Using Artificial Intelligence in Agriculture

Dowloaded : https://www.analyticsvidhya.com/blog/2020/11/artificial-intelligence-in-agriculture-using-modern-day-ai-to-solve-traditional-farming-problems/

Using Artificial Intelligence in Agriculture

Agriculture plays an essential role in the economic sector. Worldwide, people use old traditional farming methods, and they have to face various difficulties. Whenever weather strikes or whole cultivated land with crops affected by the disease, farmers commit suicide. The perpetual rise of the global population and growing urbanization process, at the same time, this pandemic hit, has made everything more difficult to carry out the farming process. With the increase in disposable income and changing consumption habits, farmers are under a lot of pressure to fulfill the increasing demand and simultaneously increase productivity.

Implementing artificial intelligence on a global scale would be the most promising opportunity. Artificial intelligence can potentially change agricultural scenarios, enabling farmers to achieve good results with less effort while bringing other benefits but may be challenging as well.

Why adopting agriculture intelligence is such a challenge to farmers.

Farmers understand agricultural intelligence as something only applicable to the digital world. They might not be able to believe that how AI can help them on physical land. And this kind of resistance is due to a lack of understanding of practical AI tools that are relatively conservative.

New technologies always seem confusing, incomprehensible, and expensive. Although AI can be helpful, there is still a lot of work that has to be done by technology providers to highlight the correct way of farming to farmers.

How can AI be useful in agriculture?

Agriculture is constituted of numerous processes and stages. By rounding off the adopted technologies, AI can provide the most complex and routine tasks. It can assemble and process heavy data on digital platforms, coming up with the best policy and initiating the required actions when combined with other technologies.

1. Analyzing farm data using AI 

Surrounding temperature, weather conditions, water usage or soil conditions, and various farming-related data of farms can be analyzed for a better decision regarding agriculture.

AI enables better decision-making. Predictive analytics is a real game-changer. Analyzing current market demand, determining the best time for irrigation, harvesting, and price predictions are critical challenges to farmers, are often solved with AI. 

Another benefit to agriculture is cost savings. AI can help farmers to produce more within fewer inputs. Precision agriculture powered by AI can become prominent in farming.

2. To improve harvest quality and accuracy

AI-based technologies are used to detect diseases in plants, pests. The algorithm or program is used to analyze the captured images by robots or drones and provide helpful information on the crop and heath of the farm. It helps to identify diseases in plants, pests, and bacteria. So that farmers can use pest control timely and other methods to take required action

3. Agricultural Robotics

AI robots can efficiently perform multiple tasks in farming fields. They are programmatically trained to control unwanted plants, e.g., weeds, and harvest crops faster with higher volumes than humans. Apart from it, the most important, AI addresses labor shortages.

Agriculture is a hard-working sector, and the labor shortage in this field is not a surprise. But this problem can be solved with the help of automation. Some examples being- auto-driver tractors, smart irrigation, spraying, fertilizing systems, and AI-based robots for harvesting.

Downloaded : https://www.wipro.com/holmes/towards-future-farming-how-artificial-intelligence-is-transforming-the-agriculture-industry/

Problems farms may face while adopting AI

1. Lengthy technological adoption process

This may be challenging for software companies to make farmers understand the whole AI system. Approaching farmers gradually to make them learn simple technology could be the first step in bridging the gap. Once farmers get used to it, they can then proceed to complex methods one step by step.

2. Lack of experience 

It is another challenge with emerging technologies. The agriculture sector in developing countries is far different from the developed ones. Some regions may benefit, but it may be difficult to sell such technology in other areas with differences.

3. Privacy and Security 

Threats like cyber-attacks and data drain may cause farmers severe problems.

Still, we think we can adopt a better AI-let agriculture environment by automating new AI and data science tools to tackle challenges.