlife Identification Accuracy
91%
Early Warning System
2-5 days advance notice
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