Abstract

Concept

Abstract

In 2014, the National Disaster Response Fund (NDRF) provided 3,347cr (of a total of 9,018cr) of drought relief to states; 107 districts were declared as drought affected. In 2015, drought relief for the summer Kharif crops 12,773cr, a 281.6% increase; drought affected 263 districts, in KA(30), CT(25), MP(51), MH(36), UP(75) and RJ(33).

Given the growing acute shortage of water resources across the country, the future of food production is at risk without the the capacity to deliver effective water management techniques & strategies on a national scale.
The primary goal of this project is to create the foundation for a national argo-information infrastructure that connects any farm (both controlled or open environment agriculture) to enable the capability to address the breakthroughs in advanced agricultural techniques that need information technology at its core such as: remote monitoring, decision support, data gathering, and precision farming.

Rationale

A general solution to a national water management problem must enable:

• Farm automation for optimized water usage to reduce incidents of 'peak irrigation'.
• Dissemination of crop-specific best practice on efficient water utilization
• Data analytic tools used for research on the effectiveness of the current farm practices.

To solve such a problem on a national scale, we need to find ways to deliver agricultural best-practices using IT as an enabler to reduce cost and increase scale.

In the proposed project, models & plans to address water shortage is delivered through the Internet to precision farms that use low-cost micro-controllers, sensors & actuators, the Internet and mobiles services, to monitor and control the farm. We build it to connect farms across India to a centralized service that monitors individual farms as well as the state of agricultural practice at a national scale.

Objectives

We have the following primary objective and two supporting objectives for this project.

Primary Objective

The primary objective is to applyof such an infrastructure to address the single most critical threat to the future of food supplies and agricultural production in India: water shortage. This goal will be achieved by delivering a remotely controlled, fully automated, efficient irrigation management system to all farms in the experimental network.

Activities

• Build sensor nodes to capture soil moisture levels & send it to the internet via mobile network
• Build Internet services to collect sensor data and make it available for decisions.
• Build farm management controller to coordinate drip irrigation activities based on sensor data.
• Develop a mobile phone application to administer & monitor the irrigation plan for a farm.

Secondary Objective - 1

A secondary objective is to provide researchers with the tools to analyze the large amount of data aggregated by collecting sensor data across the country to identify trends, patterns and insights into the state of agriculture on a nationak scale.

Activities

• Build Internet services to collect sensor data and make it available for decisions.
• Provide research oriented tools to analyze trends and identify patterns in large data sets.
• Prorvide a simple dashboards of perf. indicators to summarize the state of agriculture.

Secondary Objective - 2

A third objective is to provide crop advisory and cultivation planning capabilities based on analysis of climatic trends, pricing trends, patterns of crop failures, consumption trends and land utilization. The data used for this analysis will initially be based on models using percipitation forcasts, historical sensor data and expert (researchers) advice.
Current practices on crop advisory are largely based on statistical models and computer simulations. With the immediate access to historical sensor data and the farm's characteristics (geographical location, topology, environmental facts etc.), it becomes possible to use other readily available real-time weather and pricing information to generate more sophisticated and realistic models (using risk models, game theory, logistic regression or linear programming) of farm behavior. These models then allow us to decide what optimal cultivation plan will generate the most revenue for the farmer.

Activities

• Build Internet services to collect sensor data and make it available for decisions.
• Provide modeling tools to simulate farm behavior and simplify generation of a farming plan.
• Demonstrate a set of practical models of farm behavior under various irrigation plans.

Expected Results

• Development of a farm automation system that manages a 1 hectare farm at a cost of Rs. 10000 for the system, takes 10hr to deploy and suffers less than 10hr of downtime per year.
• Irrigation automation system that reduces average water utilization in a farm by 40%.
• Delivery of a suite of tools that will be used during the project to develop optimized irrigation plans.
• Deliver of a suite of software to visualize and analyze the trends and patterns of farm practice in the experimental farms.
• Build an experimental network around 40 currently functioning polyhouse farms in Trivandrum, Kerala and fully automate management of its irrigation needs.

Performance Metrics

The following performance metrics will be used to measure the performance of the farm and by extension the capability of the platform.

• Average Water Utilization: The total water consumed during a given period per hectare of arable soil. The baseline of measurement will the the average water utilization per hectare at the start of the project.
• Downtime: The amount of time a particular sensor or actuator node is brought down per year.
• Data Throughput: The amount of data collected from all the sensors during an hour in a hectare of arable soil.
• Response Time: The average amount of time required to perform a sensor command issued from the centralized server hosted on the internet.