AI in agriculture and computer vision raise animals, help to monitor and manage animal health and well being.
One such example is Connecterra, a Dutch company that develops the Intelligent Dairy Farmer's Assistant (Ida). Ida uses AI and computer vision to monitor the behavior and health of dairy cows in real time, providing farmers with insights that can significantly improve the welfare and productivity of their herds.
We talk about how computer vision technology is helping to analyze animal behavior — and even determine their emotional state.
The system uses a combination of sensors and cameras to collect data on each cow's movements, eating habits, and overall well-being. This data is then processed by AI algorithms to detect patterns and anomalies, such as early signs of disease or stress, that may not be immediately apparent to human observers. By identifying these issues early, farmers can take proactive measures, such as adjusting feed or isolating sick animals, reducing the risk of widespread disease and improving overall farm efficiency.
The company's technology is proven to reduce antibiotic use in the dairy industry through more targeted therapies.
CV and AI are not only used in manufacturing but in food production too. For example, Singapore-based Singrow is developing innovative agro-technology solutions to select high-quality fruits and vegetables and revolutionize urban farming.
The company collaborated with Universal Robots and Augmentus to develop a robot with artificial intelligence for use in its harvesting and pollination systems. The robot was programmed to identify strawberry flowers and fruit; it promotes more efficient pollination when it identifies the flower and picks the fruit once it is ripe.
With this technology, Singrow's indoor farms are 40% more energy efficient and produce 20% more yield than conventional strawberry farms. Such technological solutions are particularly welcome in Singapore, where large open spaces are in short supply.
Of course, computer vision technology is not only used to speed up production, but also to keep people safe. We tell you more about it in our other article.
Water management, especially in drought-prone regions, is one of the most critical aspects of agriculture. AI and computer vision have enabled the development of smart irrigation systems that optimize water consumption, ensuring that crops receive the right amount of water at the right time. One such leader is California-based CropX.
CropX has developed a cloud-based platform that integrates data from soil sensors, weather forecasts, and satellite imagery to provide farmers with precise irrigation recommendations. Artificial intelligence in agriculture can analyze this data in real-time, adjusting irrigation schedules and volumes to meet the specific needs of each crop. This not only saves water, but also increases crop yields by preventing under- or over-watering. This shows an important advantage of artificial intelligence in agriculture.
The platform's computer vision capabilities allow it to monitor plant growth and soil moisture levels, providing farmers with detailed insights into the health of their crops. CropX's technology is particularly beneficial in regions such as California's Central Valley, where water resources are scarce and efficient use is essential for sustainable agricultural practices.The pure advantages of robotics in agriculture!
AI and computer vision technologies have revolutionized the process of crop monitoring. One example is French company Naïo Technologies, which has developed a range of agriculture robotics that use AI to monitor and maintain crops.
Naïo's agriculture robot are equipped with cameras and sensors that scan fields, capturing detailed images and data about the crops. The AI then analyzes this data to identify problems such as pest infestations, nutrient deficiencies, or irregular growth patterns. These ai farming robots can also perform tasks such as weeding, significantly reducing the need for chemical herbicides.
The company's offerings include the use of robotics in agriculture
By automating crop monitoring and maintenance, Naïo Technologies helps farmers save time and labor while ensuring their crops remain healthy and productive. This technology is particularly useful in organic farming. That's why the agricultural robotics market is growing steadily.
American company Granular also offers a farm management software platform that integrates artificial intelligence for agriculture to predict crop yields.
Granular platform collects data from various sources, including weather patterns, soil conditions, and historical yield data. The AI algorithms then analyze this information to forecast yields for different crops under various scenarios.
This allows farmers to make more informed decisions about planting, resource allocation, and marketing strategies. In addition to yield prediction, the platform also provides farmers with actionable insights to optimize their operations, such as recommending the best times for planting or harvesting.
The sorting and grading of harvested crops has traditionally been a labor-intensive process that relies on human judgment. However, advances in AI and computer vision are revolutionizing this task by enabling more efficient, accurate, and scalable solutions. A leading player in this field is Tomra, a company that has developed an automated sorting system powered by AI and computer vision.
Tomra's machines use high-resolution cameras and sensors to analyze each piece of produce as it moves along the conveyor. The system captures detailed images of the crop and assesses factors such as size, color, shape and even internal defects. Using AI algorithms, the system can quickly and accurately determine whether to accept or reject individual items based on quality standards. This level of precision ensures that only the highest quality products reach the market, while reducing waste by redirecting inferior items to other uses, such as animal feed or biofuels.
Drones have become an increasingly common tool in agriculture, and AI is enhancing their capabilities. American company DroneDeploy offers a drone mapping and analytics platform that integrates AI to provide detailed insights into crop health and farm management.
DroneDeploy's platform allows farmers to create detailed maps of their fields using imagery captured by drones. AI then analyzes these maps to identify issues such as nutrient deficiencies, pest infestations, or irrigation problems.
The platform also allows farmers to monitor crop growth over time, compare different management practices, and optimize their operations for maximum efficiency. DroneDeploy's technology is used by farmers around the world to improve crop management, increase yields and reduce costs.
Greenhouses provide a controlled environment for growing crops, but managing these environments can be complex and labor-intensive. AI and computer vision technologies are simplifying greenhouse management by automating many of the processes involved. Dutch company Priva provides integrated systems that use AI to optimize greenhouse conditions.
Priva's systems monitor and control various factors such as temperature, humidity, CO2 levels, and light intensity. AI algorithms analyze data from sensors placed throughout the greenhouse and make real-time adjustments to maintain optimal growing conditions. Computer vision is used to monitor plant growth, detect disease, and ensure that plants receive the right amount of light and nutrients.
By automating greenhouse management, Priva's technology reduces labor costs and increases crop yields, making greenhouse agriculture more efficient and sustainable.
Weed management is one of the most labor-intensive and chemical-heavy tasks in agriculture, but AI is transforming this process with innovative precision technologies. One standout company in this area is Carbon Robotics, based in the U.S., which has developed an AI-powered robot that identifies and destroys weeds using high-power lasers, eliminating the need for herbicides.
Equipped with 12 cameras and sophisticated computer vision software, the robot scans fields to distinguish between crops and weeds. Once weeds are detected, the robot uses carbon dioxide lasers to precisely zap them, killing the unwanted plants without disturbing surrounding crops or soil. This targeted approach helps farmers reduce chemical use by up to 95%, improving both environmental sustainability and operational efficiency. In just one hour, the robot can destroy up to 100,000 weeds, covering large fields with minimal human intervention.