Explore the transformative power of precision agriculture, highlighting innovations like Particle's M-Series and the future of sustainable farming. Dive into the evolution, technologies, and trends shaping tomorrow's agriculture.

Unearthing the Potential of Precision Agriculture

With the expected population of the UK to be 73.7 million by 2036 and increased pressure to reach net zero by 2050, how does the Agriculture industry fair when challenged with growing populations, climate change, sustainability goals and resource inefficiencies? 

What does the future hold for Agritech?

Our new report, AI at the Edge: Technology Accelerated by Wi-Fi Services, dives deeply into the convergence of Wi-Fi services and Edge AI and explores how a technology model like WaaS can accelerate the adoption of AI at the edge.&nbsp;Below is an excerpt from Chapter 3 of the report. To read the full report, including in-depth case studies, download it now.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1710514655459-Relay+2.png" style="width: 100%px;" class="fr-fic fr-dib"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> The applicability of Wi-Fi Edge AI is fairly expansive and is growing by the day, spanning various industries and application areas. The most central aspects of this intersection of technologies are the real-time insights they provide, how these insights impact the speed and type of response, and how they are communicated across the network. Whether it is in smart healthcare, education, retail, or other application areas, Wi-Fi-enabled Edge AI is redefining how technology is leveraged in real time. Relay2 utilizes several Edge AI platforms to enhance the functionality of AI applications on the edge. In this chapter, we will take a look at some interesting use cases of Wi-Fi Edge AI, and we will see the impact of this technology convergence and the new opportunities it is opening in new and emergent technological spaces.<h2>Education / Smart Campus</h2>Wi-Fi Edge AI plays an important role in education-related applications, among which is remote learning integration, facilitating seamless and interactive remote education and bridging the gap between on-site and remote learning experiences. With localized content engagement pattern analysis and personalized experiences for students, Wi-Fi services and edge computing can help enhance and refine education content delivery.&nbsp;Campus facilities can also benefit significantly from integrating such technologies, especially in terms of security and surveillance, where Wi-Fi Edge AI can help analyze surveillance videos locally and in real time to recommend timely actions for security staff. It also powers use cases like attendance automation and traffic patterns, streamlining attendance tracking for educators and student flow analysis for operation enhancement.&nbsp;Another use case of Wi-Fi and edge computing can be seen in revenue generation, in which they enable intelligent, location-based advertising through audience behavior analysis for commercial partners. By leveraging these technologies, educational institutions can help promote campus services better, boost product marketing across campus premises and beyond, and enable efficient digital transactions.One example of applying Wi-Fi and edge computing in education is by WENet, an OEM partner of Relay2 in Vietnam. In order to support the University of Transport Technology in Vietnam in developing a digital technology infrastructure platform, WENet deployed Relay2’s Wi-Fi-enabled edge computing solution, making use of the advantages provided by Relay2 ServiceEdge Platform compared to conventional Wi-Fi networks. From stable bandwidth to fast processing speed, short deployment time, minimal service interruption time, and optimal operating costs, the features brought about by Relay2’s ServiceEdge Platform were highly effective. As a result, over 17 thousand students across three campuses were able to benefit from this platform, especially in terms of the following three key functions:<ul><li>Digital signage interacting with mobile devices to support two-way communication (university-to-student communication and student responses to university requests)</li><li>Students’ access to digital education materials from Relay2’s Service Points</li><li>Students’ ability to order food digitally from the cafeteria</li></ul>Such functions have not only enabled students to benefit from a Wi-Fi-powered edge computing platform but also helped collect analytic data for future AI processing at the edge. Read more about the WENet use case on the Relay2 website.<h2>Smart Healthcare</h2>Undoubtedly, one of the most important aspects of healthcare is real-time monitoring and real-time decision-making. However, as we have seen over the recent years with pandemic-caused crises, healthcare workers are more often than not overworked, and hospitals are resource-limited, which can limit their abilities to provide timely care. In order to ensure patient safety and health within hospital spaces and elsewhere, it is crucial to track, monitor, analyze, and act in real-time. All this can be made available by incorporating Edge AI and Wi-Fi. Whether it is remote monitoring and management, patient activity tracking, patient care, or even assistance during healthcare crises, hospitals, and medical personnel can benefit significantly from integrating Wi-Fi Edge AI into their processes.Smart healthcare comes in the form of connected healthcare, where AI-based smart devices, healthcare management software, and digital instruments are integrated into a “connected” healthcare system using a network protocol like Wi-Fi. As such, medical personnel would have access to all the medical-related information they need to provide the patients with the necessary medical treatment in the most effective and convenient way possible. This has been made possible by utilizing Edge AI and Wi-Fi technologies to empower the Internet of Medical Things (IoMT). In other words, healthcare personnel can leverage the low-latency capabilities of Edge AI processing and the ubiquity of Wi-Fi connectivity to access real-time data from diverse medical sensors, enabling timely decision-making and interventions and fostering a proactive approach to patient care.Consider intensive care units (ICUs), operating rooms, or other healthcare spaces, the use of Edge AI and Wi-Fi can augment the work of doctors, nurses, and clinicians by minimizing limitations, redundancies, and time allocated to activities away from direct patient care (such as documentation). As a result, medical workers can benefit from an emerging ambient intelligence , powered by edge computing, AI capabilities, and Wi-Fi. This can even be expanded to daily living spaces, which would support independent living, chronic disease management, mental health, and physical rehabilitation, particularly of elderly individuals.<h2>Smart Retail</h2>Global retail is almost always in flux, and both retailers and suppliers are grappling with the complexities of ever-changing consumer demand, behavior, and expectations. The continuous shifts in these dynamics create uncertainties in predicting future trends and exert significant stress on international supply chains and store operations. Navigating these challenges necessitates real-time adaptability to stay ahead in the retail industry.Edge AI emerges as a potent solution, offering retailers the capability to swiftly and precisely forecast daily demand while automating crucial aspects of supply chain logistics, customer engagement, and operational agility. This not only addresses challenges related to in-store supply management but also tackles issues in last-mile delivery costs, aligning with consumer expectations regarding timely deliveries.Within physical stores, retailers leverage Edge AI to combat issues such as shrinkage and stockouts, optimizing inventory management. Simultaneously, the application of Edge AI and Wi-Fi contributes to the creation of frictionless in-store experiences while prioritizing the health and safety of both employees and shoppers. The integration of AI in retail is thus transforming operations, offering a multifaceted approach to address the intricate challenges posed by the dynamic retail landscape.D.Phone, one of the largest cell phone retailers out of China, has deployed in-store Wi-Fi to enhance its customer experience and promote engagement as a way to offer a differentiated experience that would distinguish its &nbsp;D.Phone stores from competitors. They opted for Relay2’s wireless broadband solution, taking advantage of its unified native-cloud wireless networking and edge-service delivery.By leveraging Relay2 access points, D.Phone was able to offer high-quality customer experiences and deliver value-added services in-store. With its fast and reliable coverage in demanding environments like customer-dense spaces, including shopping centers and large venues, Relay2 access points enabled D.Phone to meet its customers' expectations and offer them the high-speed connectivity they desire. Moreover, with Relay2’s Edge services, D.Phone was able to run sales-generating applications and computation-intensive services locally and place content right at its &nbsp;D.Phone customers’ fingertips, thus reducing content download time to just seconds. This helped streamline the customer purchasing experience and circumvent bandwidth bottlenecks. It even enabled D.Phone to deliver new services to its customers, including app delivery and couponing. This has displayed an accelerated go-to-market process for D.Phone’s digital merchandise and a reinforced branding strategy. Read more about the D.Phone use case on Relay2’s website.<blockquote>“Relay2’s plug-and-play access points and cloud-based platform [have] given us a solution that lowers the cost of deployment and management.” - Wu Huan, CIO, D.Phone</blockquote><h2>Smart Buildings</h2>With the recent growth in smart homes and building automation systems, edge computing, AI, and Wi-Fi have become increasingly popular in this space. The integration of Edge AI with sustainable architecture and smart buildings has been rapidly gaining momentum and transforming the manner in which we construct and interact with our built spaces. With advantages like enhanced energy efficiency, optimized systems, personalized occupant comfort, and streamlined building maintenance, smart buildings are leveraging the real-time analysis capabilities of Edge AI and its integration with IoT and developing potential for more sustainable architecture and digital integration.Acting as a centralized intelligence hub, AI processes and interprets data obtained from an array of edge devices (IoT devices) such as sensors and actuators scattered throughout the building. This network of devices forms a comprehensive information system, providing valuable insights into various aspects of the building's operations. Through the implementation of AI algorithms, smart buildings gain the ability to efficiently monitor and regulate crucial functions like lighting, heating, ventilation, air conditioning, security, and energy consumption. Such an integration results in an environment that is not only responsive but also adaptive, catering to the dynamic needs and preferences of the building occupants.This can be further supported by Wi-Fi connectivity and cloud-based Wi-Fi services, in particular. Cloud-based Wi-Fi services enable centralized management and control of Wi-Fi networks. This centralized approach simplifies the deployment and maintenance of Wi-Fi connectivity across the building, ensuring a more streamlined and scalable infrastructure. Furthermore, the cloud facilitates the storage and analysis of the vast amounts of data generated by IoT devices in Smart Buildings. AI algorithms require substantial data inputs to make informed decisions, and cloud-based services offer the computational resources needed for processing and interpreting this data. It enables more sophisticated analytics, allowing for better insights into building operations, occupant behaviors, and energy consumption patterns.&nbsp;Similarly, the cloud's scalability can easily accommodate the dynamic nature of Smart Buildings, especially when the number of connected devices grows or changes. Just as importantly, cloud-based services enable remote monitoring, management, and updates of Wi-Fi networks and connected devices. This remote accessibility is invaluable for building administrators, allowing them to troubleshoot issues, implement updates, and optimize network performance without physically being on-site. In this regard, smart buildings can benefit meaningfully from Relay2’s innovative solutions. With advanced networking capabilities, Wi-Fi Edge Computing power, and intelligent analytics, users of Relay2’s ServiceEdge platform can ensure seamless connectivity and optimized operational efficiency.<h2>Smart Agriculture</h2>The Internet of Things (IoT) and edge computing have influenced the agricultural and farming industries quite extensively over the past decade, especially with the rapid rise of low-power wide-area networks (LPWAN) . Wireless communication protocols are, in fact, a vital part of smart agriculture systems, especially since the fields cover large areas that necessitate system components to be placed at remote locations. The integration of Wi-Fi and edge computing has been key to expanding the digital functionalities in agriculture, especially with the advent of AI at the edge, thus increasing the possibilities of smart agriculture over large areas.One type of smart agriculture that has been propelled by Edge AI and Wi-Fi services is precision farming. By deploying sensors and cameras in fields, farmers can gather real-time data on crucial factors such as weather patterns, soil conditions, crop growth, and pest infestations. This localized data processing enables farmers to modify and regulate their irrigation, fertilization, and pest control without delay, leading to an increase in crop yields and resource efficiency. The implementation of edge devices equipped with sensors extends beyond crop monitoring to include livestock health and behavior. Wearable devices on animals, such as cattle, provide early indications of illness or oestrus, empowering farmers to take timely actions, resulting in improved animal well-being, reduced rates of mortality, and higher farm productivity all around.&nbsp;Furthermore, the incorporation of Edge AI has paved the way for autonomous farming machinery, where tractors and drones equipped with edge devices can analyze field data in real time. This enables them to refine their routes, control planting depths, and identify and eliminate weeds in an autonomous manner. Not only does autonomous farming machinery reduce labor costs, but it also minimizes the use of chemicals, aligning agriculture with more eco-friendly practices. This is further empowered with the integration of Wi-Fi Services, allowing for centralized, remote monitoring and seamless connectivity between edge devices across large fields and in remote areas. The seamless integration of Edge AI and Wi-Fi technologies is proving transformative in making agriculture smarter, more efficient, and more sustainable over expansive agricultural landscapes.Relay2 offers smart farms state-of-the-art solutions that can help transform crop production, efficiency, and sustainability. These solutions seamlessly connect and monitor agricultural devices, collect real-time data, and leverage advanced analytics for informed decision-making. By optimizing resources, automating processes, and implementing precision farming, Relay2 empowers farmers to maximize yield and sustainability.<hr>This was an excerpt from Chapter 3 of the AI at the Edge: Technology Accelerated by Wi-Fi Services report. If you would like to read the full report, including in-depth case studies, you can download it below. &nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1710514806917-Relay+2.png" style="width: 100%px;" class="fr-fic fr-dib"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>

Wi-Fi-enabled Edge AI is redefining how technology is leveraged in real time.

AI at the Edge Report. Chapter 3: Applications & Case Studies

New, highly stretchable sensors can monitor and transmit plant growth information without human intervention, report University of Illinois Urbana-Champaign researchers in the journal Device.&nbsp;The polymer sensors are resilient to humidity and temperature, can stretch over 400% while remaining attached to a plant as it grows and send a wireless signal to a remote monitoring location, said <a href="https://chbe.illinois.edu/" target="_blank">chemical and biomolecular engineering</a> professor <a href="https://chbe.illinois.edu/people/profile/yingdiao" target="_blank">Ying Diao</a>, who led the study with <a href="https://sib.illinois.edu/departments/plant-biology" target="_blank">plant biology</a> professor and department head <a href="https://sib.illinois.edu/directory/profile/leakey" target="_blank">Andrew Leakey</a>.The study details some of the early results of a NASA grant&nbsp;<a href="https://las.illinois.edu/news/2020-12-18/cultivating-astronomical-plant-growth" target="_blank">awarded to Diao</a> to investigate how wearable printed electronics will be used to make farming possible in space.“This work is motivated by the needs of astronauts to grow vegetables sustainably while they are on long missions,” she said.&nbsp;Diao’s team approached this project using an Earth-based laboratory to create a highly dependable, stretchable electronic device – and its development did not come easily, she said.&nbsp;“Honestly, we began this work thinking that this task would only take a few months to perfect. However, we quickly realized that our polymer was too rigid,” said Siqing Wang, a graduate student and first author of the study. “We had to reformulate a lot of the components to make them more soft and stretchable and adjust our printing method to control the assembly of the microstructures inside the device so that they did not form large crystals during the printing and curing process.”&nbsp;The team landed on a very thin film device that helps restrain the crystal growth during assembly and printing.“After addressing the stretchability and assembly issues, we had to tackle the problems that come with working with wearable electronics in high humidity and under rapid growth rates,” Wang said. “We needed reproducible results so we could not have the sensors fall off or electronically fail during the growth experiments. We finally came up with a seamless electrode and interface that was not affected by the demanding conditions.”<iframe width="640" height="360" src="https://www.youtube.com/embed/WU1mXLertMM?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>The ‘Stretchable-Polymer-Electronics-based Autonomous Remote Strain Sensor,’ or SPEARS2 – is the product of three years of hard work, proving that applied science rarely experiences eureka moments. &nbsp;“It is an exciting technical advance in our ability to perform precise, noninvasive measurements of plant growth in real-time. I look forward to seeing how it can complement the latest tools for interrogating genomic and cellular processes,” Leakey said.Diao also said she is excited to uncover all of the ways this research will continue to progress.&nbsp;For example, this study looks at plants like corn that grow primarily upward. However, the researchers plan to advance their electronics printing methodology to create a system that can monitor upward and outward growth.&nbsp;The team said they are also working toward the ability to sense and monitor chemical processes remotely. &nbsp;“I think the wearable electronics research community has ignored plants for too long,” Diao said. “We know that they are experiencing a lot of stress during climate adaptation, and I think soft electronics can play a bigger role in advancing our understanding so we can ensure that plants are healthy, happy and sustainable in the future – whether that is in space, on other planets or right here on Earth.”&nbsp;Researchers at NASA and Illinois researchers from&nbsp;<a href="https://bioengineering.illinois.edu/" target="_blank">bioengineering</a>,&nbsp;<a href="https://cropsciences.illinois.edu/" target="_blank">crop sciences</a>,&nbsp;<a href="https://matse.illinois.edu/" target="_blank">material science and engineering</a>, the&nbsp;<a href="https://www.igb.illinois.edu/" target="_blank">Carl R. Woese Institute for Genomic Biology</a> and the&nbsp;<a href="https://beckman.illinois.edu/" target="_blank">Beckman Institute</a><a href="https://beckman.illinois.edu/" target="_blank">&nbsp;for Advanced Science and Technology</a> contributed to this study.&nbsp;

 Research led by the University of Illinois Urbana-Champaign uses polymer-based stretchable electrodes to remotely monitor plant growth, bringing scientists a step closer to growing plants in space to feed astronauts during long missions.  Photo courtesy NASA Marshall Space Flight Center

New, highly stretchable sensors can monitor and transmit plant growth information without human intervention, report University of Illinois Urbana-Champaign researchers in the journal Device. 

Study brings scientists a step closer to successfully growing plants in space

In this episode, we discuss how Dyson - the company best known for their vacuum cleaners - has created an automated and sustainable farm to harvest the best possible strawberries with the least amount of environmental impact.

Podcast: Dyson's Automated, Self-sustaining Strawberry Farm

It’s no secret that digital manufacturing is revolutionising the agriculture industry – In fact, we delved into the <a href="https://www.protolabs.com/en-gb/resources/blog/turning-over-a-new-leaf-digital-manufacturing-in-agriculture/?utm_source=wevolver&utm_medium=referral&utm_campaign=uk-agriculture-0124&utm_content=wevolver-digital-manufacturing-agriculture-blog-0224" target="_blank" title="Turning Over a New Leaf: Digital Manufacturing in Agriculture">transformative potential of digital manufacturing</a> in agriculture in an earlier blog. But the demand for more is unprecedented, which begs the question: what is driving the growth?Let’s look at the five root causes of the insatiable appetite for digital manufacturing in agriculture to understand how it is making such an impact. Green Consumers on the RiseDemand Driver: As environmental awareness grows, consumers increasingly seek products produced through sustainable and environmentally friendly practices. This shift in consumer preferences pressures the agriculture industry to adopt sustainable methods throughout the supply chain, from farming practices to food processing.Digital Manufacturing Impact: Digital manufacturing enables the agriculture industry to embrace sustainable practices by incorporating precision farming, reducing waste, and optimising resource usage. The demand for digital manufacturing rises as it becomes a key enabler for meeting consumer expectations for environmentally conscious products.&nbsp;<img border="0" width="431" src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA4NDMxMzgwNTk1LTE3MDg0MzEzODA1OTUuanBlZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" alt="arrow lake - technology for agriculture" class="fr-fic fr-dii">&nbsp;When designing their ozone purification system, The FLO3W®,&nbsp;Arrow Lake, was able to make a rapid decision about the feasibility of their part by using Protolabs’ automated solution to get an immediate initial analysis of manufacturability and cost-effectiveness.&nbsp;<a href="https://www.protolabs.com/en-gb/resources/case-studies/arrow-lake/?utm_source=wevolver&utm_medium=referral&utm_campaign=uk-agriculture-0124&utm_content=wevolver-digital-manufacturing-agriculture-blog-0224" target="_blank" title="Arrow Lake">Read the case study to find out how they did it.</a>&nbsp;&nbsp;Regulatory PressuresDemand Driver: Governments and regulatory bodies worldwide are implementing stricter environmental regulations and standards. Compliance with these regulations is not just a legal requirement but also a necessity for businesses to operate sustainably and maintain their Social License to Operate.Digital Manufacturing Impact: Digital manufacturing provides the tools and processes necessary for the agriculture industry to meet and exceed regulatory requirements. From precision farming practices to energy-efficient manufacturing techniques, the demand for digital manufacturing is fuelled by the need to align with and surpass regulatory standards.&nbsp;Small Portions of ResourceDemand Driver: The agriculture industry faces challenges related to resource scarcity, including water, arable land, and energy. Volatile prices for these resources make it imperative for businesses to optimise resource usage and reduce waste to maintain profitability.Digital Manufacturing Impact: Digital manufacturing technologies, such as precision farming and automated processes, help optimise the use of resources. By reducing waste, improving efficiency, and minimising the environmental impact of agriculture and food processing, digital manufacturing has become a sought-after solution to address resource scarcity and volatile prices.&nbsp;<img border="0" width="399" src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA4NDMxMzgwNjA1LTE3MDg0MzEzODA2MDQuanBlZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" alt="fambot - automation in horticulture" class="fr-fic fr-dii">&nbsp;FarmBot, the&nbsp;world’s first open-source, CNC small-scale farming machine, allows individuals to create and manage a garden using a laptop, tablet, or phone to oversee the automated planting, watering, and monitoring of crops. Protolabs’ product development experts helped FarmBot transition from 3D-printed components to more&nbsp;<a href="https://www.protolabs.com/en-gb/resources/case-studies/farmbot/?utm_source=wevolver&utm_medium=referral&utm_campaign=uk-agriculture-0124&utm_content=wevolver-digital-manufacturing-agriculture-blog-0224" target="_blank" title="FarmBot">repeatable and cost-effective injection-moulded parts.</a>&nbsp;&nbsp;Technological AdvancementsDemand Driver: Advances in technology, including renewable energy technologies, efficient manufacturing techniques, and smart systems, are driving the demand for more sustainable products and processes across industries. Businesses that adopt these technologies gain a competitive edge in efficiency, cost-effectiveness, and environmental stewardship.Digital Manufacturing Impact: Digital manufacturing plays a crucial role in implementing these technological advancements in agriculture. Whether using smart sensors in precision farming or adopting sustainable manufacturing practices, digital manufacturing is at the forefront of technological innovation, driving demand in the agriculture industry.&nbsp;<img border="0" width="491" src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA4NDMxMzgwNjEzLTE3MDg0MzEzODA2MTMuanBlZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" alt="small robot company - robotic agriculture innovation" class="fr-fic fr-dii">&nbsp;Small Robot Company&nbsp;developed the 21st-century answer to the 21st-century problem in agriculture, producing more food from less land. Their Tom V4 Per Plant farming makes autonomous robotic farming a reality, meaning more food and less waste at a cheaper cost than ever before. With sustainability as the driving force of their product, they needed to minimise the entire system weight so that ground pressure was reduced, so they partnered with Protolabs to&nbsp;<a href="https://www.protolabs.com/en-gb/resources/case-studies/small-robot-company/?utm_source=wevolver&utm_medium=referral&utm_campaign=uk-agriculture-0124&utm_content=wevolver-digital-manufacturing-agriculture-blog-0224" target="_blank">3D Print two different parts&nbsp;for their latest agri-robot.</a>&nbsp;&nbsp;Squaring the Circular EconomyDemand Driver: The circular economy approach, emphasising waste reduction, reuse, and recycling, is gaining traction as a sustainable business model. Life Cycle Assessment (LCA) is a key element in assessing the environmental impact of products from creation to disposal.Digital Manufacturing Impact: Digital manufacturing supports the circular economy by enabling more efficient use of materials, reducing waste in production processes, and promoting developing products with a longer lifespan. The demand for digital manufacturing rises as businesses seek to align with circular economy principles and implement sustainable practices throughout their operations.&nbsp;The agriculture industry is quickly realising the importance of sustainability and the need to address environmental awareness, regulatory pressures, resource scarcity, technological advancements, and the rise of the circular economy. That's where digital manufacturing comes in as a critical solution to support more eco-friendly and efficient practices in agriculture and food production. It's exciting to see businesses recognising the potential impact of this technology and embracing it to meet these challenges.

It's no secret that digital manufacturing is revolutionising the agriculture industry. In this blog, we explore the five root causes of the insatiable appetite for digital manufacturing adoption in agriculture to understand how is making such an impact.

Digital Manufacturing: The Growing Appetite in Food and Agriculture

As the IoT matures, analysts forecast that NB-IoT and LTE-M&nbsp;(<a href="https://www.nordicsemi.com/Products/Wireless/Low-power-cellular-IoT" target="_blank" rel="noreferrer noopener">cellular IoT</a>) are likely to become the dominant technologies for connecting local area networks (LANs) or standalone wireless devices over kilometer distances to the Cloud. The process is already well underway and forms a lucrative market into which IoT connectivity vendors are keen to tap.&nbsp;&nbsp;<h2>LPWAN&nbsp;IoT&nbsp;connections set to&nbsp;boom&nbsp;</h2>Low power wide area networks (LPWANs) are a critical part of the IoT’s infrastructure and as such are set to grow rapidly. According to global intelligence firm, ABI Research, LPWAN connections will reach 5.3 billion in 2030, with smart metering, asset tracking, and condition-based monitoring cited amongst key IoT applications.&nbsp;&nbsp;Statista forecasts LPWAN IoT connections will outnumber any other IoT connectivity technology by 2030. And a recent study by Allied Market Research projects the global LPWAN market—valued at $8.2 billion in 2022—will reach a staggering $582 billion by 2032, growing at a CAGR of 53.4 percent over the forecast period (2023-to-2032).&nbsp;&nbsp;<h2>Bridging the gap&nbsp;between&nbsp;IoT end-devices and the Cloud&nbsp;</h2>But as rapidly as the LPWAN market is growing, it remains fragmented. However, cellular IoT is gaining traction as the dominant ‘bridge’ between remote IoT end-devices and the Cloud. As alternative non-cellular connectivity technologies like LoRaWAN and Sigfox face technical and commercial pressures, cellular IoT is establishing itself as the LPWAN leader.&nbsp;&nbsp;For example, according to Mordor Intelligence’s&nbsp;Cellular IoT Market Size &amp; Share Analysis – Growth Trends &amp; Forecasts (2023–2028)&nbsp;report, the cellular IoT market size is expected to grow from $5.02 billion in 2023 to $14.26 billion by 2028, at a CAGR of 23.21 percent during the five-year forecast period. This global market growth will be driven by the rise in digitalization and automation across industries such as manufacturing, automotive, and energy and utilities, claims the analyst.&nbsp;<h2>Key advantages for massive IoT&nbsp;</h2>Cellular IoT growth comes from the key advantages it offers for massive IoT; chief among these advantages is its Internet Protocol (IP) interoperability which enables a bidirectional link between end-devices and the Cloud without the need for expensive and complex routers or gateways. Further advantages include future proofing, scalability, security, and high quality of service (QoS).&nbsp;&nbsp;<h2>NB-IoT&nbsp;for static&nbsp;applications&nbsp;and LTE-M&nbsp;for mobile applications&nbsp;</h2>NB-IoT and LTE-M&nbsp;are the two underlying technologies supporting cellular IoT. NB-IoT is suited to static applications. Examples include smart meters and smart streetlights. LTE-M is suited to devices that can change locations, such as asset trackers or wearables.&nbsp;&nbsp;<h2>Flexibility and support for massive IoT&nbsp;</h2>Industry experts suggest the positive trends for NB-IoT and LTE-M can largely be attributed to flexibility and support for massive IoT that cellular IoT’s competitors struggle to match.&nbsp;&nbsp;Cellular IoT uses existing cellular base stations (with software upgrades) to connect massive IoT devices to the Cloud. The LPWAN technology can connect over kilometers, supports a high density of IoT devices, doesn’t require much battery power, and offers high security. &nbsp;&nbsp;Cellular IoT base stations can each support up to 50,000 cellular IoT connections. The communications are fully bidirectional, and the technology is an integral part of the 5G specifications.&nbsp;Standardization for 5G is carried out by several international organizations, primarily the International Telecommunication Union (ITU), the 3rd Generation Partnership Project (3GPP), the Internet Engineering Task Force (IETF), and the European Telecommunications Standards Institute (ETSI).&nbsp;Based on the support of these mature global standards bodies, powerful mobile network operators (MNO)—such as Vodafone, Orange, Telenor, and Telefonica—and a solid vendor ecosystem including Nordic Semiconductor, cellular IoT is beginning to justify the hype, not to mention the considerable investment.&nbsp;&nbsp;<h2>Cellular IoT takes the largest market&nbsp;share&nbsp;</h2>The technical and commercial advantages of cellular IoT are driving the technology towards a dominant share of the LPWAN market. According to IoT Analytics, NB-IoT (47 percent) and LTE-M (10 percent) already made-up 57 percent of the global LPWAN installed base in 2022, compared to 43 percent for the combined competition.&nbsp;&nbsp;In its&nbsp;LPWAN Market Report – 2022, Omdia predicted LPWAN connections will grow at a CAGR of 23 percent in the five-year period to 2028, driven predominantly by growth in NB-IoT and LoRaWAN technologies. The analyst forecasts NB-IoT and LoRaWAN will account for 87 percent of all LPWAN connections in 2028, up from 85 percent in 2023.&nbsp;The company expects there will be almost 1.6 billion NB-IoT LWPAN connections in 2028 with a further 300 million LTE-M connections – around 800 million more connections than the closest competitor, LoRaWAN, and dwarfing the number of connections for Sigfox and other technologies.&nbsp;<h2>Boosting productivity and saving cost&nbsp;</h2>Cellular IoT connectivity has already played&nbsp;a major role&nbsp;in enhancing productivity, streamlining operations, minimizing downtime, automating processes, and generating cost savings across various industries&nbsp;– for example,&nbsp;utilities, agriculture, industrial, retail,&nbsp;and healthcare. And having&nbsp;already&nbsp;taken the lead&nbsp;in&nbsp;the LPWAN&nbsp;sector, the technology is on track to&nbsp;command&nbsp;a critical role in the future of the IoT.&nbsp;

As the IoT matures, analysts forecast that NB-IoT and LTE-M (cellular IoT) are likely to become the dominant technologies for connecting local area networks (LANs) or standalone wireless devices over kilometer distances to the Cloud. 

Cellular IoT dominates LPWANs

Wageningen University &amp; Research developed MARVIN technology for high-speed plant phenotyping, seedling sorting, and other bulk quality assessment and sorting applications for the agricultural sector. For fast and high-quality scanning and 3D model creation of plants, they use Photoneo 3D camera MotionCam-3D Color and 3D Instant Meshing software. The combination of these two technologies enables fast and high-detail 3D model creation in motion, providing 3D data, color, and texture of plants at an exceptional speed.Partner:<a href="https://www.wur.nl/en.htm" target="_blank">Wageningen University &amp; Research</a>Challenge:Wageningen University &amp; Research has a fully automated greenhouse where they screen large amounts of plants for shape and color characteristics. For this, they developed MARVIN Gen2 – a high-throughput plant phenotyping device that generates 3D models of plants and accurately determines the size and shape of their leaves and stems plus the overall architecture in milliseconds.&nbsp;Until recently, they used a machine vision solution that could only scan certain types of plants. To solve this challenge, they decided to use Photoneo MotionCam-3D Color, which can provide 3D models in higher resolution and with color information.Solution:<a href="https://www.photoneo.com/motioncam-3d/" target="_blank">MotionCam-3D Color</a> + <a href="https://www.photoneo.com/3d-meshing/" target="_blank">3D Instant Meshing</a>The solution uses multiple MotionCam-3Ds attached to a robotic arm, which can rotate 360 degrees around a plant. The cameras can also move up/down and be angled in different directions. This enables our partner to scan both small plants, such as young cabbage plants, as well as taller, flowering orchid plants.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA3NDAxMDA4OTU5LU9yY2hpZHMucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib">The solution uses MotionCam-3D model S to capture as many details of small plants as possible. In contrast to a 3D scanner, which constantly needs to stop to take 3D scans, MotionCam-3D can slowly rotate around the plant at a constant speed, which saves time.The key part of the solution is the construction of 3D models based on multi-angle scans from multiple MotionCam-3Ds. Photoneo 3D Instant Meshing software enables fast, high-detail 3D model creation in motion with texture and color.3D Instant Meshing is part of Photoneo 3D Meshing solution. It brings a big shift to 3D model&nbsp;creation as it enables users to create 3D models from a continuous stream of 3D scans taken&nbsp;by MotionCam-3D Color.The flexibility of the MARVIN system makes it easy to set it up and recalibrate. All plant species are different, which requires different camera angles to create a good 3D model. The setup makes it possible to scan both small as well as big plants.Discussion:Higher quality 3D models enable users to extract more accurate information from the models. This enables the tracking of the growth of plants over time. It provides deeper insights and thorough understanding of plant development over time, which will result in a boost in data-driven plant science.Note: This application has been developed for greenhouse use, where the effects of wind and sun are minimal.Would you like to discuss your use case with Photoneo? <a href="https://www.photoneo.com/contact-us/?utm_source=Wevolver&utm_medium=Case%20study&utm_campaign=Unique%203D%20vision%20technology%20for%20high-throughput%20plant%20phenotyping" target="_blank" rel="noopener noreferrer">Contact them here</a>.

High-throughput plant phenotyping with novel 3D vision

Plant phenotyping has reached a new level! Wageningen University & Research developed a novel technology to determine the size, shape, color, and overall architecture of plants in milliseconds, using Photoneo MotionCam-3D & 3D Instant Meshing SW.

Unique 3D vision technology for high-throughput plant phenotyping

This article was discussed in our <a href="https://www.wevolver.com/profile/the.next.byte" 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/64719573-41d7-4a7d-94ae-310d64fccf69?dark=false" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true" data-gtm-yt-inspected-10="true"></iframe> The full article will continue below.<hr><a href="https://dysonfarming.com" target="_blank" rel="noopener noreferrer">Dyson</a>, a brand synonymous with innovation in vacuum cleaners, hairdryers, and robotics, has embarked on an ambitious journey into agriculture, transforming it with the same engineering excellence that characterizes their consumer products. Over a decade ago, Dyson began acquiring farms across the UK, now totaling 36,000 acres in Lincolnshire, Oxfordshire, Gloucestershire, and Somerset. This venture is far from a side project; it's an integration of high technology and sustainable practices aimed at <a href="https://dysonfarming.com/why-farming/" target="_blank" rel="noopener noreferrer">redefining farming</a>.At the heart of Dyson's farming initiative is a commitment to agricultural improvement and environmental stewardship. The company has made significant strides in enhancing farm operations, including optimizing water management and soil health through drainage and maintenance efforts. A notable aspect of their approach is the <a href="https://www.fwi.co.uk/regenerative-agriculture/how-a-large-scale-regen-system-is-working-at-dyson-farming" target="_blank" rel="noopener noreferrer">dedication to biodiversity</a>, with around 4,000 acres set aside for natural habitats, underlining a holistic vision that marries conventional farming with sustainability.Dyson's foray into agriculture is driven by a vision to regenerate the soil, improve land management, and advance sustainable farming. The initiative employs a regenerative farming model, incorporating livestock to improve soil quality and thereby produce higher-quality food. This model is not just about farming efficiency but also about embracing technology and innovation to achieve sustainability and self-sufficiency.A standout feature of Dyson's approach is the use of an anaerobic digester, which converts crops into gas to generate electricity, supporting around 10,000 homes. This <a href="https://dysonfarming.com/renewable-energy/" target="_blank" rel="noopener noreferrer" id="isPasted">circular farming model</a> emphasizes the reuse of waste products, with digestate from the process used as a natural fertilizer, showcasing a sustainable loop that benefits both the farm and the surrounding environment. Furthermore, they ensure that no energy is wasted either, with excess heat from the process being used to keep the greenhouse warm for strawberry cultivation.Dyson has also innovated in crop cultivation, using technology like ultraviolet light and robotics to grow strawberries in a new 15-acre glasshouse in Carrington, Lincolnshire. This glasshouse not only advances sustainable farming practices but also extends the British strawberry growing season, reducing the need for imports and the associated food miles.The impacts of Dyson's farming initiative are manifold. By enhancing biodiversity, improving soil health, and employing circular farming practices, Dyson is not only producing better-tasting food but also contributing to environmental conservation. Their use of technology and sustainable practices in farming points towards a future where agriculture is not only about food production but also about ecological balance and resource efficiency.<iframe width="640" height="360" src="https://www.youtube.com/embed/n0miKj4UOiA?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true" data-gtm-yt-inspected-10="true" id="435624312" title="Behind the scenes of Dyson Farming with James Dyson">&nbsp;</iframe>Dyson's journey into agriculture reflects a broader ambition to apply engineering and technological expertise to one of the oldest human endeavors, farming. By doing so, Dyson is reimagining what is possible in agriculture, making it a model for sustainable and technologically advanced farming practices worldwide.For a closer look at Dyson's innovative farming practices and their implications for sustainable agriculture, you can explore more through <a href="https://dysonfarming.com" target="_blank" rel="noopener noreferrer">Dyson Farming</a>'s official site.

How a Tech Giant is Redefining Farming with Innovation and Sustainability

Engineering the Fields: Dyson's Leap from Gadgets to Agriculture

DFKI will be presenting its strawberry-picking robot to the public for the first time in&nbsp;Hall 23a. A row of strawberry plants has been specially planted for the smart robot at the joint stand of the Kuratorium für Technik und Bauwesen in der Landwirtschaft e.V. (Board of Trustees for Technology and Construction in Agriculture). It is designed to be small, flexible and inexpensive, and to harvest fruit independently. The system is being developed as part of the RoLand (Robotic Systems in Agriculture) project, coordinated by the Robotics Innovation Centre (RIC) at DFKI Bremen.&nbsp; &nbsp; The concrete application scenario is strawberry harvesting in the open field, which poses an increasing challenge for fruit growers. Agricultural businesses, such as the Glantz strawberry farm associated with the project, are complaining about a decline in seasonal labour on the one hand and rising wages on the other, says DFKI project manager Dipl.-Ing. Heiner Peters: "This is where our robot comes in. It is designed to support and relieve the labourers during the harvest. If necessary, it can work in parallel or even be used at night." The system enables cost-effective automation in agriculture. The use of several robots is conceivable on larger fields.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1705298738122-1705298738122.png" style="width: 766px;" class="fr-fic fr-dib">The animations show how the strawberry picking robot should work in the end. Two arms pick a strawberry every three seconds. Animation: DFKI, Meltem Fischer<h3>AI recognises ripe fruit</h3>The technical components of the strawberry picking robot are a mobile platform, a fruit recognition system and a harvesting gripper. With the help of artificial intelligence (AI), the robot recognises which fruits are ripe enough to be picked. This AI method can potentially also be transferred to other types of fruit.The system will initially be on display at the Grüne Woche with just one gripper arm, with grippers on both sides planned for the long term. One of the challenges for the researchers is to enable the gripper arms to cleanly separate ripe strawberries from the stem without crushing them. These problems are currently being addressed in the project. Peters: "Our aim is to pick a strawberry with each gripper in six seconds by the end of the project, meaning one every three seconds in total. That is roughly equivalent to the picking performance of a human."RoLand is being funded by the Federal Ministry of Food and Agriculture with a total of 1.7 million euros over a period of three years (1.10.21 - 30.9.24). The Robotics Innovation Centre at DFKI is coordinating the project. The project partners are the Research and Transfer Centre (FTZ) of the Hamburg University of Applied Sciences (HAW), Othmerding Maschinenbau GmbH &amp; Co. KG and Glantz Erdbeerhof (associated).<hr>Further information:<a href="https://robotik.dfki-bremen.de/en/research/projects/roland" target="_blank" rel="noreferrer">https://robotik.dfki-bremen.de/en/research/projects/roland</a>Venue: Hall 23a, special exhibition hall of the BMEL - Robots in AgricultureBooth: Kuratorium für Technik und Bauwesen in der Landwirtschaft e.V. (KTBL)

The strawberry-picking robot that DFKI is currently developing and is now presenting to the public for the first time is designed to be small, flexible and inexpensive. 

The German Research Center for Artificial Intelligence will be presenting new technologies for agriculture in three exhibit halls at the International Grüne Woche, which will take place in Berlin from 19 to 28 January 2024.

DFKI presents strawberry picking robot and AI ecosystem

The work in the greenhouse at Beerstecher AG in Hinwil is demanding. With humidity levels of 80 percent and temperatures of up to 35 degrees Celsius, those working in it very soon find themselves exhausted. The family business in Hinwil is consequently faced with a challenge when finding and retaining suitable labour for its vegetable harvests.<iframe width="640" height="360" src="https://www.youtube.com/embed/M_W38gdWgiI?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>Video: ETH Zurich / Nicole DavidsonThe picking robot from ETH spin-off Floating Robotics addresses these challenges. It automates crucial tasks such as defoliating, harvesting and boxing vegetables. “The robot primarily takes over strenuous and repetitive activities, allowing our employees to focus on more demanding tasks that require a creative and critical mindset," explains Bianca Curcio, who is responsible for production management in the Beerstecher greenhouse and is an ETH Zurich alumna.Although the robot is still in the pilot phase, Curcio anticipates it will play a permanent role in Beerstecher AG’s production process.The robot was developed by engineers and students from the Robotic Systems Lab (RSL) at ETH Zurich. Under the leadership of Salman Faraji, they established the spin-off Floating Robotics in 2023 with the aim of bringing the technology behind the picking robot to the market.Equipped with an integrated camera, the robot monitors the crops, and with the assistance of its built-in computer can recognise different plants and objects. Its robotic arm is activated to perform specific tasks, such as de-leafing or harvesting.

Working in a greenhouse is both strenuous and time-​consuming. The picking robot from ETH spin-​off Floating Robotics takes on particularly repetitive tasks, thereby alleviating the strain on human pickers. It is currently undergoing testing at Beerstecher AG in Hinwil.

A picking robot for the greenhouse

In this episode, we talk about how researchers from the Technical University of Denmark are tackling the issue of monoculture farming by utilizing robotics and next-gen image analysis.

Podcast: Robot Farmers Bring Back Biodiversity

<a href="https://www.wevolver.com/article/the-rock-engineering-challenge" target="_blank">The ROCK Engineering Challenge</a> invited engineers, entrepreneurs, inventors, and developers to submit an idea for a part, product, or system that took advantage of the <a href="https://www.wevolver.com/specs/radxa-x-okdo-rock-4c" target="_blank">ROCK single-board computers</a>. The challenge received a significant number of submissions from across the globe, impressing the judging panel with cutting-edge applications of single-board computers. In a new series, we are speaking with entrants from the challenge to learn more about their innovative ideas. In our latest interview, we spoke to Urban Kenda who has been working on a robotic farming project with fellow students from the University of Maribor in Slovenia.Wevolver writer, Lori Baldwin, spoke with Urban about the collaborative nature of the project and how SBCs are enabling near, real-time&nbsp;detection and localization.Lori Baldwin:&nbsp;Can you start by telling us about yourself and the project you're working on?Urban Kenda:&nbsp;My name is Urban, and I come from Maribor, Slovenia, where I attended the University of Maribor. I've been part of a farm-based project, a team working on a robot for the past four years. I've been leading the team, but I'm gradually transitioning to a new project as I've now completed my Masters.&nbsp;The farm-based robot project involves students from various courses, including engineering, programming, and agriculture. This diverse team allows us to address problems more effectively. The project began in 2008 when the current professor, who is now our mentor, was a student working on it. Over the years, the robot has undergone several updates, with each iteration introducing new features and improvements. The robot has two main objectives: to compete in field robot events and to make farming more efficient by automating manual tasks. This year, our focus was on automating raspberry picking due to the challenges involved in harvesting raspberries without damaging them.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzAxOTc5Mzk4NTMwLXJvYm90IDIgc21hbGwuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 300px;" class="fr-fic fr-dib">The robot project.Lori Baldwin:&nbsp;What was your role in the project?Urban Kenda: My primary role was focused on the detection and localization of raspberries. I also served as the team captain.Lori Baldwin:&nbsp;So, you applied for the OKdo competition with your robot; how have you incorporated SBCs?&nbsp;Urban Kenda: We've integrated SBCs into the robot, especially for raspberry detection and localization. To detect raspberries, we use an algorithm that employs neural networks, requiring substantial computational power. Additionally, we need to transform 2D camera images into 3D point clouds, which also demands computing power. However, since we aim to keep everything on our robot, we needed small, robust, and powerful SBCs, which served our needs well.Lori Baldwin:&nbsp;What are some of the benefits you see in the ROCK series of SBCs?Urban Kenda: The team is in need of a powerful computing device, such as the <a href="https://www.okdo.com/c/rock-shop/rock-sbc/?utm_source=wevolver&utm_campaign=rock&utm_medium=affiliates&utm_content=rock_challenge_robotics_agriculture" target="_blank" rel="noopener noreferrer">ROCK 5B 16GB,</a> to support their current work and future research. This device will be utilized to process data from various sensors and calculate the best path for the autonomous field robot. Furthermore, the team plans to use it for their upcoming research on using a YOLO neural network to detect raspberries and a robotic arm with an original origami gripper design to pick them. In summary, the ROCK 5B 16GB will greatly enhance the team's ability to perform their current and future research. &nbsp;<iframe id="639e88944155b50008d4cdf8" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/okdo-x-radxa-rock-5-model-b?iframe=true" frameborder="0" scrolling="no" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;</iframe>The main advantage of using SBCs was that they made the entire system faster. While it's not real-time detection, it's sufficiently fast for our robot, which moves at a slow pace. In comparison, using traditional PCs for detection led to much slower processing, with one detection occurring every five seconds. So speed and efficiency were the primary advantages.Lori Baldwin: How long did it take to have a working system?Urban Kenda: The development process had its ups and downs. We received the <a href="https://www.okdo.com/c/rock-shop/rock-sbc/?utm_source=wevolver&utm_campaign=rock&utm_medium=affiliates&utm_content=rock_challenge_robotics_agriculture" target="_blank" rel="noopener noreferrer">ROCK SBC </a>in March or April, and by June, we had tested the system and considered it functional. However, there was ongoing fine-tuning, optimization, and addressing minor issues, which is typical in such projects. So, the most time-consuming part was the continuous refinement and improvement of the system.Lori Baldwin: And have you succeeded in developing a raspberry-picking robot?Urban Kenda:&nbsp;To be honest, we haven't fully succeeded in developing a robot that can pick raspberries. We've made progress in different sections, and each part has been successful in its own right. However, integrating all these components into a functional robot has proven to be a more significant challenge, taking an additional year or two. It's more of a proof of concept at this stage.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzAxOTc5NDQ4NTg5LXJvYm90IDEgc21hbGwuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 300px;" class="fr-fic fr-dib">The team is made up of engineering, programming, and agriculture students. Lori Baldwin:&nbsp;Let's talk about the primary challenge the robot was built to address. Can you tell us more about it?Urban Kenda: Certainly. Our robot was designed for the Field Robot Event competition, where it faces several tasks. The first two tasks involve row navigation in a field of corn, requiring the robot to navigate the rows and handle obstacles. The third and fourth tasks involve camera-based detection, where our SBCs were crucial. This year, we had to detect objects like humans and deer and take appropriate actions. The fifth task, known as "freestyle," allows teams to work on farm-related ideas. This year, our focus was on raspberry picking, though we couldn't compete due to incomplete development.Lori Baldwin:&nbsp;I hope you can compete in the future. Can you also tell us about the challenge related to raspberry picking?Urban Kenda:&nbsp;Yes, of course. Raspberry picking involves several stages, and we divided it into three main parts. First is raspberry detection and localization, which was my area of focus. We used two types of sensors, an RGB camera and a LiDAR sensor to detect raspberries in 3D space. The LiDAR provided precise point cloud data. For robot arm control, we initially used a 3D printed arm but later switched to an industrial arm. We faced challenges in planning the arm's approach to raspberries. Finally, we developed a soft gripper inspired by Japanese origami, which allows for delicate and damage-free picking. This approach showed promise and offered an innovative solution to raspberry harvesting.Lori Baldwin: Outside of the competition, how can this technology benefit the agricultural sector?Urban Kenda: Beyond the competition, our robot has the potential to automate and reduce the manual labor required in farming. It offers the advantage of working continuously and can handle tasks that are physically demanding for human farmers. However, we've encountered resistance from traditional farmers who prefer established methods. Younger farmers tend to understand the benefits of automation and are more open to these technologies.Lori Baldwin: Have you received any feedback from farmers regarding the raspberry picking robot?Urban Kenda: While testing, we received feedback from farmers, and while they acknowledged the potential of our technology, they expressed concern about the pace of development. Farmers are understandably eager for end products and often reluctant to wait for technology to mature. However, the agriculture sector is gradually evolving, and younger farmers tend to be more receptive to adopting such technologies.Lori Baldwin: What initially sparked your interest in agricultural robotics?Urban Kenda:&nbsp;I became interested in agricultural robotics because I noticed that many industries, like automotive and manufacturing, had advanced significantly with the use of robotics. However, the field of agriculture seemed to lag behind. I saw an opportunity to bring technological innovation to this sector, and I find it both fun and challenging to work in this domain. It's a dynamic field with unique problems to solve.Lori Baldwin:&nbsp;How do you see SBCs playing a role in the future of agricultural robotics, and how can they be integrated further?Urban Kenda:&nbsp;I believe that in the future, agricultural robotics will benefit from a more decentralized approach, with smaller and more diversified single-board computers (SBCs) handling specific tasks. Instead of relying on a central computer, having SBCs with their own functions can lead to a more efficient and adaptable system. Each component of a farm can have its own SBC, such as a sprayer, a tractor, or a robot, making the entire system smarter and more agile.<a href="https://www.wevolver.com/article/precision-agriculture-with-single-board-comoputers" target="_blank">Read more about how SBC’s are enabling precision agriculture here.</a>

In response to the OKDo Engineering Challenge provocation, a team from the University of Maribor submitted a proposal to use the ROCK 5B in their raspberry detection and localization robot. 


OKdo ROCK Challenge: Interview with Urban Kenda. Precision robotic farming

This article was discussed in our <a href="https://www.wevolver.com/profile/the.next.byte" 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/c8f44e2e-59a9-4392-8f63-049c5c1029d1?dark=false" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> The full article will continue below.<hr><section id="isPasted">When Lazaros Nalpantidis sees a field, he imagines a future where a fleet of small robots chugs along, tending and caring for the crops on their own. Each machine has its own task—they sow, remove weeds, check for pests, water, spray pesticides and harvest. And the fields look different. There are no endless rows of wheat, barley, and corn, but instead many different crops—and the surroundings are buzzing with life.<h2>Shaped after machines</h2>If we want to improve biodiversity, we must change our agriculture. In Denmark, agriculture takes up over 60% of our land and the vast majority of the fields are monoculture, where a single crop dominates large areas. This creates bad conditions for biodiversity. But what if robots could change that?"We have shaped the environment to our agricultural machines. But with robotic technology, we can shape the machines to the environment," says Lazaros Nalpantidis.He is a professor at DTU Electro and is heading the project SAVA (Safe Autonomous Vehicles for Agriculture), which will develop safe agricultural robots that can work autonomously in much smaller areas than large agricultural machines. That can create fertile ground for a paradigm shift in agriculture and bring an end to monoculture while still maintaining efficiency and yield.<h2>Monoculture is bad news for biodiversity</h2>Before industrialization, it was common for farmers to grow several different crops on the same field. But as machines took over manual labour, it became more widespread to grow the same crop on large areas, as it made it easier to plough, fertilize and harvest using large machines."Back in the day, it was necessary to have a versatile farm with crop diversity to meet local needs, but after World War II the specialization of agriculture began to take hold. That made economies of scale and monoculture possible," says Ane Kirstine Aare. &nbsp;She’s assistant professor at the Department of People and Technology at RUC and has done research on transition towards more sustainable agriculture practices such as co-cultivation, where multiple crops are grown on the same field.Agriculture became more efficient, but monoculture is bad news for biodiversity. In nature, there are many different plants that bloom at different times of the year and a diverse cover of trees, shrubs, grass and herbs that create habitats for a number of animal species and all that disappears when the fields are uniform.At the same time, it also increases the risk that the entire field will be affected by pests and diseases and thus the need for using pesticides also increases, which is hurting biodiversity."The problem is that we’ve developed a food system that has been shaped to fit monocultural practices. Most involved parties in the food system have adapted to this practice, so it’s difficult to change course," says Ane Kirstine Aare.The Food and Agriculture Organization (FAO) of the UN has concluded in a report that monoculture in agriculture leads to less plant diversity and thus fewer ecosystem services. There are fewer pollinators like bees, pests have fewer natural enemies, there are fewer microorganisms in the soil and fewer wild species of crops. The FAO points out that one of the solutions is technology that can have a positive effect on biodiversity - and this is where robots come into play.<h2>All sensors on the table</h2>Robotic technology is slowly making its way into agriculture – there are already robots that can remove weeds (including the <a rel="noopener noreferrer" href="https://www.dtu.dk/english/news/all-news/nyhed?id=783c65fd-3cc1-448f-afbf-37a06860b2b0" target="_blank">Galirumi robot</a> where DTU was involved), spray with pesticide, and harvest certain crops. The development is making rapid headway, but there are still very few agricultural robots on the market. According to Statistics Denmark, only 1% of Danish farms use self-driving machines or robotic technology, and the technology has not yet matured enough for the robots to run fully autonomously, so it’s mandatory that a person supervises them."If the farmer has to stay with the robot, you’re not gaining much from it," says Lazaros Nalpantidis.The problem is that the robots are still not capable of handling unforeseen obstacles such as people, animals, and rocks, but the SAVA project aims to solve that. Lazaros Nalpantidis and his colleagues will test a range of new sensor technologies that will increase safety so that the robots can be fully unleashed in the fields."We have to put all the toys on the table and see if it opens up some new possibilities," says Lazaros Nalpantidis.</section><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzAxODk3NjE3MjY0LUxhbmRicnVnc3JvYm90dGVyLUFHQ08uanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib">The SAVA project will test safety systems in different areas such as grass fields, parks, fruit orchards, and vineyards. This will happen in collaboration with various companies creating agricultural machines. Photo: AGCO<h2 id="isPasted">More biological cameras</h2>Today, robots and self-driving machines mainly use cameras and Lidar, a laser technology that can measure distances, but the SAVA project will also test infrared cameras and thermal cameras that can better detect animals and people in the surroundings.In addition, the project will test so-called neuromorphic cameras (also known as event-based cameras), which function more like our eyes and only register when something changes in the image, rather than constantly registering everything in the image. Whereas the best DSLR cameras can capture around 120 frames per second, a neuromorphic camera can take up to 1,000,000 frames per second. Lazaros Nalpantidis hopes that this kind of technology can help the robots react significantly faster to unforeseen obstacles and come to a stop if, for instance, an animal or a person suddenly runs in front of them (in Denmark, approx. 20,000 deer fawns are killed by agricultural machines every year, <a rel="noopener noreferrer" href="https://www.jaegerforbundet.dk/om-dj/dj-medier/nyhedsarkiv/2017/op-til-20-000-radyrlam-draebes-hvert-ar-i-danmark/" target="_blank">according to Denmark's Hunters' Association</a>).<h2>Agricultural paradigm shift</h2>Robots can fundamentally change the appearance of our fields. As agricultural robots tend to be significantly smaller than traditional agricultural machines, they can be adapted to a smaller area without sacrificing efficiency.This means that you can plant narrow strips of several different crops next to each other, as the robots can sow, water, spray, and harvest in a narrow area.Studies show that if you grow several different crops in an area, it’s better for biodiversity, as it provides habitats for more species, while there is less need for fertilizing and spraying with pesticides. If a crop is affected by pests or disease, it is limited to a single strip rather than an entire field.In the long term, the robots can help change the entire landscape. In many places, the fields are moulded to the needs of large agricultural machines – streams are straightened out, low-lying areas drained, and hills leveled – but small robots will be able to follow nature’s shapes to a greater extent. Thus, more habitats for animals and plants can be preserved.<h2>Robots within ten years</h2>To get to that vision, the robots must first prove that they can operate safely and autonomously and not be of danger to their surroundings."Unfortunately, the robotic technology is not quite mature enough yet," says Lazaros Nalpantidis.He acknowledges that robots are only a small part of the solution to the biodiversity crisis – and there will still be a need for large agricultural machines – but he hopes that robots can help make changes in parts of the world where industrial agriculture has not yet gained traction.Ane Kirstine Aare also sees potential in robots."Some experience limitations with current agricultural machines when they wish to practice co-cultivation, so it’s really exciting to see what the robots can contribute. If robots are developed thoughtfully they may pave the way for a different kind of agriculture with more flexibility and local adaptation," she says.To Lazaros Nalpantidis, his vision of robots chugging around in the fields might become reality within ten years."I am quite optimistic because there is momentum in this area and it is clear that we cannot continue with the current agricultural production. It’s just not sustainable," says Lazaros Nalpantidis."But in ten years’ time, we’ll have far more futuristic machines in agriculture."

Small, autonomous robots will make it possible to grow several different crops on the same field and that can help improve biodiversity. Illustration: Mark Airs.

In Denmark, agriculture makes up almost 2/3 of our land and oftentimes one crop is grown in huge areas. That's hurting the biodiversity, but agricultural robots can help do away with monoculture, and a new DTU project will pave the way for that future.

Agricultural robots can help improve biodiversity

Precision agriculture uses technology and automation to optimize crop production, reduce waste, and promote sustainability. It enables farms to make informed decisions based on real-time data and historical trends, maximizing crop quality while minimizing resource usage and environmental impact. As technological advances, the precision agriculture scope expands. The integration of SBCs enables the management of various sensors and devices critical to precision farming, but also makes it possible to handle data processing for smart agriculture and farming automation.This article explores how SBCs can be used to improve precision agriculture applications, integrating automation and autonomous operational processes.<h2 dir="ltr">Benefits and Challenges of SBCs in Precision Agriculture</h2>Due to their flexibility and processing capabilities, SBCs can provide several aspects of precision agriculture applications:<ul><li dir="ltr">Increased Efficiency: SBCs optimize environmental conditions, enabling the integration of IoT applications and AI for efficient farming.</li><li dir="ltr">Control and Automation: SBCs can manage various aspects of indoor farming systems, from climate control to nutrient management.</li><li dir="ltr">Cost-effectiveness: SBCs are cost-effective, with compact sizes and low power consumption making them increasingly popular for battery-based applications.</li></ul>However, depending on the the location and application, concerns may rise related to communication and data security:<ul><li dir="ltr">Real-time Challenges: Real-time farming relies on reliable networks and low latency, which can be challenging to achieve in remote rural areas [3].</li><li dir="ltr">Security Concerns: Protecting agricultural data and automated systems from cyber threats is a growing concern, especially as the industry becomes more connected.</li></ul><h2 dir="ltr">SBCs in Action</h2><h3 dir="ltr">Data collection</h3>Data play a central role in decision-making in precision agriculture. Sensors are placed strategically in fields and on equipment to monitor parameters such as temperature, humidity, soil moisture, and nutrient levels. The table below lists sensors that can be used in precision agriculture applications.<div dir="ltr" align="left" id="isPasted"><table><tbody><tr><td><h2>Purpose</h2></td><td><h2>Application</h2></td><td><h2>Sensors examples</h2></td><td><h2>Sensor type</h2></td></tr><tr><td rowspan="2">Management of Crop</td><td>Growth</td><td>Parrot Sequoia</td><td>Multispectral</td></tr><tr><td>Pest detection</td><td>FLIR Blackfly23S6C</td><td>Cameras</td></tr><tr><td rowspan="3">Substrate monitoring</td><td rowspan="2">Moisture and temperature of soil&nbsp;</td><td>DS18B20</td><td>Digital temperature&nbsp;</td></tr><tr><td>VH400</td><td>Soil moisture&nbsp;</td></tr><tr><td>Chemical elements such as nitrate, nitrogen</td><td>SEN0244</td><td>Total dissolved solids (TDS)&nbsp;</td></tr><tr><td rowspan="13">Environment monitoring</td><td rowspan="2">Humidity and temperature of air</td><td>DHT11</td><td>Temperature and humidity</td></tr><tr><td>DHT22</td><td>Temperature and humidity</td></tr><tr><td>Solar radiation</td><td>SQ-110</td><td>Solar radiation</td></tr><tr><td rowspan="2">CO2&nbsp;concentration</td><td>MG-811</td><td>CO2&nbsp;</td></tr><tr><td>MQ135</td><td>Measures the level of NH3, NOx, alcohol, Benzene, smoke, and CO2 in air.</td></tr><tr><td rowspan="3">Rain</td><td>YF-S402</td><td>Water flow</td></tr><tr><td>YL-83</td><td>Water detector</td></tr><tr><td>SE-WS700D</td><td>Weeding control</td></tr><tr><td rowspan="2">Wind speed and direction</td><td>WS-3000</td><td>Ambient weather</td></tr><tr><td>SEN08942</td><td>Wind speed, wind direction, and rainfall</td></tr><tr><td>Atmospheric pressure</td><td>MPL3115A2</td><td>Piezoresistive absolute pressure</td></tr><tr><td rowspan="2">Luminosity</td><td>BH1750</td><td>&nbsp;Digital Light sensor</td></tr><tr><td>TSL2561</td><td>Digital Luminosity, Lux, Light</td></tr></tbody></table></div>Table 1: Sensors and their application in farming.However, acquiring the data is only part of the process. SBCs act as the central control unit for these sensors, enabling real-time data collection and analysis. Thus, there is the possibility of processing the data locally or performing the transmission to a cloud-based platform. As new SBCs provide more processing power and are ready to execute machine learning, farmers rely less on high-speed data transmission to analyze data in real-time by cloud solutions. As a result, farmers can quickly respond to changing crop conditions, making precise adjustments to farming processes, such as irrigation.<h3 dir="ltr">Agricultural systems automation</h3>SBCs can also play a crucial role in automating processes in precision agriculture. By enabling autonomous vehicles and robots, SBCs allow farmers to equip them with sensors and cameras that collect data on crop growth and environmental conditions. For instance, autonomous tractors can be used to plant and harvest crops. At the same time, drones can monitor crop health, detect pests and diseases, and even spray pesticides on the affected areas. In addition, SBCs can also automate irrigation systems, fertilizer application, and other aspects of crop management, reducing the manual labor need and improving efficiency [3,4,5].These automation applications are economically viable for medium and large farms, and even small farms can benefit from automation. Thanks to the computing power of SBCs, a single SBC can execute several tasks, making it possible for small farmers to take advantage of automation benefits. Automating fertilizer and irrigation management reduces costs and errors, resulting in timely actions and minimal crop losses, for example.<h3 dir="ltr">Agricultural data analysis</h3>SBCs run on operating systems like Linux, providing access to a vast library of advanced open-source software. They can handle substantial volumes of data from multiple sensors in real time, supporting precision agriculture decision process. The data can be analyzed locally using big data analytics and machine learning algorithms, running the software analysis using the SBC's processing power. For example, machine learning algorithms can be used to analyze soil data and recommend the optimal amount of fertilizer to apply to each crop, or to predict the likelihood of a pest outbreak based on weather patterns and other environmental factors. As a result, advanced data analysis applications can run locally, providing farmers with insights.<h2 dir="ltr">Use case: SBCs for Irrigation</h2>Water is a crucial component of agriculture and is normally the first aspect approached by agriculture precision. In this section, you will find a case study using SBCs in an irrigation system.<h3 dir="ltr">Setting up IoT sensors</h3>First, it is necessary to set up the sensors and to cover broad crop field areas, it is required to use IoT devices with wireless transmission. One option is to use sensors like the DHT11 for temperature and humidity and FC-28 for soil moisture. They can be connected to ESP8266 boards to transfer the acquired data, which use Wi-Fi and MQTT to transfer the data.<h3 dir="ltr">Using SBCs for data management and automation</h3>Besides acquiring the data, it is necessary to have a server to receive and process it. SBC models like the ROCK 4 SE serve as data hubs. These SBC models are robust and versatile, featuring a high-performance Hexa-core Rockchip RK3399-T processor and 4GB 64bit LPDDR4 RAM. Furthermore, it is equipped with a Dual Arm Cortex-A72 CPU, Quad-core Cortex A53, and Arm Mali T860MP4 GPU. In addition, you can also create user-friendly interfaces for real-time monitoring using tools like <a href="https://nodered.org/" target="_blank">NodeRed</a> and <a href="https://www.influxdata.com/" target="_blank">InfluxDB</a>.The system can go beyond data collection and monitoring. The ROCK 4 SE's processing capabilities can automate irrigation based on the received data. For instance, if some regions of the field show soil moisture levels below a specified threshold, the system can trigger the irrigation pumps only for those zones if this possibility exists. As a result, energy and water usage would be optimized.<h3 dir="ltr">Future enhancements</h3>To further increase the project capabilities, you could integrate it into the cloud and add machine learning algorithms. The cloud integration would facilitate the system management access from anywhere. While the machine learning algorithms could improve the water and energy used based on the historical data.&nbsp;<iframe id="639e88944155b50008d4cdf8" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/okdo-x-radxa-rock-5-model-b?iframe=true" frameborder="0" scrolling="no"></iframe><h2 dir="ltr">Future Outlook in SBC-Powered Precision Agriculture</h2>The future of precision agriculture supported by SBCs is promising, with many innovations on the horizon. As SBCs increase the capability of handling artificial intelligence and machine learning algorithms, more advanced and complex data analysis can be made, providing farmers with increasingly precise insights into crop management. Regarding robotics and automation, new machines are expected to replace work in repetitive farming tasks, and drones equipped with SBCs are expected to provide more accurate crop monitoring, improving pest detection and disease prevention.&nbsp;Besides the conventional crop farms, SBCs can increase process automation and optimization of vertical farming, helpint it to gain more traction, controlling indoor luminosity, for example. Moreover, combining new IoT and sensor devices with SBC management can improve livestock farming, optimizing feed consumption and reducing disease incidence by closely monitoring each animal and requiring treatment as soon as an anomaly is detected.<h2 dir="ltr">Conclusion</h2>SBCs are essential supporting devices of modern precision agriculture. Their ability to process and analyze data in real-time and their role in automation make them indispensable tools for farmers striving for sustainable and efficient crop production. As the agricultural sector evolves, SBCs will gain traction, boosting new precision farming applications.<h2 dir="ltr">The ROCK series powering precision Agriculture</h2><div data-message-author-role="assistant" data-message-id="8f00c95e-d481-406f-9796-e1d2ff18e0a9">OKdo's smart agriculture solutions are at the forefront of modernizing farming practices using IoT technology. A key component of their smart farming technology is the <a href="https://www.okdo.com/smart-agriculture/?utm_source=wevolver&utm_campaign=rock&utm_medium=affiliates&utm_content=sbcs_precision_agriculture" target="_blank" rel="noopener noreferrer">ROCK 4 Model C+ 4GB SBC</a>. This powerful <a href="https://www.okdo.com/p/okdo-rock-4-model-se-4gb-single-board-computer-rockchip-rk3399-t-arm-cortex-a72-cortex-a53/?utm_source=wevolver&utm_campaign=rock&utm_medium=affiliates&utm_content=sbcs_precision_agriculture" target="_blank" rel="noopener noreferrer">single board computer&nbsp;</a>is equipped with a Rockchip RK3399T SoC, making it ideal for smart agriculture applications. It features 4GB 64bit RAM, an eMMC socket, integrated fan control, and dual microHDMI ports supporting up to 4Kp60 resolution. Additionally, it includes Bluetooth 5.0, Gigabit Ethernet, and wireless LAN capabilities. This hardware is specifically designed to support the demands of smart agriculture, providing the processing power and connectivity required for efficient and sustainable farming operations.&nbsp;<a href="https://www.okdo.com/?utm_source=wevolver&utm_campaign=rock&utm_medium=affiliates&utm_content=sbcs_precision_agriculture" target="_blank" rel="noopener noreferrer">Learn more here.</a></div><h2 dir="ltr">References</h2>[1] McFadden, Jonathan, Eric Njuki, and Terry Griffin. "Precision Agriculture in the Digital Era: Recent Adoption on US Farms." (2023).[2] Tycoonstory. “<a href="https://www.tycoonstory.com/iot-in-precision-agriculture-advancements-and-benefits-for-modern-farming/" target="_blank">What is IoT Precision Agriculture and How is it Different from Traditional Agriculture?</a>“[3] AgriTech Tomorrow “5 Challenges For Precision Agriculture To Face”. 2020[4] Abu, N. S., et al. "Internet of things applications in precision agriculture: A review." Journal of Robotics and Control (JRC) 3.3 (2022): 338-347.[5] Raj, E.F.I., Appadurai, M., Athiappan, K. (2021). Precision Farming in Modern Agriculture. In: Choudhury, A., Biswas, A., Singh, T.P., Ghosh, S.K. (eds) Smart Agriculture Automation Using Advanced Technologies. Transactions on Computer Systems and Networks. Springer, Singapore.&nbsp;[6] Mathe, Sudha Ellison, et al. "A survey of agriculture applications utilizing raspberry pi." 2022 International Conference on Innovative Trends in Information Technology (ICITIIT). IEEE, 2022.[7] Gsangaya, K. R., et al. "Portable, wireless, and effective internet of things-based sensors for precision agriculture." International Journal of Environmental Science and Technology 17 (2020): 3901-3916.[8] &nbsp;Sebastian. “<a href="https://admantium.medium.com/iot-sensor-project-esp8266-with-dht11-sensor-sends-data-to-mqtt-a0e7e101f095" target="_blank">IOT Sensor Project: ESP8266 with DHT11 Sensor sends Data to MQTT</a>”.[9] Jia, Weibing, and Zhengying Wei. "Raspberry Pi-Embedded Intelligent Control System for Irrigation and Fertilization Based on deep learning." Journal of Physics: Conference Series. Vol. 2504. No. 1. IOP Publishing, 2023.[10] askSensors. “<a href="https://www.instructables.com/How-to-Connect-Soil-Moisture-Sensor-and-ESP8266-to/" target="_blank">How to Connect Soil Moisture Sensor and ESP8266 to the AskSensors IoT Cloud</a>”.

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