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Data analytics for agriculture

  1. Data Analytics for Agriculture Santanu Chaudhury IIT Delhi
  2. Data: Open Data ++ • Agricultural Data • Structure & Unstructured • Public & Private • Gross and Precision • Numerical, Categorical, Textual, Spatial • Images • Variety and Velocity • Climate/Weather, Soil • Produce • Crop, horticulture, livestock, fisheries • Disease, Stress factors, fertiliser/chemical usage • Mechanisation, Power, Irrigation • Market Prices (available as open data)
  3. Challenges • Data to Actionable Outcome • Actionable outcome: • Bridge between Service Providers and Service Consumers • Apps to provide link • Big data analytics • Algorithms as Service • Structured between Cloud and End-user delivery platform like mobile • Service on demand • Predictive Analytics • Example -Market Intelligence • Diagnostic Analytics • Example- Process Intelligence
  4. DeliveryModalities:AStudy Gaps Identified Way Forward Mobile Based Initiatives Text SMS Generic Information Delivered Requirement for farmer’s specific information Language / Literacy Barrier Requirement for voice & Image based information Exchange Limited records of the farmers & their farming details Requirement for Updated info No direct interaction with expert (for push based services) Requirement for Personalized Advisory Voice Calls Largely Push based services and information delivery at undesired time Requirement of right information at right time as time desired by farmer No direct interaction with the expert (for push based services) Requirement for Personalized Advisory Call Centre / IVRS Information provided (at both ends) on voice alone is not always complete Requirement for other modes of information exchange for better understanding Limited records / database of the farmers Requirement for complete & updated database - Farm & Farmers No / very limited follow up of services Requirement for Experts field visit and other feedback mechanisms
  5. Example Scenarios
  6. Agri-business • Collection of data on supply, demand and price trends of selected agricultural products in green market, wholesale markets, livestock markets, slaughterhouses and silos • Analysis of the collected data and dissemination of market information on selected agricultural products (fruits, vegetables, livestock, cereals, feed and inputs) • Enable farmers, creators of the agrarian policy, enterprises and other participants in making sound business decisions regarding production and marketing of agricultural products
  7. Agro-Advisory • Information need for farmer • Information requirement for input provider • Forecast demand correctly, to forecast crop yielding, to determine land area and usage • Real time online input for problems and difficulty • Sharing of mechanised appliances • Farmers can plan, run and analyse their entire farming operation through the entire farming cycle as efficiently as possible • Input providers can devise adaptive strategy for profitability and marketing • Responsible & Clean technology
  8. Integrated Services Customised agricultural advice access to credit and insurance products access agricultural inputs and a channel for selling their final produce – all on an integrated platform 8/11/2013 8 Requirement Driven Model Data Anaalytics Service Knowledge Service
  9. IASP – Proposed Structure
  10. Interactive Information Dissemination System for farmers : Pull and Push based system : Data can be transmitted through voice, text, images and videos from both end (farmers to expert and back). Multi-platform: Web, Mobile & IVRS Multilingual Web Portal and IVRS : Currently available in Hindi, Telugu & English Personalized Agro Advisory Based on 'Farm & Farmer Profile’ Integrated Multi-platform Data Analytics Delivery