AI based National Pest surveillance system

1. In Aug 2024, the central government has introduced the National Pest Surveillance System (NPSS).
2. It is an AI-powered platform designed to connect farmers with agricultural scientists and experts, improving pest control strategies.
3. This initiative aims to shift farmers' dependence away from pesticide retailers and towards scientifically backed pest management techniques.
4. The NPSS offers regular and accurate pest management advisories and promotes Integrated Pest Management (IPM).
5. It functions under the Directorate of Plant Protection, Quarantine & Storage, which operates under the Ministry of Agriculture.

Need for NPSS

1. Reduce farmers' reliance on pesticide retailers.
2. Address the overuse of pesticides.
3. Prevent losses in food production due to pest attacks, which account for up to 20%.

Key Features of the NPSS Platform

1. AI-Powered Insights: The platform uses Artificial Intelligence (AI) to process real-time pest infestation (invasion of insects) data, enabling timely intervention.
2. Direct Farmer-Expert Interaction: Farmers can upload images of affected crops or pests through their mobile phones, allowing experts to provide quick diagnoses and recommendations.
3. Reduced Pesticide Usage: NPSS offers precise pest management solutions, helping reduce the excessive use of pesticides and encouraging sustainable farming.
4. Wide Accessibility: The system is designed to reach around 140 million farmers nationwide, making expert guidance more accessible.
5. Pesticide Purchase Prevention: By offering accurate pest control advice, the platform helps farmers avoid unnecessary pesticide purchases.
6. Localised Support: State-level outreach programs will promote the platform, ensuring farmers receive pest management advice tailored to their specific regional needs.

AI and Agriculture Artificial Intelligence (AI) has the potential to solve issues related to food insecurity, climate change, and low agricultural yield. Applications of AI in Agriculture Diagnostic: Detects water stress, pest infestations, and disease outbreaks. Prescriptive: Analyzes soil health and prescribes appropriate fertilizers (e.g., SENSAGRI: SENsor-based Smart AGRIculture). Advisory: Provides weather forecasts and irrigation schedules. Predictive: Forecasts crop yield, predicts pest attacks, and issues early warnings (e.g., BharatAgri App). Challenges in AI Adoption in Indian Agriculture Policy Gaps: Lack of comprehensive data governance, enforcement, and regulations. Farmer Resistance: Reluctance to adopt new technologies due to risk aversion (strong dislike) and mistrust. Digital Divide: Small-scale farmers struggle with limited access to digital infrastructure. High Initial Costs: Significant investments required, making it difficult for small farmers to adopt. Initiatives Promoting AI in Agriculture Kisan e-Mitra: An AI-powered chatbot that helps farmers with queries related to the PM Kisan Samman Nidhi scheme. AI for Agriculture Innovation (AI4AI): An initiative by the World Economic Forum to promote AI-driven agricultural innovations. The Saagu-Baagu project was introduced under this initiative to promote agricultural innovation in Telangana. AI-based analytics for monitoring crop health using satellite data, focusing on rice and wheat crops.

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