The world is in a potential hunger crisis and food shortage. In fact, according to statistics, farmers and food growers will need to increase productivity by 60 percent to feed the world’s population by 2050. To ensure that this goal can be achieved, technologies such as AI, machine learning (ML), Internet of Things (IoT), and predictive analytics need to be used in agriculture to increase efficiency, reduce cost, and increase farm productivity. As shown by the US department of agriculture’s economic research service, technologies like ML and AI bring lots of benefits when it comes to food production and distribution. In the US alone, the food production, processing, and distribution industry have an economic value of $1.7 trillion.
AI Application in Agriculture Sector
AI is proof of the profoundness of human intelligence. Humans are now able to build machines that mimic human intelligence and perform tasks of varying complexities. The goal of AI is to build machines that are capable of self-learning, reasoning, and perception.
AI has been a major contributor to increasing crop health, yield, and overall food production. Now, farmers are able to understand the precise needs of their farms. These technologies are able to automate repetitive tasks reducing costs and increasing profits.
5 ways AI is improving Agriculture
Analyzing Farm Data For Better Results
Nowadays, technology has made it possible to collect huge amounts of data from farms. This data can then be processed and analyzed to give farmers the ability to make better decisions on the future of their farms. The data is collected by sensors placed on the farm and analyzed using ML and predictive analytics. It has given growers the power to predict weather and climate patterns. So, they know when to sow their crops and when to harvest.
Farm yield predictions and price forecasts
Small farm owners are always worried about the price fluctuations controlled by large corporations. Due to this uncertainty, they are not able to predict their profits and plan for further agricultural projects. This problem is prominent for farmers who grow crops with a limited shelf life. However, access to climate and satellite data is giving these growers the ability to constantly monitor their crops’ health. Advanced technologies including deep learning, ML, and predictive analytics help to estimate crop yield and forecast prices. They provide all the players in the agriculture sector with future price pattern changes, demand for products, and choosing the right type of crop to plant, which will increase profits and minimize cost.
AI Forecasts Weather Data
Farmers can now use a computer model to predict harsh weather conditions. The AI does this by detecting cloud behavior using satellite images. This ensures that growers are informed and make the right decisions on which crops to plant and how to protect them. So, farms will not have to lose a huge portion of their crops due to bad weather, thereby increasing farm yields and profits.
Irrigation is good for plants but not always. In excess, the water can destroy the soil, making it not conducive for crops to grow. That is why it is important to irrigate only when necessary. With the help of satellite data, AI, deep learning, and machine learning algorithms, farmers can now spot the precise areas on their farms that need irrigation. Combining satellite imagery and data collected from farm sensors will provide a 3D picture of what is going on on the farm and how to fix it.
Drip irrigation with AI helps farmers to automate the process of watering their crops. It determines the appropriate time to irrigate, how much water to apply, and for how long. This will ensure that the crops are getting the optimal amount of water needed for growth. The process not only helps the plants thrive but also saves the cost of production.
Farmers can use sensors and AI to monitor their livestock’s daily activities. With this information, they can understand cattle’s behavioral patterns and determine if they are sick or in heat.
Livestock monitoring makes managing a large number of animals easy. Farmers will not lose livestock easily. For example, if an animal strays away from the grazing zone or barn, the sensors will notify the farmer and send the exact location of the cattle.
The use and importance of technologies such as AI, ML, and satellites have proven to be invaluable in agriculture. Conventional methods of farming come with lots of challenges that technologies can fix and make the farming process more efficient. With the use of these technologies, growers can increase productivity, decrease costs, and ensure that their farms remain productive for generations to come.