Agriculture and farming are some of the oldest professions in the world. The evolution of humankind along with technology has changed the way we grow crops and farm. As cities expand and the global population moves on an upward trajectory, agricultural land is becoming increasingly scarce. This is why new, innovative, and state-of-the-art farming techniques and technologies are coming to the fore.
Today, a lot of farmers are focusing on growing more and getting a better yield on lesser areas of land. The $5 trillion industry is gradually leaning towards artificial intelligence (AI) to address numerous challenges in agriculture. AI is tipped to play an important role in controlling pests, organizing information for farmers, keeping a track of soil health, and more.
Artificial intelligence in farming and agriculture is currently in the infant stage. However, support from the government coupled with advances in AI is simplifying multiple agriculture-related tasks. AI has emerged as one of the key components of the agriculture sector, and the trend is likely to continue in the future.
As governments from around the world are looking to tackle world hunger, efforts are in place to boost food production. AI-driven tools will allow farmers to enhance food production, improve the quality of their produce, and also ensure their products reach the market as fast as possible.
Analyze and monitor farm data with AI
Each day, farms have hundreds and thousands of data points on the ground. AI allows farmers to monitor and analyze a host of aspects such as water usage, soil quality, weather conditions, temperature, and more. In addition, farmers can make data-driven decisions.
AI-tech allows farmers to improve their strategy and generate lucrative yields by planting the most relevant crops. They can also determine whether they want to use hybrid seeds and how they should utilize resources.
Over the past few years, AI-powered solutions have helped farmers improve harvest quality and accuracy – also known as precision farming. Precision farming uses AI tech to identify diseases in pests, plants, and more. AI is playing a critical role in ensuring that the over-application of herbicides and excessive toxins is prevented.
In several regions of the world, farmers are turning to AI to develop seasonal forecasting models to enhance agricultural productivity and accuracy. Such models provide a clear understanding of weather patterns to the farmers who can make decisions based on this information.
A few farmers are also relying on aerial devices such as drones to monitor farms. Deep learning algorithms and computer vision process information captured by these drones flying. Since unmanned aerial devices have the ability to cover and study a larger area of land in very little time in comparison to humans.
AI to address labor challenges
Today, the number of people who are picking up agriculture as a full-time profession has reduced by a considerable amount. This has created a workforce scarcity in many farms around the world.
Typically, a farm requires different workers to ensure the farms are productive and the harvest is successful. Currently, we are seeing a paradigm shift in the way people live. We are moving from an agrarian society to people who are living in urban regions, leading to a notable shortage of labor in agriculture.
AI-powered agriculture bots are emerging as an ideal solution to address this labor gap. These bots can be used to perform different tasks in farms. Besides, they can also harvest crops at a much higher volume at a faster pace in comparison to human laborers.
Many farmers are also leaning toward chatbots for assistance. Besides, chatbots can help you find answers to an array of questions and also offer recommendations on farm-related problems. At present, chatbots are successfully being deployed in different industries.
Farms are running more efficiently with less labor due to cognitive and AI-powered technologies. The demand for food is never going to slow down as it is one of the fundamental needs of humankind. The arrival of AI is a blessing for farmers and stakeholders in the value chain as it can be deployed across farms of all sizes.
A lot of tech companies are focusing on the development of robots that can perform different types of tasks on the field. Robots can now control weeds and also harvest crops at a faster rate in comparison to humans.
These robots can also determine the quality of crops and provide a clear picture of the picking and packing of crops.
Challenges to AI adoption in the agriculture
Although AI offers tons of benefits, there are a few challenges that we need to overcome. One of the biggest challenges in the widespread adoption of AI in agriculture is the dearth of simple solutions that can seamlessly integrate and embed AI in agriculture.
A majority of farmers do not have the necessary digital skills and time to learn about AI solutions. Besides, the use of AI jargon needs to be reduced and replaced with common terms that are accepted globally. AI solutions will have to be fused into legacy and existing systems and infrastructure that are already in use through APIs.
Regardless of the challenges, AI will continue to witness considerable adoption in agriculture. In addition, as AI technology continues to mature, the scope of applications will also expand. There needs to be an ecosystem wherein science, government, and businesses can work together to uplift the state of agriculture with technology in the future.
The adoption of AI in agriculture is growing at a rapid pace, and this trend is expected to continue in the years to come. It is allowing farmers to automate different aspects of farming and also turn to precision farming.
With the threats of global warming and environmental degradation looming upon us, farmers are turning to precision farming for higher crop yield.
At present, companies involved in the tech space that are rolling out AI-driven applications for agriculture are likely to shape the agricultural sector in the future. The onus is also on governments and independent private firms to fuel the adoption of AI in agriculture.
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