Page 41 - AI for Good-Innovate for Impact

AI for Good-Innovate for Impact

aims to promote data sharing and enable access to the exchange of data between
government agencies, research institutions, and other stakeholders to support evidence-
based policymaking and development initiatives.

UN Goals: 5 - UW

• SDG 2: Zero Hunger
• SDG 9: Industry, Innovation, and Infrastructure.
• SDG 13: Climate Action
• SDG 15: Life on Land

Justify UN Goals selection:

1. Data Integration: By unifying data from multiple government agencies such as IASRI, IISS,
IMD, ISRO, and others, AI models can provide comprehensive insights into various aspects
of agriculture, including crop production, soil health, weather patterns, and market trends.
This integrated data approach enables evidence-based decision-making and supports
initiatives aimed at achieving Zero Hunger and promoting sustainable agriculture.
2. Precision Agriculture: AI-driven technologies offer farmers precise information and
recommendations tailored to their specific needs and conditions. This precision
agriculture approach increases resource efficiency, minimizes environmental impact, and
contributes to achieving Sustainable Development Goals (SDGs) related to climate action
and sustainable land use.
3. Policy Formulation: By leveraging AI-driven insights, government agencies can formulate
more effective policies and programs to promote agricultural development, ensure food
security, and address key challenges in the sector. This policy alignment contributes to
achieving SDGs related to Zero Hunger, Industry, Innovation, and Infrastructure, and
Climate Action.
4. Capacity Building: AI technologies can also facilitate capacity building initiatives by
providing training and education to farmers on modern agricultural practices, technology
adoption, and climate-smart farming techniques. This capacity building enhances
resilience, promotes sustainable livelihoods, and supports the achievement of SDGs
related to Zero Hunger and Life on Land.

5�2�2 Future work

However, the current digital platform does not optimize the data between multiple government
agencies. Unifying the data of various agencies and using machine learning models to predict
the best plans, policies, and strategies using data will help relevant stakeholders make informed
decisions and implement effective interventions for sustainable agriculture and development.

We propose to use an AI-based strategic model to enable decision-making based on
comprehensive government data related to agriculture, including crop production, land use,
water use, market prices, weather patterns, and government schemes to enable farmers to
make informed decisions by leveraging the existing data.

5�3� Use case requirements

• REQ-01: Data Integration and Standardization - Required data from various sources
mentioned above in the references.
• REQ-02: Machine Learning Models - predictive analytics, analyzing historical data to
forecast crop yields.
• REQ-03: User Friendly Interface - To interact with the AI driven decision support system

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