Agritech Case Study Series: Farmer Advisory Services by IBM


Solution Name: Farmer Advisory Services (Timely, localized and actionable advisory for farmers at scale, Digital Dashboard for Agriculture)

Name of Organization: IBM India

At the helm: Mr. Karan Bajwa

Core technology used:  Artificial Intelligence (AI) and Machine Learning (ML)




1. Tell us about your solution in brief.

IBM has developed a robust technology platform to address some of the fundamental challenges in improving farm yield and farmers’ income in India. This technology is based on the “data fusion” approach, where data from The Weather Company, an IBM Business (termed as Remote sensing data), satellites as well as data from the field using IOT sensors (termed as local sensing data) are fused together using AI technology to provide timely, localized and actionable Agri Advisory to farmers.

Weather data and analytics on a field-by-field or zone-by-zone basis helps farmers make informed decisions that lead to better crop output throughout the year. This further helps improve the quality of life for Farmers as the information they need as well as solutions are available via a Smart phone. Farmers can thus save time traveling to Agri Labs in search of solutions.

Some of the key features of the Farmer Advisory Services are:  

  • Pest/Disease Advisory: Crop-specific pest and disease risk prediction based on integrating Weather forecast models and Crop Health data. This advisory helps the farmers with – “When and how much pesticide/ insecticide to apply”


  • Irrigation Advisory – Irrigation management using soil moisture estimation leveraging real-time weather data from weather sensors to ensure crops are getting the right mix of sun and water. This advisory helps the farmers with – “When to irrigate and how much water to use”


  • Nutrient Advisory – This advisory helps the farmers with optimizing fertilizer usage for maximum output – “What kind and how much fertilizer to use”


Graphic shown below provides an overall solution approach and high-level architecture:






 2. Mention the geographic area where your solution is implemented and give us details of the intervention.

Geo-graphic area: Indian states

Technology/Capability Used:

  • Remote sensing (Satellite based data)
  • Hyperlocal Weather Data from The Weather Company
  • Local sensors
  • IBM Watson IoT Platform
  • The Weather Company provides Historical Weather data with Seasonal and Enhanced Forecast data which helps in the triangulation and forecasting of value added services to crop cycles. Additionally the ‘Current Conditions’ data sets help to predict Hail Storms and other local weather events
  • The Weather Company’s Agricultural Dashboard provides real time weather insights in a graphical format which is extremely useful for decision-making on soil-moisture, soil-temperature and evaporal-transportation.


3. What was the objective of the project and how much of it was achieved?

  • Provide highly affordable and scalable Farmer Advisory Services by combining remote sensing, Weather Data and local sensing via IoT
  • Provide fundamental parameters like crop health (NDVI), soil moisture at the best possible resolution available from remote sensing analytics alone
  • Using leading edge technology to maximize crop yield and optimize use of farm input

4. Give details of the cost of your solution and scope of scalability

Scope for scalability:

  • Farmer Advisory Services based on remote sensing can be scaled up to 50-100 million farmers across India
  • Multiple crops
  • Multiple agro-climatic zones


5. Are you looking for partners? Mention details of partnership.

The Weather Company, an IBM Business, is looking at developing the AgriTech Partner Ecosystem and is seeking partners who will further add value to enhance Farmer Output.


To see other agritech companies in the series, follow agritech case studies

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