If we say that today you can apply Artificial Intelligence to your agricultural business, perhaps you might imagine an army of robots working on your fields. In fact, AI is not necessarily related to robots or something extraordinary. There are many available innovations in AI and Data Science, which can be implemented quite fast and affordably, and these innovations can significantly improve the efficiency of agribusiness. So, today we would like to tell you about some of these innovations.
The use of OCR technology for real-time field inspection and timely response
The technology of image recognition today helps to quickly examine the real situation on the fields and respond to it promptly. The sooner you find out about the problem, the sooner it is going to be solved and you will avoid losses.
How does it work?
You just need to have images of your fields: they can be taken by a drone, or you can use satellite images of high quality.
These images can be recognized, analyzed and compared with many images previously collected in the database. The system can determine:
- areas of the fields, where there is no harvest for some reason
- plants with damaged and unhealthy leaves
- areas where plants are affected by pests
- the maturity of the fruits or vegetables in specific areas
When you know about the problems with harvests, you can react to this situation properly and fast, sending an agronomist for reseeding.
Similarly, an agronomist can go to particular areas where plants are affected by some diseases. Moreover, a mobile application with an integrated OCR function allows the agronomist to scan damaged leaves and immediately determine which disease has affected the plant. These self-trained systems contain hundreds of pictures from previous experience and are capable of perfectly diagnosing the diseases. This approach in agriculture is called scouting and is already used successfully a number of agrocorporations.
When you know the exact area injured by pests, it gives you a big advantage. You can use pesticides only where it is truly necessary. As a result, you can save your money and effort, at the same time you improve the quality of your products making it greener. This approach allows reducing the use of pesticides by up to 90%.
Another useful feature you can use is the detection of areas where plants have already reached maturity. Similar plants grow differently depending on different factors: relief, humidity, the amount of sunlight, and many others. The approach we propose allows you to harvest in time avoiding extra costs. The mobile application analyzes plant images comparing color spectrum and other characteristics of fruits, depending on each individual variety of plants, and determines the best time for harvesting, and the system automatically notifies the administrator about it.
Just imagine how much easier and your work can become!
Voice Recognition and mobile applications for agronomists
A very useful thing for your business is the mobile application for agronomists. Such applications allow you to take photos and videos of the fields and to immediately send them to the administration point, while this information is stored in the database. This data is extremely important because it will be used in the future to analyze the situation on the fields and to make predictions.
Natural language processing tools in mobile applications are used to quickly create a report from the field. You can forget about hand-written reports that take so much time and effort. Now reporting is simple and looks like a conversation with a chatbot. The mobile application itself will ask you the necessary questions and you will answer them orally. The application transforms the voice into a text, inputs the answers to the appropriate strings of the document’s form, and formulates the report, which is sent immediately to the head office. In addition to this, the agronomist may receive operational guidance from the management if there is a possibility to correct the situation on the field.
Analytics and forecasting with the use of machine learning and neural networks
Each agrocompany aims to achieve maximum productivity. For this purpose they analyze various parameters and their impact on the fields’ productivity. But not always do they succeed in it, because the number of factors and the amount of different data is enormous. For instance, if we are trying to predict the harvest it is not enough to only analyze weather conditions, the amount of fertilizers, the seeding period. Because harvest can be influenced by: the history of previous plantings, the history of companion plantings, weather conditions on the day of fertilization, the schedule of pest control measures, the history of plant diseases, and many more. Hardly ever can a person analyze this whole set of factors and make a prediction, because it is a complex mechanism that has worked with a lot of data for many previous years. The implementation of machine learning helps to build the right prediction model. Now you can understand more deeply the impact on your crops and your managerial decisions become much more efficient.
The situation in livestock farming is even more complicated, because there are a lot more factors: the history of vaccination, genetics and reproduction, increase or decrease in weight, history of the diet, data on periodic veterinary examination, conditions (temperature, humidity, content of different substances in the air, etc.). All these data should be stored in a common database, they are of great value to the agrocompany. The analysis of the impact of all these factors will optimize the work of the farm.
Recently we have worked on a project for a poultry company. The problem they had was that equal numbers of poultry stock could vary greatly in their total weight, depending on the weight of each individual bird. This would result in either an excess of meat, or in its shortage, and, consequently, it was very difficult to produce the exact amount of meat to meet the terms of the contracts with vendors. And this is what we have done. We offered to develop a system that periodically monitors the weight of the birds, depending on different parameters, especially the diet. The system works on the basis of data science and is self-trained. It allows controlling the total weight of birds by changing their diet, temperature or humidity on site, or other parameters. Now it is much easier to maintain the planned total weight of birds.
Digitizing old documents
If you have been working in agriculture for a long time, the information you have collected is extremely valuable for your company, because it involves quite long periods of time, so it will be possible to make really accurate predictions. However, most likely this information has been stored for years in the form of old paper documents in archives. Illegible texts, lost words – it would take hundreds of hours to transfer these data into an electronic version. In such cases, intelligent information systems with handwriting recognition functions can be used. We already have experience in such projects. The efficiency and accuracy of this approach is about 90%. Digitizing old documents is a reality today.
Monitoring of machinery
An important and valuable aspect of agrocorporations’ work is machinery. Smart information systems today are used to optimize processes of planning capital and current repairs, to prevent the premature wear of specific parts or equipment as a whole through accounting and notification systems.
These systems also use a GPS-tracking technology. Each mile is tracked and recorded in the database, and the number of miles covered during the reporting periods (day, month, year) is calculated. On the basis of this information it is possible to build schedules of equipment load and plan its safe use. It helps to control fuel consumption, to track the activity and movement of each unit of equipment remotely and to monitor the area under cultivation.
It is also useful to keep a history of breakdowns and repairs of each unit of machinery to detect and prevent the most likely breakdowns in the near future and to properly plan the work of machines on different types of field. Modern information systems take into account many factors and allow preventing dangerous situations and excessive wear of the machinery.
So, these are just a few cases showing how you can use artificial intelligence, Data Science and machine learning in the work of an agricultural corporation right now. In fact, there are so many other possibilities, it depends on the specificity, the problems and needs of each individual company. If you do not know exactly what your business needs, you can trust experts in business intelligence and they will help you understand how your data can be used to boost your business performance. [bvblogic] company is a software development company that specializes in smart innovative solutions for agriculture. Currently [bvblogic] is offering free business consulting for agricultural companies. This is a great opportunity for you to find new opportunities for the development of your business!