India is a country where Agriculture has been the primary occupation for ages. Even before the Indus valley civilisation, there is evidence of agricultural activities happening as early as 8000-6000 BCE. Most importantly, the traditional agricultural practices we have been following have always tried to maintain the balance between farming and nature, and as a result, the great Indian civilisation prospered with a rich culture of agriculture and allied industries, e.g. cloths, dairy, leather, etc.

Fast forward to today – and while doing that, we see so many ups and downs in agriculture during this period. There was an era of good and bad rulers, of exploiters and supporters, and what stands out starkly in the 19th century are the effects of the Industrial Revolution on Indian agriculture and the allied industries. Post-Independence, we have seen many colourful revolutions- green (industrialisation –use of hybrids) and white (dairy), yellow (oil seeds) and blue (fishery). And they have promoted certain crops/ cropping patterns/allied industries with a focus of increasing productivity.

Hence it is no wonder that with the fourth industrial revolution, as we see so many new technologies coming to the fore, these are going to impact agriculture of the world. With globalisation, the technological gap between the countries has reduced drastically, and the pace of change is alarmingly rapid.

We already have multiple companies – huge industrial houses as well as young start-ups, who have sensed this opportunity and are applying AI/ML, IoT, autonomous driving and a host of newly accessible, as well as affordable, technologies to the world of agriculture. 

Here are some of the use cases which we see in the AI space for agriculture:

• Weather prediction: Agriculture across the world is dependent on climate, and so the use of AI for predicting the weather is the most obvious use case. There are multiple such initiatives across countries to predict weather both at a government level as well as by enterprises link IBM and Google.
• Crop Monitoring using Image processing: Whether we use a satellite, a drone, or a robot to take images, there are cases where image processing is being used to assess the crop. This includes real-time crop vegetation index monitoring from satellite images, monitoring for pests, for yield size, yield prediction, soil assessment and a host of other use cases.
• Harvesting robots: There are various robots being built for harvesting yield. A list of such robots can be found here ( https://roboticsbiz.com/top-14-agricultural-robots-for-harvesting-and-nursery/ ) although not a complete list by any means.
• Driverless tractors: The unavailability of farm labour has led to multiple companies across the world, introducing self-driving tractors. Even Mahindra and Mahindra Ltd, India’s largest manufacturer of tractors, showcased its first driverless tractor in Sept 2019. Mahindra’s tractor can steer automatically using GPS-based technology, lift tools from the ground, recognise the boundaries of a farm, and can be operated remotely using a tablet.

The big question, though, from the perspective of India is – will the latest tools and techniques be applicable and useful for Indian farmers? Will they be affordable for them?

Indian agriculture realities

While we look with excitement towards the possibilities that human minds have achieved, we cannot help but look back at the realities of Indian agriculture. As we know, the reality is that even today, our farmers owe all the risk of their enterprise. They are completely dependent on others for the produce of their land – whether it is money for buying seeds, fertilisers, pesticides or the weather, they are bugged with water scarcity, lack of skilled labour and the list goes on. Even the income from their produce is not guaranteed, and since the produce is perishable, they have to accept whatever amount they get for lack of storage facilities.

Most importantly, in the context of applying technology, the majority of farmers in India have a very small landholding, and they are unable to sustain the cost of buying the seeds and other essentials. In such a situation, can we expect them to invest in such a technology which is expensive, not completely proven and may not be needed for a small land? 

What about sustainability?

This is another important aspect which is often ignored in the context of agriculture. It is a well-known fact that a large amount of pollution is happening across the world due to the use of fertilisers and pesticides. In the attempt of industrialising agriculture, increasing production, requirements for produce of a specific size, colour etc., a large amount of food goes waste, while on the other hand there are many who are not getting a daily square meal. There is an increasing rally behind the thought that it is not important to have a large amount of produce with little or no nutrition value. Rather, it is required to have a reasonable amount of produce with the least pollutants and more nutrition.

Much of the technology available in the market today do not consider this fact. Hence, despite a focus on providing technology to accurately target the fertilisers/pesticides, we are still far away from a step-change in outcome linked to sustainability.

Technology as an enabler

We have always debated whether science and technology is a boon or a bane, and as the time progresses and we look back, the more we realise that it is us who makes it a boon or bane. So it is very much possible to enable improved agriculture with the use of the right amount of technologies, targeted towards a sustainable future. Some of the examples for this could be – use of AI/ML to correctly predict the weather at a local level, guidance modules to farmers to use sustainable techniques to help manage pests through ecology, robots for harvesting in a multi-crop farm, AI for demand prediction based on available stocks, export, and local needs, etc.

Most importantly, technology can enable education and training to enable a large skilled workforce, which is lacking currently. And while doing this, the sustainability aspects can be considered as the core of the course. This skill enablement can lead to job creation for at least 10 lakh people, and while doing this, it can also bring down the people concentration in urban areas thereby making urban and rural areas more sustainable.

We also need technology to help the farmer look at agriculture as a business, and enable them to use it to increase their profit in a sustainable way. This will help farmers to have a profitable business and will encourage more people to consider farming as an attractive occupation.

Role of data

While we look at AI as a potential technology to provide us with life-changing solutions in the field of agriculture, it is well understood that AI depends solely on the quality of data that is available. In the Indian context, this is also a huge challenge to get the relevant data at a farmer’s level. Not only is easy data collection a challenge, but people are also not happy to share their data as privacy concerns are prevalent. Hence there needs to be a technological answer to data collection as well. We need to devise ways to collect data without encroaching on the privacy of the farmers, in an automated manner.

Our approach

Technology needs to solve real issues on the ground. It needs to be applicable, affordable accessible, achievable and sustainable. Although the world can be viewed as one global family, the issues remain largely local and need to be solved locally.

Hence our approach in the Makers Lab at Tech Mahindra, where AgriTech is one important area of research, is to create technology which can make a step-change in the lives of farmers. For example, we are building a solution to help farmers view their own accounts and manage their business better, to provide them with crop-related suggestions, to provide training in an interesting manner, help them avoid infiltration of wild and domestic animals in the farm and a lot more. We are also dipping into ancient Indian culture and farming practices to deduce if our rich Indian heritage has answers to some of the questions out there. E.g. the Panchang(Hindu calendar and almanac) provides a fairly accurate prediction as per some of the studies. As a result, we are trying to find if there are any considerations which we can utilise in our weather prediction solution.

We also intend to build solutions which are very affordable, locally viable, and easily accessible. While we build our own solutions, in our open innovation culture, we also propose to bring those partners and start-ups together whose products are in line with our philosophy to promote sustainable agriculture. For this, we work with Agriculture specialists, who have years of experience of working on the ground level with the farmers.

Conclusion

In conclusion, we believe that through a two-pronged approach of using the latest technologies and a sustainable direction, the world of AI/ML, IoT and more can truly bring a step-change in the lives of farmers and really transform agriculture leading us to a sustainable future.