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Agrobots - intelligent robots for automated farming

How AI is driving forward evolution of agricultural robots

High-tech tools are conquering the agricultural industry, enhancing the farmers’ production potential.

Automation in agriculture helps farmers improve their processes by providing real- time data on soil conditions, moisture levels and more, allowing for the optimization of irrigation, a more efficient harvest planning, prediction of food quality and accurate insights for products and services suppliers (fertilizing companies, sellers etc.).

Farmers can now use IoT sensors to obtain real-time data and monitor animals’ health conditions and activity.

Technological innovation in AI is doing more than providing analysis tools to rural businesses. It also penetrates day-to-day farm activities by bringing robotics into all agricultural processes. The potential of robotic automation is huge. Its scope covers a wide range of fieldwork such as seeding, harvesting, irrigating, and supervising to liberate workers from repetitive and heavy duties and improve all the procedures in terms of costs, time, and quality.

This phenomenon is to be attributed to the necessity of increasing food production. Considering the current world population volume of more than 7 billion people and an expectation of over 9 billion by 2050 (UN estimates), the pressure to keep up with the global demand calls for introducing more efficient practices to produce and supply goods.

Autonomous tractors, robotics arms and drones are some of the new automated farming tools employed in the fields to enhance agricultural processes for:

  • Primarily Surveillance (drones)
  • Crop Harvesting
  • Planting and seeding
  • Precision weed control
Automation in agriculture

AI and Computer Vision for weeding

One of the duties farmers would be happy to hand to agricultural robots is certainly weeding. For an agrobot to take over such a task, it must be equipped with technologies to distinguish and separate the weeds from the cultivated product.

Such tools include Computer Vision and Artificial Intelligence. These technologies rely on machine learning capabilities to increase their accuracy. The robot can take and optimize the image of the targeted area, classify the objects detected and, finally, operate the electrocution of the weeds through its end-effector.

Herbicide efficiency

Currently, more than 250 weeds are documented to have developed an herbicide resistance, due to the excessive use of these products. Such a phenomenon has already caused a $43 billion financial losses for US farmers (Weed Science Society of America estimation).

Robotic solutions are now used to address the mentioned issue, by targeting the weeds with a spraying machine that only releases the necessary amount of herbicide, significantly reducing the crops’ exposure to chemicals. We achieve a double benefit: first of all, the food supplied to the population will have lower amounts of chemicals, because farmers will no longer have to spray the entire fields with herbicides. As a consequence, farmers will save money on herbicides, being able to distribute the products with higher precision.

Crop Harvesting

Artificial Intelligence applied to agriculture also has the power to respond to the decreasing agricultural workforce. Robots, like strawberry picking machines, can harvest eight acres of land in 24 hours.

Planting and Seeding

Agricultural robots equipped with Computer Vison can generate 3D models of specific areas. These maps allow for various tasks, as planting seeds keeping an adequate distance among them—this process, called ‘thinning’, guarantees for optimal growth of products.

Smart Farming- some use cases

Optimization of pest control

Inefficient pest control can significantly impact crop yield. Manual inspection for pests is enormously time-consuming, especially for large-scale farmers, and never a scalable process.

IoT sensors can provide farmers with accurate, real-time information about the health of their crops that can be used to detect pest infestations. Low- and high-resolution image sensors can be used to gather insights into the general behavioral patterns of specific pests on a farm. For example, if climate sensors detect specific conditions in which certain pests thrive, the IoT system can help predict an infestation so farmers can prepare for it early.

These sensors and other smart-farming devices can be used to analyze the effectiveness of current pesticide use. Users can make optimizations to how, where, and when they apply certain strategies. IoT in agriculture eliminates many variables such as human subjective perception and human error.

Keeping track of animals

IoT also has provided farmers who need to constantly monitor the movement of their grazing animals with attractive, scalable solutions. It is now standard for animals to wear collars that contain a tracking sensor device rather than just bells. These trackers not only help farmers reduce the time it takes to find stray animals but they actually provide insight into animal behavior. Which places do cows prefer to graze?

An Austrian startup called SmaXtec has developed a tool that helps farmers remotely monitor the health or well-being of cows. Sensors are placed in cows’ stomachs to collect data that is transmitted via wifi. The system monitors the cow’s overall health and informs the farmer if the cow is pregnant (the margin of error here is only 5%).

While the benefits of this equipment are undoubtedly attractive to any farmer, it is still very expensive to set up. The cost is about $600 per cow. This device also only lasts four years before it needs to be replaced.

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Improved irrigation methods

Water is a precious resource that must be used as efficiently as possible. While watering plants in a garden may seem simple and straightforward, watering to a certain extent is a crucial agricultural process that can determine the success or failure of a crop. Too much or too little water can harm both plant and soil health (which in turn can hinder the cultivation of future crops).

Some IoT solution providers claim that their technology, which consists of sensors that measure soil moisture, can reduce water use by 30%. It provides farmers with data to take timely action against over-irrigation or drought. Avocado farmers in Southern California have placed sensors around their trees to measure water levels. These sensors are connected to irrigation systems (in this case, a sprinkler system) to water only those trees that are actually thirsty. The water supply is turned off at night to avoid times when watering would be wasteful. This approach significantly reduces the margin of error and saves farmers a lot of manual labor.

Preventing climate-related losses

As the world’s population continues to grow, scientists are asking how even more people can have access to food. Not only are there more mouths to feed, but population growth is also having a drastic impact on climate change. This could have devastating consequences by disrupting the usual growing season.

Smart farming management systems can be used to track and analyze weather data and cross-check this data with known vulnerabilities of current crops. Thus measures can be taken to mitigate the damage caused by hail storms, droughts, cold weather, etc.

Generally improved efficiency

In agriculture, you need to pay attention to your crops and market conditions to maintain a competitive edge. IoT sensors can be used to increase efficiency and thus dominate the market. One success story takes us to China, where a strawberry farm increased its production by over 100% while significantly reducing time to market. The system also reduced labor by about 50% per kilogram of fresh strawberries and cut the amount of water and fertilizer needed in half.

This trial of IoT solutions was conducted in five of the farmer’s winter greenhouses. China Mobile (a state-owned telecommunications company) provided the means to connect all the devices and analyze the data seamlessly was provided by China Mobile (a state-owned telecommunications company). The installed sensors collected data such as air conditions (CO2, temperature, humidity), light intensity, substrate conditions, and leaf moisture. The same technology could be implemented in many other scenarios without too much effort.

What are the goals of smart farming?

Smart farming and sustainable agriculture rely on the availability of data. Smart farming aims to drive sustainable and cost-effective agriculture through diverse endpoints that help farmers make informed farming decisions. For example, the use of sensors helps farmers make decisions about how, where, and when to use certain resources to improve environmental and economic yields.

In addition to genetic modification and crop selection, smart farming seems to be heading down the path of the green revolution through the use of innovative agricultural techniques and tools. For example, farmers can now use drones, trackers, and sensors to improve their farming practices. In general, this approach involves using connected technology to achieve specific production goals while supporting sustainable agriculture. Trends suggest that the continued implementation of smart farming in agriculture will help alleviate some of the food security issues occurring in various parts of the world today.

Sustainability in agriculture can be achieved through the proper use of data in decision-making. In fact, innovative agriculture is considered an offshoot of data analysis and mathematics. Every day, farmers deal with many factors ranging from varying soil composition to climate changes. Such variations require proper analysis so that proper farming practices can be implemented. Smart farming, which relies on big data in decision-making, can help deal with some of these issues appropriately and achieve set production goals. Many IoT service providers in this space offer farmers a user-friendly solution. The installation of sensors and other end devices is often carried out by specialists on-site. The data collected as a result is bundled on a platform so that farmers can interpret it.

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Agrobots are slowly reshaping the agricultural industry. Their impact on the sector is expected to grow year after year, when the necessity of more workforce in the fields will significantly increase.

The role of Computer Vision and AI-powered tools will become more prominent as models become more accurate. They will enable safe and efficient interaction between robots and plants with minimum or no supervision and earn farmers’ trust, even for the most delicate products.

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