IoT Technology Is Helping An Agrarian Community In Crisis

Farming in India has been in crisis mode for some time, and it only seems to be getting worse. Factors such as drought and unseasonable rains are lowering yields of cash crops, and even with lower levels of production, global commodities prices are continuing to fall–greatly impacting farmer's welfare.

The impact of these environmental and economic conditions has been devastating for a large portion of the population that depends on agriculture. Families are facing mounting debt, and these stresses have led to a growing mental health crisis in the community. Pooja Baraskar is an Intel® Software Innovator making a big impact in the small town in central India where she hails from. Having seen the struggles of her agrarian community, she looked to Internet of Things technology to find simple solutions that would increase the quality of life for those around her. Her app, Kisani ("farmer" in Hindi), uses IoT technology to assist farmers in optimizing their crops for the highest possible yields.

We spoke to Pooja about her vision for implementing Intel® IoT Technology to change her community.

MB: Hi Pooja, thanks for speaking with us. Can you tell us a little about your project, Kisani?

I describe Kisani as a farmer's best friend. It's an IoT-based application that suggests to farmers the crops that should be planted to get the maximum yield for their production.

Instead of merely planting traditional crops, the IoT-based device will evaluate the environmental conditions and soil conditions and suggest the crops accordingly. MB: Where did the inspiration for the project come from?

India is an agrarian country with around 60% of its people depending directly or indirectly upon agriculture. I am from the central part of India where the main occupation is farming. I realized that technology could help very much in solving this problem and making the life of a farmer easier. The conditions of the farming community are alarming. Most farmers are now leading an awfully despondent life.

We are noticing that in many, many suicide cases, 11.2% are farmers. In India, we are seeing one farmer suicide every 30 minutes. Because they are getting less production from fields, they are doing these terrible things. In 2014, the National Crime Records Bureau of India reported 5,650 farmer suicides.

MB: So the project seeks to increase a farmer's productivity?

Yes. In countries like India where the main occupation is farming, families are cultivating traditional crops irrespective of their field type. This results in less production due to rapidly changing weather, lack of irrigation facility, unsuitable soil type, and other factors. The Indian Government is very concerned for them and has taken many steps like "Kisan Vani" and "Kisan TV Channel", meant to educate, but these are not always helpful, as suggestions are not tailored to an individual's farm specifically.

Every piece of agricultural land is different from another. If we plant the same set of traditional crops, it will lead to less cultivation. If we plant a right crop according to the land conditions, it will make a huge difference.

Kisani, the Farmer's Guide, is an IoT-based application that will smartly suggest the right crops to be planted, to achieve maximum production with their available resources. Predicting the right crop for their field will surely save a lot of water and other resources. The device will be smart enough to evaluate the continuous pattern of data based on sensors and farmer's activities with machine learning.

Instead of suggesting that farmers buy products to increase productivity, the idea is to get the maximum production within their available resources by planting right crops at the right time. Water supply will be automatically cut off if the crops are sufficiently hydrated, and start again according to their needs, hence no need for manual monitoring. Farmers can also seek expert help through the mobile app as sensor data will be automatically transmitted to nearby Kisan Seva Kendra (farmer help centers). MB: It sounds like farming practices are largely based on tradition. Do you foresee a challenge in encouraging local farmers to break those traditions? Would you encourage them to plant crops that aren't necessarily endemic to the region, but would perform well in those environmental conditions? In India, the major crops are wheat, rice, and a variety of vegetables. There aren't a large variety of crops grown in India. In central India, where the farmland is quite vast, mostly wheat is grown. These are the staple crops of the region and with some adjustments can be grown for high yield and become profitable.

MB: What is the most challenging aspect of creating this application and program?

The farmers of developing countries are often not very educated and only understand local languages. We cannot expect that they will adopt a new technology very easily. So we are working hard on the UI part. Much of the interface will be visual, using pictures rather than words to avoid language barriers as there are so many regional languages. As we progress, the mobile app will be highly personalized, which will guide them with audio and visuals in their local language and hence adapting a new technology will be less difficult.

MB: Right now, the project is in the testing phase, what do you think the timeline is for more widespread adaptation? The world is changing pretty fast, and the timeline we have kept in mind is about 2 years. It is still hard to convince the farmers to use the technology and make this investment.

MB: What sort of hardware does Kisani utilize?

Kisani is built with the Intel® Edison Board, SparkFun Weather Shield, and various other environmental sensors. Data will be collected with the help of various environmental sensors and processed with the Intel® Edison Board which will be sent to a cloud using Intel® IoT Gateways.

The farmers themselves interact with the application through standard Android mobile devices.

MB: And the software? The programming part is done in Node.js, using many services from IBM Watson for effective evaluation of data and machine learning. For effective sensing and prediction, we are using the Urthecast API, which gives live feeds from space using the Satellite Imagery API for Weather Patterns which combine, weigh, and then decide on a solution. Reports are generated and sent to Farmer Help Centers. The data received by them is automatically analyzed with Watson Alchemy API and enhanced by our expert's advice.

MB: What are your other goals related to this project? How do you envision scaling this to have a larger impact on your community? The first would be to open education centers for the farmers, providing them learning opportunities on a larger scale. I want them to know that technology can change their lives–something that they will understand gradually. We don't expect them to adopt the technology immediately, but to implement it into their lives gradually. We want to start a community program, going from village to village to educate people on what this technology can do for them, and how it can make life better, easier. We want to change their lives for the better.

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