The Game-Changing Role of AI in Agriculture
Introduction
Around the world, agriculture employs more people than any other industry. It is the primary source of livelihood for about 40% of the global population. However, this sector has several challenges including climate change, population growth, and food security concerns. It is here that artificial intelligence (AI) is beginning to make an indelible impact. The fusion of AI and agriculture is bringing new efficiencies to a sector steeped in tradition, in turn, revolutionizing the way we grow, harvest, and sell crops.
AI and Smart Farming
Farms nowadays are starting to resemble outdoor factories, thanks to AI. With the help of ‘smart farming’, Hamilton spectrometers, dirt-cheap sensors, and flying robot overseers, farmers can optimize the use of resources, maximize crop yields, and minimize environmental impacts. GPS tracking and satellite imagery give a big-picture overview of fields, while machine learning algorithms can predict crop yields and detect potential diseases or pests. In this way, AI is helping to transform farming from an intuition-based practice to a science.
AI and Automated Farming Machines
AI also plays a prominent role in the creation of automated farming machines. With the help of advanced sensors, machines can now perform tasks like planting seeds, watering crops, and harvesting produce. Moreover, these machines can adapt to changing weather conditions and even learn from their past performances. This has the potential to drastically reduce the human labor requirement in agriculture, allowing farmers to focus on more analytical and creative aspects of farming.
AI-Driven Software Platforms
AI-driven software platforms have also started to play an important role in the agricultural industry. They offer alternative methods in area such as decision making and predictive analytics. AI can help farmers to analyze weather patterns, soil conditions, and plant health in real-time, leading to better decision making and increased crop productivity. Additionally, predictive analytics can alert farmers about upcoming weather changes, potential pest attacks, and suggest the optimal time for crop harvesting.
AI and Food Supply Chain
The use of AI extends beyond the farm too, it can be incorporated within the entire food supply chain. Machine learning algorithms can help distributors optimize their supply routes, reducing fuel consumption and overall costs. Additionally, AI can be used to forecast consumer demand more accurately, helping food retailers reduce waste and increase profits.
Conclusion
While the adoption of AI in agriculture is still in its early stage, the potential benefits it can bring to the table are clear. AI has the potential to drive efficiencies, reduce labor requirements, and boost crop yields. In this way, it can address some of the biggest challenges in the industry, including resource management and food security. As AI continues to evolve, we will undoubtedly see its impact on agriculture becoming even more significant.
References
Artificial Intelligence is Changing the Landscape of Agriculture. (2021, April 1). Retrieved from IBM Industries: https://www.ibm.com/blogs/industries/artificial-intelligence-is-changing-the-landscape-of-agriculture/
AI in Agriculture – Present Applications and Impact. (2020, January 10). Retrieved from Emerj: https://emerj.com/ai-sector-overviews/ai-in-agriculture-present-applications-and-impact/