Agriculture

With the urgency to prevent environmental degradation, reduce waste and increase profitability, farmers around the globe are increasingly opting for more efficient crop management solutions that are supported by optimization and controlling technologies derived from the <a href="https://www.wevolver.com/article/the-engineer-s-guide-to-industrial-iot-and-industry-4-0" target="_blank">Industrial Internet of Things</a> (IIoT).Intelligent information and communication technologies (IICT) (machine learning (ML), AI, IoT, cloud-based analytics, actuators, and sensors) are being implemented to achieve higher control of spatial and temporal variabilities [1] with the aid of satellite remote sensing. The use and application of this set of interconnected technologies are known as “Smart Agriculture” (SA). &nbsp;In Smart Agriculture, real-time and continuous monitoring of weather, crop growth, plant physical/chemical variables, and other important environmental factors allow the optimization of yield production, reduction of labor, and improvement of farming products (See figure 1)[2]. Practices such as irrigation management, resource management, production, or fertilization operations are being facilitated by the integration of IoT systems that are capable to provide information about multiple crop factors (see Fig. 1). In this way, while quality and quantity of production are boosted, the negative aspects of unsustainable and costly agriculture practices are also prevented with advanced interconnected actuators and sensors.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjI1MDM2MDE5NTE1LUlNQUdFIDEtMDEuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 788px;" class="fr-fic fr-dib">Figure 1 Cluster of sensors in a typical crop field.<h2>Why Smart Agriculture?</h2>In this relatively new field, the major focus is crop optimization through higher productivity and major control over environmental variations. SA provides a convenient way to integrate farming management by having in-hand mobile devices that receive data collected from Unmanned Aerial Vehicles (UAV), satellites, or wireless sensors that operate directly at the plant level and are connected for example to cloud-based systems. In general, SA can potentially:<ul><li>Reduce water consumption,</li><li>Implement a better plant nursing process with optimized nutrient levels,</li><li>Decrease risk of yield loss,</li><li>Assurance of higher revenue,</li><li>Better yield quality,</li><li>Decrease overall production of waste,</li><li>Simplification of labour,</li><li>Enhance environmental protection.</li></ul><h2 id="isPasted">Fundamentals</h2>Usually, in SA-IoT ecosystems, the exchange of information occurs in web-based systems that operate at a rapid speed (see Figure 2). For example, ML integrated with multi-scale AI models is used to analyze weather dynamics to predict crop behavior [3]. Signals collected by multifunctional sensors are sent to a remote gateway for further analysis. Data is stored in cloud services that farmers can access away from the farming fields. Cloud analytics help the farmer to configure farming daily duties, responding faster to ever-changing and unpredictable environmental patterns and therefore, allowing better decision making.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjI1MDM2MTY0NDcwLUlNQUdFIDItMDEuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 788px;" class="fr-fic fr-dib">Figure 2 Ubiquitous network in real-time farming.Figure 3 suggests a fundamental configuration of IoT ecosystems that can be replicated for agricultural purposes. The set of elements representing the network makes use of sensors to collect data that is simultaneously captured via ML (see also Fig. 1) and actuators to obtain predictive information. In the physical layer, sensors interact with the environment while humans access data via mobile devices. In the network layer, 4G or 5G technology is used to transmit the data to cloud services. In the cloud section, tensor processing units (TPU) allow speeding computational analysis through the integration of AI, ML, and analytical libraries [4]. Such IoT systems can aid farmers to work remotely by making crop and animal management an automated process with reduced direct human intervention.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjI1MDM2NDYzMTE2LUlNQUdFIDMtMDEuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 788px;" class="fr-fic fr-dib">Figure 3 IoT cloud-based farming.<h2 id="isPasted">From small farming to urban gardening</h2>The IoT can provide solutions for small farmers ranging from resource management to climate adaptability. However, urban gardeners or small producers are also benefiting from innovations brought through the evolution of IoT. Figure 4 shows a common low budget and high precision system [5] designed to improve irrigation in urban gardens. &nbsp;The system is rather simple, but it shows the potential easiness of building open-source solutions without major technical constraints in different setups where adaptation to environmental conditions is required. Basic electromagnetic sensors, power supply, a water pump, relays, and the irrigation system are hardware interconnected and managed via cloud-based monitoring. A control unit receives the data that is later accessed by the user via the internet.<div class="fr-img-space-wrap"><div class="fr-img-space-wrap"><div class="fr-img-space-wrap"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjI1MDM3MDIwNDgyLUlNQUdFIDQtMDEtMDEuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 788px;" class="fr-fic fr-dib">Figure 4 A Smart Agriculture system.</div></div></div>The functionality of the system remains linked to scripted algorithms. With threshold values such as atmospheric temperature or soil moisture, a microcontroller can be fed to fulfill a specific function, such as irrigation [5]. The system permits optimization of limited gardening spaces while providing control of resources to increase plant quality or production yield.Technology democratization can boost the competitiveness of small producers&nbsp;Despite the tremendous potential of SA, technical issues are just one aspect of the whole story. The deployment of high-tech solutions, that are less costly, accessible, reliable, and durable has not yet reached maximum potential. The limited internet coverage in rural areas, especially in emerging economies slows down the deployment of SA technologies. &nbsp;It is why the democratization of IICT including the internet is not a discussion of privilege. It is a crucial step to support the sustainable transformation of agriculture in which small farmers and rural communities can also benefit from technological development.To increase the adaptation of IIoT solutions, several options exist. Offering open access to quality tech solutions presents a potential route to democratize technological advances [6]. The proliferation of mobile connectivity options (e.g. LoRa WAN) and smart technology can support opening such processes to small producers (inclusive from remote locations) who could directly improve their farming experience and access new consumer niches. In the meantime, helping them to connect with investors and other partners. Therefore, facilitating communication between farmers and allowing sharing e.g., IoT projects and best practices.<h2>Conclusion</h2>In sum, this article has covered some of the basic principles of Smart Agriculture, including a description of the structure of fundamental IoT systems and the functional basic principles. In this exploration, an idea about the opportunities that IICT technologies bring to small producers was highlighted. The concept of smart technologies to support the sustainable transition of agriculture was explored. With the implementation of IoT solutions, it was mentioned that small farmers and producers can potentially make better use of their resources with interconnected technologies that can be developed with the use of open-source alternatives. This article just scratches the surface of the ways IIoT can enable positive change in the agricultural sector.This article is the second in a series about IIoT. Read the first article; an engineer's guide to IIoT <a href="https://www.wevolver.com/article/the-engineer-s-guide-to-industrial-iot-and-industry-4-0" rel="noopener noreferrer" target="_blank">here</a>. &nbsp;<h2 id="isPasted">About the sponsor: Arduino Pro</h2>Arduino Pro, aiming to offer adequate solutions for different size companies that are looking to easily evolve their application platforms with the IoT. With a variety of alternatives such as Arduino Edge Control, remote monitoring and control of farming activities can be better managed in a variety of rough environmental settings. With its easiness to adapt to solar-based power supply, the Arduino Edge Control offers the power of AI with state-of-the-art connectivity modems. The Arduino Edge Control, as well as other devices, can be managed via the <a href="https://www.arduino.cc/pro/arduino-iot-cloud" target="_blank">Arduino IoT Cloud</a>. &nbsp;Open source is trustworthy. Farmers can leverage ideas and support from a community of over 30 million users to begin to integrate Arduino components into their smart agriculture solutions. The range of connectivity options available to suit the local conditions along with the ability to process AI on the edge, thereby reducing the frequency and size of data transmitted to the Cloud, makes the Arduino Pro range particularly suited to SA. &nbsp;The design team at Arduino Pro understands the need to move forward in industrial sectors with the commitment to gain major sustainability. For Smart Agriculture, the company offers a set of reliable, manageable, and cost-effective solutions. The evaluation of remote sensor-collected data can be done with Arduino Pro with the advantages that remote monitoring offers. Sensing weather data, soil conditions, and plant health can be improved with the new Arduino Pro solutions. With the Arduino Edge Control, the company aims to reduce effort, improve efficiency and sustainability with the automation of farming processes.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjI1MDM2NzI5ODQ3LWFyZHVpbm8gcHJvIGxvZ28gYXJ0aWNlbCBib3R0b20gYmFubmVyLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 788px;" class="fr-fic fr-dib"><h2>References</h2><ol><li>Goel, R. K., Yadav, C. S., Vishnoi, S., &amp; Rastogi, R. (2021). Smart agriculture – Urgent need of the day in developing countries. Sustainable Computing: Informatics and Systems, 30(January), 100512. <a href="https://doi.org/10.1016/j.suscom.2021.100512" target="_blank">https://doi.org/10.1016/j.suscom.2021.100512</a></li><li>Cicioğlu, M., &amp; Çalhan, A. (2021). Smart agriculture with internet of things in cornfields. Computers and Electrical Engineering, 90(January). https://doi.org/10.1016/j.compeleceng.2021.106982</li><li>Kiran, S., Sandeep Kanumalli, S., Venkata Sesha Sai Rama Krishna, K., &amp; Chandra, N. (2021). Internet of things integrated smart agriculture for weather predictions and preventive mechanism. Materials Today: Proceedings, xxxx. https://doi.org/10.1016/j.matpr.2020.11.081</li><li>Idoje, G., Dagiuklas, T., &amp; Iqbal, M. (2021). Survey for smart farming technologies: Challenges and issues. Computers and Electrical Engineering, 92(April), 107104. https://doi.org/10.1016/j.compeleceng.2021.107104</li><li>Podder, A. K., Bukhari, A. Al, Islam, S., Mia, S., Mohammed, M. A., Kumar, N. M., Cengiz, K., &amp; Abdulkareem, K. H. (2021). IoT based smart agrotech system for verification of Urban farming parameters. Microprocessors and Microsystems, 82(January), 104025. https://doi.org/10.1016/j.micpro.2021.104025</li><li>Goap, A., Sharma, D., Shukla, A. K., &amp; Rama Krishna, C. (2018). An IoT based smart irrigation management system using Machine learning and open source technologies. Computers and Electronics in Agriculture, 155(May), 41–49. https://doi.org/10.1016/j.compag.2018.09.040</li></ol>

A short guide to the technologies behind the next agricultural revolution.

Enabling the sustainable transformation of agriculture with the Internet of Things

In this episode, we talk about the next-gen lunar rover built by Lockheed and GM for NASA’s Artemis mission, how a frustrated tech CEO made a rock-picking robot, and an initiative from University of Manchester to reduce global CO2 emissions by 2% using graphene-enhanced concrete. As always, you can find these and other interesting &amp; impactful engineering articles on Wevolver.com.&nbsp;<iframe height="200px" width="100%" frameborder="no" scrolling="no" seamless="" src="https://player.simplecast.com/b5add957-dddc-4c76-afd3-be64df45c069?dark=false" class="fr-draggable"></iframe><h3>EPISODE NOTES</h3>Take a few seconds to leave us a review. It really helps! <a href="https://apple.co/2RIsbZ2" target="_blank">https://apple.co/2RIsbZ2</a> if you do it and send us proof, we’ll give you a shoutout on the show.(0:41) - <a href="https://www.wevolver.com/article/the-electric-lunar-buggy" target="_blank">NASA's New Moon Buggy</a>:&nbsp;Lockheed Martin and GM have been chosen to develop the next iteration of lunar rovers for NASA’s Artemis missions. GM was a key partner in the development of the first Lunar Rovers and this time around, they hope to incorporate some autonomous driving features from their Cruise self-driving platform.(8:50) - <a href="https://www.wevolver.com/article/terraclear-the-autonomous-rock-picking-solution" target="_blank">Rock Picking Robot</a>:&nbsp;Brent Frei is a tech CEO with a proven record who recently raised a large round of funding for his robotic rock picking startup, TerraClear. As someone who grew up working on a farm, Frei knows the frustration of removing rocks from farmland. Naturally, he built a robot to address the problem.(19:10) - <a href="https://www.wevolver.com/article/meet-the-new-concrete-concretene" target="_blank">Super Strong Graphene Concrete</a>:&nbsp;The University of Manchester has been at the forefront of graphene research since they won the Nobel prize for graphene synthesis in 2010. Their collaboration with Nationwide Engineering aims to reduce CO2 emissions associated with concrete by making a stronger graphene-enhanced alternative.--About the podcast:Every day, some of the most innovative universities, companies, and individual technology developers share their knowledge on Wevolver. To ensure we can also provide this knowledge for the growing group of podcast listeners, we started a collaboration with two young engineers, Daniel Scott Mitchell &amp; Farbod Moghaddam who discuss the most interesting content in this podcast series.&nbsp;To learn more about this show, please visit the <a href="https://www.wevolver.com/profile/the.next.byte" target="_blank">shows page</a>. By following the page, you will get automatic updates by email when a new show is published.Be sure to give us a follow and review on&nbsp;<a href="https://podcasts.apple.com/nl/podcast/the-next-byte/id1548255861?l=en" rel="nofollow" target="_blank">Apple</a> podcasts,&nbsp;<a href="https://open.spotify.com/show/6lPPsRtegnivsRUEsQ09R7?si=IPMiah7xT_apJtPjqvXMlA" rel="nofollow" target="_blank">Spotify</a>, and most of your favorite podcast platforms!

In this episode, we talk about the next-gen lunar rover built by Lockheed and GM for NASA’s Artemis mission, how a frustrated tech CEO made a rock-picking robot, and an initiative from University of Manchester to reduce global CO2 emissions by 2% using graphene-enhanced concrete.

Podcast: NASA's New Moon Buggy, Rock Picking Robot, Super-Strong Concrete

This article was discussed in our <a data-saferedirecturl="https://www.google.com/url?q=https://www.wevolver.com/profile/the.next.byte&source=gmail&ust=1640817319915000&usg=AOvVaw2nPRdRwJrXSYYeM9RCFu5x" href="https://www.wevolver.com/profile/the.next.byte" id="isPasted" rel="noopener noreferrer" target="_blank">Next Byte podcast</a>.&nbsp;<iframe height="200px" width="100%" frameborder="no" scrolling="no" seamless="" src="https://player.simplecast.com/b5add957-dddc-4c76-afd3-be64df45c069?dark=false" class="fr-draggable"></iframe>The full article will continue below.<hr><h3 dir="ltr">A Rocky Problem</h3>Failure to remove rocks scattered through farmland can damage expensive machinery; unfortunately, the process of removing rocks from soil can be labor-intensive, costly, and dangerous to workers. To make matters worse, rock picking is often an annual endeavor because between tilling, erosion, and frost heaving, new rocks are pushed up to the surface every year. <h3 dir="ltr">The Story Behind TerraClear</h3>TerraClear’s <a href="https://www.terraclear.com/company" target="_blank">founder</a>, Brent Frei, has had former fame outside of the farm (in the software realm) where he founded hugely successful companies like Onyx Software and <a href="https://www.smartsheet.com/" rel="noopener noreferrer" target="_blank">Smartsheet</a>. &nbsp;Both companies have since conducted initial public offerings and reached “unicorn” status, boasting market capitalizations of over $1B USD. But how does a bona fide software CEO get into the farming business?Frei’s background in agriculture is deeper than you might guess. He grew up working on his family’s farm in Idaho and after exiting from his role at Smartsheet, he returned to farming full-time with his family. During Frei’s first summer back at the family farm, the backbreaking manual labor of picking rocks to clear farmland motivated him to try and build an automated solution to the problem––and that is how TerraClear was born.&nbsp; <h3 dir="ltr">The TerraClear Solution</h3>TerraClear is a robotic rock-picking arm that mounts to the front of a standard skid-steer loader which can pick up rocks ranging from 6” to 24” in diameter in a 3’ wide picking swath. TerraClear can carry over 1500lbs of rocks and removes up to 400 rocks per hour. Currently, the arm is manually operated, but TerraClear is developing a version that uses autonomous hydraulic controls supported by computer vision to remove rocks from the soil without human intervention. <div class="fr-img-space-wrap"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjIyNDc5Mjg2NTAzLXRlcnJhY2xlYXIgYXJtLnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" class="fr-fic fr-dib" style="width: 400px;">Robotic arm attachment for skid loaders and tractors (image credit:&nbsp;<a href="https://www.terraclear.com/products/rock-picker" rel="noopener noreferrer" target="_blank">TerraClear</a>)&nbsp;TerraClear bolsters their rock removal technology with advanced surveys conducted by drones that fly over the farmland to produce a map of rock locations and sizes. These rock maps help farmers to identify areas of interest for rock removal. Between TerraClear’s rock removal and rock surveying technologies, a once cost- and labor- intensive job for farmers is simplified to the easy task of driving a skid loader around their field.</div> <div class="fr-img-space-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1622479453917-rock+map.gif" style="width: 400px;" class="fr-fic fr-dib">A drone-generated map with rock sizes and locations (image credit: &nbsp;<a href="https://www.terraclear.com/products/rock-mapping-service" rel="noopener noreferrer" target="_blank">TerraClear</a>) <h3 class="fr-img-space-wrap2">&nbsp;Significance</h3></div>There has been a surge of robotics and AI technologies in the agriculture space that aim to automate all sorts of complex tasks from harvesting to weeding and sorting, but none have focused on the mundane problem that is rock picking. TerraClear leverages proven technology to reduce the time &amp; cost that farmers have to invest to remove rocks and get their fields ready for planting.As Frei <a href="https://news.yahoo.com/rock-picking-robotics-startup-terraclear-150037521.html" rel="noopener noreferrer" target="_blank">says</a>,<blockquote>“there are more than 400 million arable acres worldwide that have been waiting for a cost-effective and productive solution to this problem. Repetitive tasks like this are optimal targets for automation, and the technologies we are bringing to the field dramatically reduce the labor and time needed to prep fields.”</blockquote>

TerraClear's robotic arm attachment for rock picking (image credit: TerraClear)

TerraClear is developing an autonomous system to remove rocks from farmland, making it easier for farmers to get their fields ready for planting.

TerraClear: The Autonomous Rock-Picking Solution

Digitization and artificial intelligence (AI) play a key role in addressing the many challenges facing agriculture. In order to make use of the enormous potential of intelligent technologies, a trustworthy and powerful IT infrastructure is needed. Following the initiative of the Agrotech Valley Forum, a renowned consortium from industry and research is working in the Agri-Gaia project on the realization of an open AI standard for the agricultural and food industry based on the European GAIA-X cloud initiative. The project is funded by the German Federal Ministry for Economic Affairs and Energy (BMWi) with around 12 million euros.&nbsp;Agriculture is facing enormous challenges: On the one hand, it has to feed more and more people and, as a result, make increasingly efficient use of the available arable land. On the other hand, in times of climate change, it is called upon to act as ecologically as possible and to adapt quickly to ever-changing conditions. Artificial intelligence will serve farmers as well as medium-sized companies – the innovative and efficient backbone of the German agricultural industry – as a tool for using resources more efficiently and protecting ecosystems sustainably. However, the development of AI-supported solutions for agricultural applications requires research competences that go beyond the capabilities of medium-sized companies. In addition, there is a lack of efficient ways to make current and industry-specific AI methods accessible for diverse application developments. Open AI ecosystem for the agri-food industry shaped by medium-sized companiesThis is where the Agri-Gaia project comes in. Together with a growing number of supporters from associations, research, politics and industry, the project partners are working under the leadership of the German Research Center for Artificial Intelligence (DFKI) to develop an open, decentralized infrastructure for the development and exchange of AI algorithms in agriculture. &nbsp;In this way, an AI ecosystem is to be created for the agri-food industry, which is shaped by medium-sized businesses, based on the European cloud initiative GAIA-X. In addition to DFKI, the consortium includes AgBrain GmbH, Agrotech Valley Forum e.V., Amazonen-Werke H. Dreyer GmbH &amp; Co. KG, Robert Bosch GmbH, CLAAS E-Systems GmbH, Osnabrück University of Applied Sciences, Josef Kotte Landtechnik GmbH, Maschinenfabrik Bernard Krone GmbH &amp; Co. KG, LMIS AG, the University of Osnabrück and Wernsing Feinkost GmbH. Robert Everwand, cluster manager of the Agrotech Valley Forum:&nbsp;"Digitization is a prerequisite for future-oriented agriculture. At the same time, it presents agricultural players with major challenges. With Agri-Gaia, we also want to give medium-sized companies the opportunity to push the development of intelligent technologies for the agricultural industry. This benefits not only the companies and the farms, but ultimately all of us." Agri-Gaia is the first use case of the application domain “Agrar” in the European large-scale project GAIA-X. In it, representatives from politics, business and science are developing the basis of a modern, cross-domain data infrastructure that is intended to ensure Europe's digital sovereignty and enable data exchange within the framework of the European General Data Protection Regulation. The Agri-Gaia consortium has established the “Agrar” domain in GAIA-X, which is coordinated by Prof. Dr. Engel Hessel from the German Federal Ministry of Food and Agriculture (BMEL) and Dr. Stefan Stiene from the DFKI Laboratory Niedersachsen. In this domain, use cases such as Agri-Gaia will be developed to demonstrate the potential of GAIA-X for agriculture. Prof. Dr. Joachim Hertzberg, head of the DFKI Laboratory Niedersachsen: "We have hit a nerve with Agri-Gaia. The need for a secure networked data infrastructure, as envisaged in GAIA-X, is huge – especially for AI developments. Numerous companies from across the agribusiness value system have already approached us and plan to support the standard and become part of the Agri-Gaia ecosystem." Industry-specific AI building blocks for innovative applications and business modelsTo create this ecosystem, the partners are implementing an innovative B2B platform that provides industry-specific adapted AI building blocks as easy-to-use modules and brings users together with developers of AI algorithms. The goal of the project is to close the loop from sensor data acquisition on agricultural machines to the training of algorithms on corresponding servers to the continuous updating and optimization of these algorithms. To this end, Agri-Gaia is developing appropriate interfaces and standards that will create a cross-manufacturer infrastructure. In this way, the project benefits the entire agricultural sector and enables innovative business models. Start-ups and small companies in particular can reach a broad market with their data- and algorithm-based services. In this way, Agri-Gaia is intended to act as an AI catalyst that ensures that AI technologies are used in a wide variety of places throughout the entire agribusiness – for an efficient and simultaneously sustainable agriculture.

Based on innovative agricultural technology, the Agri-Gaia project explores the use of AI in agriculture. © Hochschule Osnabrück

Digitization and artificial intelligence (AI) play a key role in addressing the many challenges facing agriculture. In order to make use of the enormous potential of intelligent technologies, a trustworthy and powerful IT infrastructure is needed.

Agri-Gaia: Strong alliance of companies develops open AI standard for agriculture based on GAIA-X

With robots in agriculture becoming more of the norm rather than the exception, the term high-tech farming is no longer an oxymoron. Farming robots are now involved in almost every farming activity, helping farmers fill labor shortages and supermarket shelves simultaneously.

The Future of Agriculture: Adopting More Advanced Robots for Next-Gen Farming

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Enabling the sustainable transformation of agriculture with the Internet of Things

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Agri-Gaia: Strong alliance of companies develops open AI standard for agriculture based on GAIA-X

The Future of Agriculture: Adopting More Advanced Robots for Next-Gen Farming