MIT Solve

Step 2

Our Solution

FARM-ASSIST

Our solution's stage of development:

Pre-Seed

Our solution:

Input usage in farming is mostly done with unscientific and traditional methods which lead to low productivity and wastage of resources.

We solve this using technology by collecting farm data and analyze it, using IoT and machine learning to determine optimum input requirement in different conditions and maximize yield.

Our pitch:

Use of traditional methods or hit & trials in the entire farming process leads to inefficiencies & often times have negative effects on communities (e.g Reduced crop yield, overuse of resources, overuse of pesticide causes diseases like autism, asthma, etc.).

Whatever little guidance is available through government schemes are primarily based on ideal case results, mostly irrelevant in the real world.

We provide every farmer best farming practices.

By collecting all the relevant data about the farming process like

SOIL QUALITY
CLIMATIC CONDITIONS
INPUT USAGE & EFFECTS
DISEASE & PEST RISKS

We will collect it using sensors and IoT, then use DATA ANALYTICS & MACHINE LEARNING ALGORITHMS to determine optimum actions for the farm.

Irrigation is a challenge due to water scarcity. Irrigation can be automated using IoT & sensors keeping check of humidity, temperature, soil moisture etc thus using every single drop of water in the most efficient way.

The fertility of different lands are not same but most of the time fertilizers are applied irrespective of the land conditions and the variety of seeds used for cultivation. The prime reason behind this is the unavailability of technical information & costly chemical soil test. Now using IoT & sensors soil quality (N, P, K ratio) can be checked & accordingly fertilizers can be applied.

Improper use of pesticides & other chemicals reduces food quality & makes it harmful for consumption. By monitoring, we can detect(sensor/mobile camera) any risk in very early stages minimizing & preventing use of pesticide.

Also by using different inputs (water, fertilizer, seed) and output (quantity and quality of yield) data, we can find optimum input requirement for varieties of crops in different conditions.

The process will get more and more efficient with time as more data will be available to take better decisions.

The problem:

Farmers in developing countries are mostly uneducated and hardly aware about technical aspects related to farming. They use inputs by hit and trial methods or traditional rules of thumb.

This results in very low food productivity which can easily be seen when compared to countries following modern techniques. Other problems like resource wastage, soil degradation, diseases etc also arise because of it.

As urban population grows, the demand for food also increases thus creating a significant challenge for society. Thus farming in both urban and rural areas need proper use of scarce resources in optimum way to get maximum yield.

Why our solution will solve the problem:

China_uses_half_the_water_than_India _to_produce_a_kilogram_of _rice

Different_parts_of_field_need_different_nutrition

Different crops in different soils and conditions need different inputs. Many farm parameters (e.g. soil moisture, light, nutrients, diseases etc) can be measured using available technologies like geo-mapping, nutrient sensors, computer vision etc. Thus it is possible to collect all these data and analyze it to get optimum input usage in different conditions.

As all farms have different requirements, we can provide farmers customized information about it suitable to their unique condition on a real time basis. As more & more farms get connected, more data is available to us which will make our recommendations more reliable.

Who recommended you to Solve - or - how did you find Solve?

Facebook

Step 3

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The technologies we employ:

Agricultural technology
Consumer-facing software (mobile applications, cloud services)
Digital systems (machine learning, control systems, big data)
Imaging and sensor technology

Why our solution is unique:

Our idea is connecting a large number of farmers of varying conditions, using that data to make better judgments of what works best in different situations. As more farms get connected, the data keeps on growing to make it more efficient.

Few people around the world are working in different fragments of our solution, like water management and crop protection using tech, still, none is doing it on scale and harnessing the power of data.

Farmers in India are deprived of basic soil testing and modern irrigation techniques & disease prevention. No one here is doing farm input management on scale.

Why our solution is human-centered:

Farming sector is 40% of global workforce, 60% in India. But farming is suffering from reduced profitability, and many other problems and still is untouched by modern technology. This leads to food shortage to meet world demand. On top of all these many farmers are losing the incentive to continue farming. It is a serious risk for both our workforce and human population.

Our initiative is for optimal use of resources and maximize yield. It will make farming profitable thus solving the workforce problem. It will also increase the food supply thus solving the food security problem.

How people will access our solution:

Initially, we plan to work with big farm holders to reach economies of scale and gather more data at once. We still need to figure out on working with small farm holders. We are currently exploring different options like community based farming, cooperative structure and leasing of equipment.

Our solution doesn't need any hard infrastructure, but only internet and cheap equipment like sensors and everything will be done on software. Internet is cheaply available and is growing in almost all parts of world. However, most funds will be required for prototyping & after that for operations & educating farmers.

Technology-Readiness Level:

2

Step 5

Our organization:

Not Registered as Any Organization

Where we are located:

India

How we will sustain our team financially:

Bootstrapping and grants/funding for initial research and prototyping.

Grants/funding for pilot stage, as many are available from government and other organizations for agriculture sector.

External funding and profits for growth stage.

Revenues & retained earnings when scaled.

We are exploring different ways to monetize our solution. It will be different for different crops, different regions, condition of farmers. Few ways we are considering are:

Charging for recommendations on season/crop basis
Charging on production basis (Fraction of total yield/ Profit from total yield)
Charging for disease & pest prevention services (per season/instance basis)
Sale/Leasing of equipment.
Data monetization

The factors limiting our success:

Resistance to New Technology:

Farmers in developing countries are mostly poorly educated. They have little knowledge about modern technologies. Smartphone usage is also limited even after easy accessibility and affordability. Farmers believe their traditional methods are superior to modern techniques. Therefore, farmers resist using both modern techniques and technology.

Physical Expansion:

As expansion of this solution requires a lot of ground level work, meeting and educating farmers from different regions all over the world, it will require big workforce which is not so easy to achieve.

Team Building:

Encouraging talented youth to work in agriculture sector is difficult.

How long it will take to develop a pilot:

2

How long it will take to scale beyond our pilot:

2

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