A Social Life Network to enable farmers to meet the varying food demands Professor Gihan Wikramanayake University of Colombo School of Computing

Social Networks Connecting People

Mobile phone used to be a phone. It is now a – Phone – Camera and an album – GPS – Music system – Video Game console – Communication device – Personal Assistant – Computer – Information source – … much more What is a Mobile Phone?

Social Life Networks Connecting People and Public Resources

Creating a better market dispersion Market Farmer A Farmer B Farmer C LandMarket

Creating a better market dispersion Land Farmer A Farmer B Farmer C Market

Creating a better market dispersion Land Farmer A Farmer B Farmer C Market shop B Market shop B

Creating a better market dispersion LandMarket Market A Mkt B Market C Farmer A Farmer B Farmer C

9 Information / Alters

Framework for Situation Analysis Level 3: Event Graph Level 2: S-T-T Aggregate Level 1: S-T-T Data RepresentationTransformationCharacterisations Properties More abstraction Less details Less abstraction More details Examples NYC,02/12/11, Flu Case Raw Data – e.g. Tweets, photos, weather, RSS

Where to open the next store? Situation Analysis...

Middle 3.5 Billion Top 1.5 Billion Bottom 1.5 Billion MOP: Strengthening Information Environment TOP: Strong Information Environment BOP: Deprived of Information Middle of the Pyramid Ref: Ramesh Jain

Use Mobile Phones – no text – for interactions Provides integrated view of : Disease Risk (Sensor and Model based), Actual Symptoms and (Human Observation), Disease Severity based on Images or by Image processing Expert's ConsoleFarmer's Mobile phone application No Typing required, local language support, images and speech useful for illiterate rural masses Used by more than 5,000 Farmers in remote areas in India.

Use Mobile Phones – no text – for interactions

Implementation Plan Contextual Inquiry. Supply chain Process mapping. Identifying the varying information needs of different stake-holders to enable decision- making. Design of analytical models to enable aggregation of information from multiple sources to meet the identified information needs.

Overall System Architecture and Functionality Input / activityOutput Micro Information / blogAlert QueryReply BrowsingOrganised aggregated information Input: images, voice, text, symbols, sensory data Output

Research Methodology Exploring possibilities using Action Research Requirements for Aggregation Unit Aggregation Unit Requirements for Processing Unit Processing Unit Requirements for User Interface Unit Mobile App Evaluation Stakeholder Needs SLN for Farmers Requirements Artefacts Evaluations

Farmer Information Need Analysis

What Crop to Grow? What are the best seeds to be cultivated? (Quality) From whom/where to buy good quality seeds at a lower rate? (Quality / Resource Prices) How much yield is estimated for the selected vegetable seeds? (Prediction) What are the precautions to be carried out to avoid specific pest and diseases? (Quality / Precautions / Decision taking) Information Need...

High Level Conceptual Architecture

Mobile UI Development

Seeds Soil fertilizer Weather Pest disease & remedies places to buy places to sell Prices at markets / economic center traditional knowledge and practices... Knowledge Management

Agriculture Ontology for SLN

Implementation Plan Further development of analytical models. Development of architecture for the Information System deployment. Develop Prototype Information System and trials. Extend analytical models by incorporating predictive models for prediction of future demand based on historical data and other trends.

User Empowerment Given some information How can we assist user to act on that information From user action How can we extract useful information

Implementation Plan business models sustainable deployment maintenance Refine the prototype based on feedback Large scale field-testing.

Expert Console Voice query Picture Info specific to crop From public website Ready references for expert Sensor data – if applicable

Maps

Implementation Plan Refinements to the system based on field trials. Assist with the deployment, technology transfer, and training. Generalization of the findings for wider applicability and publishing the insights gained.

Recognition recognition + augmented reality

People