Agriculture & AI: 3 ways AI is redefining farming’s future
With long-held traditions and well-established practices, the agricultural industry may not strike you as a hotbed for technological activity. However, an increasing reliance on data-driven insights and a serious need for repetitive manual labor makes farming a perfect beneficiary of AI innovation. Indeed, these new technologies are having a significant impact on the sector as numerous tech companies are deploying AI to battle the industry’s greatest challenges.
Agricultural Data Analytics
Crucially, farms often have multiple ongoing operations that cover large areas. As a result, farmers are continually bombarded with a multitude of diverse data points – from air temperature to water usage and soil conditions. AI systems can help make sense of this data and offer actionable insights that optimize and simplify farm management.
For example, aWhere, a Colorado based tech company, offer users ultra-precise daily weather forecasts. Their AI models use this weather data to provide predictive insights. For instance, they can output recommendations for optimal harvest dates, or else alert farmers when weather conditions are conducive for certain diseases or pests. With this digestible information, farmers have everything they need to make well-informed decisions and ensure maximum yields.
With concern growing regarding the use of pesticides in food products, a solution that minimizes their usage while maintaining safe conditions is in high demand. Seemingly, AI technologies can offer just that, as they ensure that pesticides are only used when completely necessary.
This is accomplished through image processing – a task that AI does exceptionally well. Using thousands of labelled training images that depict either healthy or affected plants, companies can train an AI model to recognize pest-ridden crops with super-human accuracy. This computer vision technology can then identify contaminated plants within a crop and inform a spraying system to spray only affected areas rather than entire fields. As a result, farmers use pesticides only when totally necessary, thus saving resources and improving the quality of harvest.
Weed identification can benefit from similar methodologies. Using satellite images or aerial footage, engineers can train an AI system to differentiate between healthy crops and unwelcome growths. Again, this can inform on where to focus a de-weeding procedure so as to maximize the efficiency of farm operations.
Autonomous Agricultural Robots
In the video below, we show the start-up Iron Ox, who created a fully autonomous farm in San Carlos, California. The hydroponic, indoor farm relies on two robots to plant, care for and harvest all its produce.
One of the robots is 1,000 pounds and about the size of a car. It picks up the trays of plants and transports them around the greenhouse. A second machine, a robotic arm, is responsible for all the fine manipulation tasks, like seeding and transplanting. As a tray of plants matures, the mobile robot carries it to the processing area. Here, the robotic arm moves baby plants in densely packed trays to containers with more space. This optimizes space efficiency because, throughout their life cycle, plants are only given the room they need.
A rapidly shrinking labour force is encouraging greater automation within the farming industry. As we move further from an agrarian society, farmers are now looking to AI-powered farmer ‘bots’ to conduct mundane tasks once performed by humans.
AI-Powered autonomous farm
Another example, Harvest Croo, has developed an autonomous strawberry picker. It deploys a computer vision algorithm to identify ripe fruit and an intricate collection system to pick strawberries at the perfect time. Similarly, a robot apple-pickers can navigate through rows between trees while detecting ripe and ready apples. It then reaches for the apples and gently sucks targets from trees using a vacuum device.
Consequently, these robot harvesters are addressing labor shortages while saving humans from laborious, repetitive tasks.
Seemingly, as is the case in most industries, AI’s impact on the farming world is substantial. Indeed, with a rapidly increasing global population and a diminishing labor force, AI may prove vital in addressing the agricultural industry’s future challenges.