Academic
An IoT System for Organic Farming
Organic farming is often discussed as a sustainable alternative, but for marginal farmers, the transition is risky and uncertain. This team project explored how design, data, and physical computing can support farmers during the difficult conversion period from chemical to organic farming, while also enabling government bodies to promote and scale sustainable practices.
The Challenge
For many farmers, switching to organic farming means facing immediate losses. During the 3–5 year conversion period, soil productivity drops, certification is delayed, and access to expert guidance is limited. Subsidies favor chemical fertilizers, organic practices lack standardization, and reliable data on soil health is often unavailable.
The core challenge was to design a system that supports farmers financially and operationally during this transition, while helping agricultural departments encourage organic farming at a regional level.
Research
The project began with primary and secondary research to understand the ecosystem around organic farming.
These conversations helped us understand on-ground realities, pain points, and decision-making constraints. Secondary research focused on government policies, organic certification processes, market trends, and sustainability reports.
The research revealed gaps in access to soil data, expert knowledge, and coordinated support systems during the transition period. We understoof that since 86.2% of Indian farmers are small and marginal farmers, with less than 2.4 acres of land - feasibility and accessibility played a large role.
Understanding the System
Organic farming is not an individual effort. It involves farmers, agriculture officers, experts, seed banks, and policy frameworks. To make sense of this complexity, we mapped stakeholders, data flows, and value exchanges using affinity mapping and system mapping.
This helped identify where data breaks down, where trust is missing, and where design interventions could enable better coordination and decision-making. We identified challenges in transitioning to organic farming such as - increased pest infestations, lack of access to knowledge about nutrient replenishment cycles etc and solved for these gaps using tech and design.
Based on the research, we defined three key goals:
Reduce uncertainty for farmers during the transition period
Enable data-driven decision-making at the farm level
Support standardization and knowledge sharing across the ecosystem
The solution needed to work across physical environments, digital interfaces, and institutional systems.
The Solution
Jaivik Mitra ( 'Organic friend' in Hindi) is an IoT-enabled system that combines physical devices, mobile applications, and dashboards to support organic farming.
The system includes:
A constant soil monitoring device for real-time soil health data ( Placed in the farm)
A portable soil nutrient testing device ( Rented by the farmer bi-annually)
A mobile app for farmers to understand soil conditions, plan crops, access organic inputs, identify diseases and connect with a community of farmers.
A dashboard for agriculture officers to monitor progress and guide interventions
Together, these tools enable farmers to make informed decisions while giving authorities better visibility into regional farming practices.
As part of the project, we designed and prototyped both hardware and digital interfaces. This included physical computing for soil sensors, interaction design for the farmer app, ML Model for disease identification and data visualization for dashboards.
Final Thoughts
This project helped us understand how design can operate at a systems level, especially in complex domains like agriculture. We learned how data, devices, and people must work together to support behavior change and long-term sustainability. It pushed us to think beyond screens and design for ecosystems. By combining research, physical computing, interaction design, and data systems, the project explored how design can support livelihoods while enabling sustainable change.
