Artificial Intelligence (AI) is becoming more powerful and ubiquitous by the minute, and every industry is trying to find ways to make use of the new technology. Agriculture is no exception, and many startups and companies are already incorporating cutting-edge AI tools into an age-old industry.
Last year, the market was estimated to be worth $1.1 Billion, and Vantage Market Research stated that the Artificial Intelligence (AI) in Agriculture Market is expected to reach $4.2 Billion by 2028, growing at a CAGR of 25.1%.
There are three main areas where AI has already shown great promise. Starting with the use of intelligent sensors, network-connected sensors can measure soil moisture, position, airflow, and weather. Having more accurate readings can help farmers adjust environmental factors to improve yield and lower costs. Which brings us to the second area where AI can help, replacing labor. Unfortunately, young people are less inclined to enter careers in the agricultural field, and skilled elderly farmers are retiring. AI can be used to automate many processes, reducing the need for extra labor. Finally, the use of drones can help farmers be more accurate in their use of chemical spraying to only target areas that are ready and in need, significantly decreasing the amount of spray needed and the chemicals entering groundwater.
Many associate AI with large-scale farming, while this may be the case in a lot of applications, Ai can still be hugely beneficial to smallholder farming as the technology becomes more mainstream and more affordable. The cost savings and yield increases will more than cover the initial cost of the investment in these new technologies. While many of these tools are being created for the use of larger scale farms, many researchers and organizations are leveraging Big Data and machine learning to provide dynamic open-source information and tools that can be used by anyone, regardless of scale.
Engineers and developers in Africa are jumping on the bandwagon and creating tools that can help even the smallest farmers, designed specifically for the region's needs.
In Tanzania, Project Artemis, a new collaboration, is using advanced phenotyping technology to help breeders and smallholder farmers discover strains that are more resistant to water shortages and result in larger yields.
In Kenya, farmers are using UjuziKilimo, an AI platform that provides agricultural data to smallholder farmers.
While Software developers from Mbale, Uganda used Google's TensorFlow, an open-source machine learning platform, to create the "Farmers Companion App" which prevents the spread of Fall Armyworm from damaging crops.
