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How Is Agriculture Changing In The Age of AI and ML?

Without agriculture, there would have been no start to humanity as we know it now. Agriculture is a basic, yet most important, profession in human lives. Today, the agriculture industry accounts for up to $5 trillion worldwide. As there were more inventions around us, agriculture has transformed from requiring just human labor to using time-efficient machinery. Increased human population demanded efficiency in land usage too; the inventions in the field of farming were more productivity-oriented, both in the terms of healthier products and reduced efforts. Now, moving a step further, AI and ML introduce a whole new landscape in organizing farm-related tasks such as soil monitoring, climate tracking, and plantations. Here are some ways in which AI and ML are transforming agriculture for better results.

Weather Forecasts

AI has been helping in near-to-accurate weather forecasting for a long time now. This reliable weather data is beneficial for farmers to plan their cultivation, irrigation, and fertilizing processes accordingly. Weather forecasts are especially helpful when the crops are seasonal; harvests tend to be perfect and there is a minimal chance of error which leads to huge losses. The technology should be adopted on an even larger scale by small farm owners in developing countries as well, they produce a huge share in the total agricultural output.

Precision Farming
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As one of the greatest innovations in farming, PF has changed the way farmers deal with sustainable agricultural techniques. Traditionally, many farmers used the same techniques for all the crops regardless of seasonal changes or differences within the cultivation. Precision farming deals with the problem of unwanted wastage of resources. Apart from predictions about crops, it also analyzes the soil quality based on past databases. PF also detects and predicts crop diseases and the level of nutrition in the plants. This prevents any over or under-fertilizing that is fatal to the crops. Moreover, precision farming uses AI sensors that can detect and target weeds in a farm, and avoid using toxic chemicals all over the farm field. The sensors solve the problem of appropriate irrigation as well. While drawing a bigger picture of precision agriculture, helps in lessening the negative impact on our environment.

AI-Enabled Drones And Bots

The computer vision cameras on drones analyze the whole farm, provide insights, and suggest probable improvements. The foremost benefit of the drones is that it saves a lot of time; you would need days to do the same manually. Thus, you can frequently monitor the field and yield better results than ever. Farmers can manage the quality of both crops and soil, and optimize the use of resources. Soil health is important, not only for the ongoing production but also for ensuring the quality of all the future cultivations. Farmers can use chatbots in this field as well, where they can receive immediate help for any emergencies they are facing regarding their farms.

Today, farmers have lesser reliability on human labor, mostly because people prefer urban lifestyle over agriculture. As a result, the workload on a single farmer is a lot more than one can handle. To deal with this issue, AI technology introduces agriculture bots. These bots minimize human efforts by taking up the repetitive tedious work in farming. Farmers can, hence, focus on overall farm management and save on labor costs with this one-time investment. Machine learning anomaly detection enables these bots to accurately identify and eliminate risks such as pests, weeds, etc. Furthermore, bots can work for longer hours than humans, which means that farmers can look after their crops in a better way. Some may say that this is a clear-cut example of machines taking over human jobs. But we can use the same human potential in something that requires more creativity and thinking.

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1 Comment
  1. […] productivity and reduce efforts with the aid of technology to meet food requirements. Based on insights, let’s take a look at how AI and ML can open up new vistas for climate tracking, soil-monitoring, […]

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