Agriculture seems to me to be one of the most exciting industries to be transformed by AI.
It makes sense when you think about it, but much of agriculture involves geospatial analysis, which requires detailed data to be used to fine-tune systems. But it also applies to many other industries. Perhaps one of the reasons AI is so great for agriculture is that it allows us to see the consequences in the food chain. In other words, the fruits of this type of innovation are manifesting themselves in very tangible ways.
Let’s take a look at some of the latest AI tools being applied to agriculture these days. One is to use things like aerial and thermal data to drive agricultural solutions and increase efficiency.
CultivateAI is a venture that is doing a lot of things with this kind of data. Key data sources include high-resolution drone and satellite imagery, and the results are often very impressive. In this case, farmers use the company’s software and services to look at things like land use and cover crops, as well as facility and asset monitoring. By looking at metrics such as yield performance, farms improve resource use.
Part of CultivateAI’s work involves integrating datasets into a cloud-based platform that actually works for farmers. Whether it’s machine sensor data or dedicated systems for historical analysis and reporting, everything runs on a kind of her ERP software hub that connects to other parts of the data architecture.
Consider connecting this type of software to systems such as computer vision harvesters. We now know that this detailed work, usually done by immigrants or contractors, is done expertly by machines that can use highly sophisticated image processing to select and prune. Convolutional neural networks.
But when you connect these systems back to these systems, you have something centralized that can do even more with automation.
Then we have Agricolabo, for example. This AI solution provides matching between companies and workers. Here we think about human capital and how to manage it. For more information, here’s how the team introduces new projects.
“We are a company born at the Massachusetts Institute of Technology that connects AI, sustainability, and agriculture. We are tackling the workforce crisis in agriculture, where 33% of crops rot in the field due to harvest issues. Our solution? AI-powered social networks, supported by avatars that break language barriers, seamlessly connect farmers with the necessary workforce and ensure clear communication.” (Watch Eric from Agricolab’s video explaining this in detail.)
As with many other types of AI tools, much of the value is in the interface. You can see labeled parties and how they are treated within the app. A “path to market” is presented that aims to optimize a minimum viable product. You can imagine how this will help farmers who are used to working with spreadsheets.
It’s all part of running a modern farm with cutting-edge solutions. Again, we see the connection between AI software and optimal use of cover crops, growing larger and juicier crops, harvesting more efficiently with fewer hands, and more. This is exciting for anyone interested in food production, and it’s one of the frontiers of AI and machine learning that we’re watching closely.
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