Europe Union

Advanced Technologies for Agriculture and Farming

Advanced technology for sustainable farming, distribution and food processing.

Managing natural resources and food production for sustainable agriculture research and operations is crucial when facing the challenges of the modern world. We can help elevate agriculture, environment and food processing business operations with broad spectrum of artificial intelligence solutions.

A man using technology to inspect crops in the field

Sustainable agricultural technology – precision agriculture with AI and IoT

Precision agriculture is a cornerstone of contemporary farming technology. It uses advanced technology to optimise and manage farming operations. Technologies like geolocation, the Internet of Things (IoT), and machines like drones aid producers in managing resources or monitoring plant health and crop yields. It’s an essential matter for sustainable agriculture practitioners.

Agricultural technology and sustainable agriculture research are focal points of many organisations, like the European Union. Emerging tech components can hugely contribute to the development of sustainable agriculture practices.

Artificial Intelligence in Agriculture, Computer Vision Tractor Tracking

Computer vision for agriculture and farming

Computer vision is making a large part of new technologies in the agriculture sector. It can transform traditional farming methods into smart agriculture. Here are some of the most important uses of computer vision in sustainable agriculture:

Autonomous machines and robots: automated machines can contribute to different aspects of agricultural technology. For example, automated harvesting robots equipped with CV technology can identify when the crops are ready for harvest. They can also differentiate between crops and other objects, ensuring efficient and accurate harvesting.

Crop monitoring and analysis: computer vision methods enable real-time monitoring of crops to identify issues like diseases, pests, and nutrient deficiencies at an early stage. Farmers can also analyse video data of crops to get insights into crop health or soil fertility and take timely corrective measures. CV can also contribute to predicting crop yields, helping farmers to plan better and optimise their operations.

Weed detection and control: Accurate weed detection ensures plant health and good quality. Adopting computer vision can contribute to precision weed control by identifying and distinguishing between crops and weeds, facilitating targeted herbicide application or mechanical weeding.

Plant phenotyping: computer vision can aid scientific knowledge in understanding characteristics for breeding and research. It can be applied for capturing and analysing images to measure traits like height, leaf area, and colour.

Livestock monitoring: CV solutions can be ideal for keeping an eye on the health and well-being of animals on farms. It aids in identifying issues like lameness or illness early on for swift intervention for good animal production practices.

Smart irrigation: devices and tools equipped with computer vision technology can monitor soil moisture levels and crop conditions, adjusting irrigation schedules to optimise water usage for added sustainability.

Artificial Intelligence Solution for Agriculture - Fruit Strawberry Maturation Analysis through Computer Vision Solution

Artificial intelligence (AI) and machine learning (ML) in farming and agriculture

A significant advance in agricultural technology can be attributed to artificial intelligence and machine learning. Modern AI- and ML-based farm equipment and tools enable data gathering and assist in informed decision-making and sustainable agriculture practices. Drones, remote sensors and satellites can gather data constantly, offering insights into a variety of factors that include:

Weather forecasting: analysing weather data to help make decisions regarding planting, harvesting, and managing crops.

Yield prediction: predicting yields based on weather conditions, soil quality, and crop health, aiding in planning and marketing.

Disease and pest prediction: assessing the likelihood of diseases and pest infestations by analysing historical data and environmental conditions to allow for prevention.

Remote sensing for crop monitoring and management: using drones and satellites equipped with sensors, AI analyses images to monitor crop health, growth, and hydration levels.

Internet of Things (IoT) for better farming

The power of IoT can be utilised to improve the efficiency, sustainability, and traceability of the agricultural sector. Hence, the efforts for large-scale adoption are heightened and essential. A reliable IoT infrastructure can create a collaborative ecosystem of end-users, service providers, suppliers, and research bodies to enhance innovation and technology uptake.

Internet of Things in AgriTech

Sustainable Agriculture

With recent climate changes, sustainable agriculture has gained a lot of significance. Ecological practices to improve environmental quality and help mitigate climate change are also at the forefront of technology debate. So, how can emerging tech solutions contribute to propagating sustainable agriculture practices?

Blockchain in AgriTech

Blockchain technology can create transparent and unchangeable ledgers for agricultural products from farm to table, ensuring fair compensation for farmers and informing consumers about the sustainability of products. It can also help create a reliable authentication solution, for example, by adding immutable signatures to data gathered by space imaging technologies.

Blockchain concept, visualisation of data flow

Data Analytics and Cloud Computing in Agriculture

Based on historical and real-time data, big data analytics can optimise various aspects of farming operations, from seeding to harvesting. Advanced analytics tools can process this data to extract meaningful insights. For instance, analysing weather data alongside crop yield data can help determine the optimal time for planting and harvesting.

Businesswomen is using a laptop to access the cloud computing system

Technology for Streamlining Food Production and Control Processes

Food technology, or FoodTech for short, is the branch of modern tech that deals with food science and processing. Automation of quality assurance food processors and other tech solutions can highly contribute to the future of the food industry.

Improved quality assurance

Technologies like automation and computer vision can significantly contribute to maintaining the satisfactory quality of food products. By precisely monitoring the food, we can use autonomous machines and robots to monitor the quality of the food and alert in case of anomalies or faults. Collected data can give valuable insights into the frequency and type of food prone to worse quality and can also help determine the cause.

Mechanical sorting

Machines and robots equipped with computer vision technology can help determine food quality and mechanically sort them based on the quality. Engineers can use AI and ML-based training methods to help the device recognise faulty food and separate it from good-quality food. However, CV technologies can aid in sorting food not only based on the quality, with the use of detection algorithms, it can also help sort the food based on the type, to make the operations more efficient.

More sustainable food operations

Emerging technologies can also contribute to more sustainable food management and processing. Innovations in waste management, including waste tracking and food upcycling technologies, reduce food waste and promote circular economy principles in food operations.

AgriTech and FoodTech solutions, computer vision, automation in agriculture

The future of AgriTech and FoodTech

We believe sustainable agriculture and food systems will remain among the most important technology topics. Here’s what you should look out for in the coming years:

Computer vision enhancements: CV is an essential part of deep tech, offering a range of applications that can contribute to the quality of products and operations. It can ensure proper monitoring of crops or food and provide insights into health and quality.

Automation and robotics: The advancement in robotics will see more autonomous machines taking over labour-intensive or hazardous tasks, improving efficiency, reducing labour costs, and minimising human errors.

Real-time monitoring with IoT: reliable and efficient IoT infrastructures will enable real-time monitoring and control of agricultural and food processing operations, ensuring optimal conditions for food safety, quality, and resource efficiency.

Remote sensing and satellite imaging: remote sensing will provide more accurate and timely data on crop health, soil conditions, and environmental factors to boost decision-making and resource allocation.

AI Computer Vision Cattle Recognition Solution

Build your AgriTech and FoodTech solutions with us

If you’re an environmental-conscious person working in these sectors and want to elevate your business operations with innovative technologies, reach out. Our experts will help you achieve results that exceed your expectations. With their vast expertise and industry knowledge, they can tailor the solution to meet your needs. Don’t hesitate to contact us, and let’s build the future together.

Estimate your project.

Just leave your email address and we’ll be in touch soon
ornament ornament

Check out our Case Studies