The agricultural sector carries out a crucial role in the country’s economic sector. With a gradual rise in population, the demand for food is burgeoning. The prevalent methods used by the farmers in the past are not enough to match the rising demand and because of this, the need for innovative automated methods and technologies arises.
According to a published report, the global population is likely to surpass the nine million mark by 2050, which requires an increase in agricultural production by 70 percent to accommodate the demand.
In the past, there were several climatic issues that humans faced. Frequent droughts, warmer day-and-night-time temperatures, reduced snowpacks, and an increase in evaporation have proliferated. These factors have typically resulted in water shortages, increased depth to groundwater, which is directly affecting the health of the crops. To address these problems, employing AI-based machine systems is the best solution for the sector.
Many other sectors are efficiently implementing advanced Artificial Intelligence (AI) technologies to enhance productivity, performance, and results. The agricultural sector is also steadily coming into the picture and is adapting to the modern digital world. We can properly apply AI across various verticals, and it can also deliver a significant change in how we typically see farming today.
Slowly and steadily, AI-based machine systems are undoubtedly growing in this sector. Right from monitoring the crops, soil to plowing, weeding, irrigation, etc are being taken care of by this technology i.e by drones, robots, etc. AI-powered solutions will not merely enable farmers to serve more with less, but it will also help farmers to gain more yields and increase their production value.
It is anticipated that by 2025, the AI in the agricultural market is likely to hit 186 billion dollars.
Following are some potential benefits & uses of implementing AI-enabled models in farming.
1. It will help in yielding much yield healthier crops as compared to the traditional method.
2. It will help in combating pests and other crop infections.
3. AI-enabled models will help in monitor soil and can also help in compiling the data for farmers
4. It will help in cost reduction and minimize the efforts and time.
5. The AI-enabled models will help to forecast the weather. Apart from this, it will help in carefully monitoring the soil and crops’ health.
6. It will maximize the overall output.
These represent only a few benefits and one can reap maximum benefits when the authorities successfully implement quality AI-enabled models. We can only achieve the desired results by providing quality training to the data, which is properly communicated into the machine learning algorithms. In the agricultural and farming sector, Cogito is professionally known for providing high-quality training datasets.
Challenges in the adoption of Artificial Intelligence
AI-based systems are already in place in many agricultural activities, such as precision agriculture and automated crop harvesting.
This technology possesses immense possibilities in the agricultural sector but few challenges are being faced while incorporating this innovative technology in the sector. Farming is traditionally done according to the particular seasons, and sometimes it is extremely challenging to accurately predict the weather. Apart from this, several external factors also hampering the quality and production of crops. In order to identify the nuances of the agricultural sector, the AI model requires an enormous amount of quality training data that can be fed into the machine learning algorithms so that the AI model can make correct and accurate decisions.
As we all know that construction of a robust AI model takes time because the database takes time to mature and several crop-specific data can only be fetched only once a year. It will be a challenge to collect a suitable amount of training data and construct the AI-enabled model on time.