Madhya Pradesh has made a huge leap toward conserving the forest with India's first ever real-time AI-based forest alert system. Satellite images, artificial intelligence, and field reporting over mobile are the key to finding encroachment in land, felling trees, and similar activities in forest land. Five forest divisions will pilot the effort that can act as a model for successful management of forests in India.

Madhya Pradesh has developed India's first AI-driven real-time forest alert system, a pioneering effort that is aimed at intensifying forest conservation measures. Utilizing cutting-edge technologies such as satellite imagery, mobile inputs, and artificial intelligence (AI), the system is set to enhance forest surveillance and enhance response to land encroachment and forest degradation.

Aim of the System

Proactive Monitoring: The system will identify changes in land use, deforestation, and encroachment, allowing for corrective measures to be taken immediately.

Real-Time Alerts: Satellite images trigger alerts, which are automatically forwarded to ground-level staff for verification and action.

Importance of the Initiative

First of Its Kind: Madhya Pradesh is the first to use AI and satellite data for monitoring forests, giving other states a benchmark.

Efficiency: With real-time data, the forest officers can respond quickly to solve problems such as illicit felling and land encroachment.

Sustainability: Through identifying and reacting to environmental changes more quickly, the system helps in improved conservation and sustainable forest management.

Background

The project is a reaction to recurring problems such as illegal logging and land encroachment in forested regions of Madhya Pradesh.

The system makes use of satellite imagery from Google Earth Engine and AI algorithms to monitor land use change such as vegetation change, building, or agricultural encroachment.

Important Facts

Pilot Project: The system is being piloted in five critical forest divisions: Shivpuri, Guna, Vidisha, Burhanpur, and Khandwa.

AI Integration: Machine learning algorithms constantly enhance the precision of predictions and alerts based on field data.

Data Features: Every alert contains more than 20 data points, such as GPS-tagged images, voice recordings, and mobile app survey comments.

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