Agricultural Monitoring and Event Detection (AMED) API

  • 15 Jul 2025

In News:

Google has introduced a set of artificial intelligence (AI)-based innovations to advance India’s agricultural practices and enhance the cultural and linguistic relevance of global AI models.

Agricultural Monitoring and Event Detection (AMED) API

  • Launched by: Google DeepMind and Google’s Partnerships Innovation Team
  • Collaborators: TerraStack, IIT-Kharagpur, and other local partners
  • Foundation: Built on the Agricultural Landscape Understanding (ALU) API launched in 2023
  • Key Features:
  • AI-Based Field Monitoring: Offers field-level insights using satellite imagery and deep learning to monitor crops and agricultural activity.
  • Crop-Specific Data: Provides details on crop type, season, field size, and three years of historical cropping and land-use data.
  • Event Detection: Detects agricultural changes at individual field levels, improving yield prediction and input management.
  • Biweekly Updates: Data refreshed every two weeks to ensure real-time agricultural monitoring.
  • Open Access for Innovation: Available for integration by agri-tech startups, financial institutions, and government bodies to support data-backed rural lending, climate adaptation, and sustainable farming practices.
  • Objectives and Utility:
  • Empower agriculture stakeholders with granular, real-time intelligence.
  • Facilitate precision agriculture by tailoring support for soil, water, and climatic needs.
  • Strengthen India's resilience to climate-related risks and promote informed policymaking.
  • Help financial services design location-specific rural credit systems.

Amplify Initiative: Cultural and Linguistic Localization of AI

Google is also working to enrich AI systems with deeper understanding of India’s diversity through the Amplify Initiative, piloted earlier in Sub-Saharan Africa.

Indian Collaboration:

  • Partner Institution: IIT-Kharagpur
  • Goal: Create hyperlocal annotated datasets in multiple Indic languages related to healthcare, safety, and social issues.
  • Aims to ensure that Large Language Models (LLMs) are better aligned with India’s cultural plurality and linguistic complexity.

Global Impact:

  • Builds on success in Africa, where 8,000+ queries in 7 languages were developed by 155 experts to address issues such as chronic illness and misinformation.