7 Reasons Why Machine Learning Is a Game Changer for Agriculture
Old days of hard and not always profitable human labor is over, Smart Farming powered by Machine Learning with its high-precision algorithms is a new concept emerging today. Aiming to increase the quantity and quality of products, this cutting-edge movement makes sustainable productivity growth for everyone working in the agriculture realm.
Farming goes digital and now we are observing 4th Agricultural Revolution. Everyday machines learn to solve complicated tasks, and they are doing it better with time. So, what is Machine learning applications in farming today and why should farmers care? This post will help you with this question.
Irrigation systems are not an easy task when working with large open areas, however, today many farms are already using it very successfully. The main problem of organizing the work of such systems is a dependency on weather conditions when forecasting the resources required for irrigation. Automated irrigation systems are used to continuously maintain the required soil conditions in order to increase the average yield. This not only significantly requires less human labor but also has the potential to reduce production costs. In addition, irrigation systems are crucial for optimizing and accounting for freshwater consumption statistics. Many scientists believe that these technologies will subsequently have a global impact on global water supply processes.
One of the most popular and widely available smart devices making great strides in the agro-arena. The function of providing new ways to increase crop yields through in-depth, ubiquitous analysis, regular and systematic spraying of the crop has become an integral part of working routine for many farmers. Unmanned aerial vehicles technology is actively developing and acquiring new applications that provide a wider range of options necessary for high-quality and productive work in the fields.
Leading tech companies have been working for a long time on the innovative approach that will minimize human intervention. Agriculture has become one of the key areas where such equipment has become extremely necessary and useful. Smart tractors equipped with software with “ready” intellectual technologies — sensors, radars, GPS systems — go around the fields, cultivating the land and harvesting, without needing a driver company. With such autonomous crop handling systems, it is possible to cultivate much more areas for longer periods of time.
Conventional methods of monitoring the health of agricultural crops are incredibly time-consuming. Many technology companies have been working for some time on the intelligent systems development that can monitor, detect and analyze the field of various data to study the status and feasibility of growing certain types of crops. It is anticipated that the work of such automated systems will be built on the processing of hyperspectral images and 3D laser scanning, which will significantly increase the accuracy and amount of data collected. It is noteworthy to comment that such technologies would help many farmers to produce accurate diagnostics of individual areas or even individual plants growing on the field, thus controlling their harvest and its potential.
Right now Machine Learning can help farmers to predict yield and crop quality, detect weed and disease:
Engineers from Microsoft along with ICRISAT scientists use artificial intelligence to determine the optimal planting time in India. An application using Microsoft Cortana Intelligence Suite also monitors the condition of the soil and selects the necessary fertilizers. Initially, only 175 farmers from 7 villages participated in the program. They started sowing only after a corresponding SMS notification. As a result, they harvested 30–40% more than usual.
