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3 AI use cases in Agri Tech

Introduction

Agriculture is a major segment powering the Asian economy. A small transformation in agricultural outcomes can have a huge impact on 2 dimensions – economic and human. Keeping this in mind CANOPY ONE  brings to you our pick of the top 3 use cases which would have a massive impact. So here they come

1. Determining Optimal Fertilizer Mixes

One of the fertilizer manufacturer and leading producer and distributor of specialty fertilizers in the world, with revenues of almost US$ 2.0 billion in more than 80 countries. XYZ produces seven main specialty fertilizers and more than 300 fertilizer blends, depending on the needs of its customers. Farmers want the company to quickly recommend optimal fertilizer blends that will provide the appropriate quantity of ingredients for their particular crop at the lowest possible cost.

A farmer will provide a company sales representative with information about previous crop yields and his or her target yields and the company representatives will visit the farm to obtain soil samples, which are analyzed in the company labs. A report is generated, which indicates the soil requirements for nutrients, including nitrogen, phosphorus, potassium, boron, magnesium, sulfur, and zinc. Given these soil requirements, company experts determine an optimal fertilizer blend, using a linear programming model that includes constraints for the nutrient quantities required by the soil (for a particular crop) and an objective function that minimizes production costs. Previously the company determined fertilizer blend recommendations by using a time-consuming manual procedure conducted by experts. The linear programming model enables the company to provide accurate, quick, low-cost (discounted) estimates to its customers, which has helped the company gain new customers and increase its market share

2. Pesticides spraying using Drowns

 One of the Drowns manufacturers, is a start-up designer, manufacturer and distributor of drowns for agricultural purpose in India. The said produces drowns which can carry 10lts, 20lts and 30 lts with a flying time of one hour. Batteries are designed in such a way that they can take care until liquid pesticide is sprayed to the last drop.

Farmers want the company to take care of the exact mapping of farm boundaries and cost-effective. A farmer will provide the company typical land boundaries of farmland in Indian context, challenges they are facing while using drowns e.g. 1) farm will give today in the middle of the form, 2) farm will have a semi-arid land in the middle of the farm, 3) Bunch of trees at the edges of farm for which spraying of a pesticide is strictly prohibited, etc. Also, farmers wanted optimum utilization of the pesticide quantity and cost-effective than the humans spray the pesticides. Ensure the pesticide sprayed using drowns is as effective as it is sprayed manually. The objective of this use case is to develop artificial intelligence/machine learning algorithms to take care of all farmers concerns are addressed.

3. Role of Robots in Agriculture

The biggest challenge of today’s agriculture is the human labor and areas which can’t be automated or least scope for automation. A few examples:

1) Ploughing a small sugarcane farm with plough,

2) Rice and wheat residue stacking post cutting,

3) Pesticide spraying in farms which are small in nature, farms having zigzag boundaries, semi-arid portion inside a farm, farms with trees having a crop and pesticide not allowed, etc. The aim of the current use case is to develop bunch of Artificial, machine and deep learning algorithms with highest smartness and can control a Robot for doing above tasks with accuracy of 95% or above.

The successful implementation of above task would take care 99% of small and medium farmer’s day-to-day activities in India. This would lead to our rulers’ slogans of doubling or tripling the income of farmers by 2020. As a result most of the young generations would choose farming as profession. Hence, country’s food production will go up. The FMCG sector’s export percentage will increase and import percentage will decrease. The GDP rate of the country will be in the growth path. The employment dependency on outsourcing will reduce and India as a country will become self-sufficient in generating employment for upcoming generations.