For a Multi-Stakeholder Discussion on 5G in Agriculture and Rural Area Development

Saverio Romeo
March 11, 2020

 

In agriculture, 5G is seen as the enabler for empowering the smart farming vision taking it towards autonomous and predictive farming. That view, very technological-centric, has shadowed other considerations on agriculture and rural areas creating a foggy view on 5G by rural and agricultural communities. This article wants to explore this initial journey of 5G in agriculture and rural areas and highlight future directions.

A Brief Overview of Smart Farming and Smart Rural Areas

The common belief sees agriculture as an old sector, not highly technological and based on traditional practices. The reality is totally the opposite. Agriculture has embraced digital technologies in a profound way proving exceptional innovation capabilities. The term “precision agriculture” was strongly embraced by the agricultural sector a long time ago, when terms like “ubiquitous computing”, “pervasive computing” and “Internet of Things” were ideas of technological pioneers and visionaries. Agricultural machinery manufacturers such as John Deere, CNH-Global, CLAAS, AGCO, and others have been working on precision agriculture for some time. Their combines and agriculture vehicles have used positioning technologies and sensors for gathering data about the fields and the crops. They move the data to information management systems, also known as farm management information systems, in order to optimize agricultural operations. This era of “precision agriculture” was based on M2M connections, quite often based on satellite technology. As technologies have evolved and the Internet of Things has become more mainstream, agriculture has embraced the IoT vision driving the rise of “smart farming” or “smart agriculture”. In small-sized fields, such as vineyards, mesh-networks of sensors monitor the grapes, send data to farm management information systems, and actions are taken to optimize production and increase quality. Similarly, it is happening for livestock and for fish farmers. Farming, in all its sizes and forms, is embracing the IoT vision in which the farm is a space, a sensed space, where data is used – at the edge or on the cloud – for optimizing farming processes and creating new services.

The smart agriculture vision embraces all the phases of the farming value chain. In “A Case for Rural Broadband” published in April 2019, the United States Department of Agriculture offers a useful framework on how to look at farming activities and the impact of smart farming vision. The report highlights three main phases:

  • Planning. Using data for decision support in order to make better decisions about what to produce, when and how.
  • Production. Monitoring the farming cycle and optimizing, accordingly, the entire process.
  • Market Coordination. Creating access to new customers and market channels, through the understanding of customers’ preferences and tendencies.

The common element of the three phases is the data. Data is gathered from different sources. Those sources could be sensor-based, external data (for example, weather data), and IT system data. The data is then analyzed, and various decisions are taken. As shown in figure 1, smart farming is not an on-off project, but a cycle process.

Figure 1: The lifecycle of smart farming.Figure 1: The lifecycle of smart farming.

The objectives are then: enhanced the understanding of the farming process through data to lower the costs reducing inefficiencies and risks. In turn, that means better margins and better capacities to meet the markets and customers’ needs.

Several sources such as the EU funded Smart Akis Smart Farming Thematic Network (https://www.smart-akis.com/) project can show the positive impact of smart farming, but it is very difficult to quantify the overall impact of smart farming on the agricultural sector. There are some studies that have designed models for describing that. One of those has been done by the US Department of Agriculture as shown in figure 2.

Figure 2: Potential Annual Gross Benefit of Smart Farming .

Figure 2: Potential Annual Gross Benefit of Smart Farming1.

Figure 2 shows an extract of the analysis. The analysis looks at the different types of farming activities, different smart farming technology used and quantify the impact in revenue for the US agricultural sector.

The benefits are potentially very lucrative and very impactful, but smart farming does not come without challenges. Some of those are technological, directly deriving by the Internet of Things as conceptual roots of smart farming. There are then some important business and market ones.

The main technological challenges are:

  1. Smart farming, as all the IoT solution, is an integration of components: devices, connectivity forms, IoT platforms, farm management software. Selecting the right component and integrating them is not an easy exercise.
  2. Technology incompatibility exacerbates the previous points. Compatibility between hardware and software of different suppliers of sensors, data, and implementations is not always there.
  3. Securing smart farming solutions is essential to have data security and protect the entire solution. There are several guidelines and best practices that can help in pursuing that, but it requires the necessary skill sets and collaboration.
  4. The lack of wireless and wired connectivity in rural areas is a strong impediment for designing and deploying a smart farming solution.

The main non-technological challenges are:

  1. For most farmers, the investment in a smart farming solution is not affordable. The margins are too low for spending resources on innovation. That approach exacerbates if smart farming project return of investments becomes difficult to prove.
  2. There is a shortage of workforce and skills in agriculture. Agriculture does not strongly attract the younger generations. That delays the adoption of smart farming solutions.
  3. The debate on climate change is calling the agricultural sector to embrace sustainable ways of production. The response is not easy and immediate.

Addressing these challenges requires different actions and different tools. Emerging technologies are examples of those tools, but also an additional element of disruption. It is also important to highlight that those challenges can be better addressed if the convergence of technologies is considered. The convergence of the IoT with AI, blockchain, and 5G can solve some of those challenges and bring the smart farming vision to a different level of sophistication, towards the automated and predictive agriculture. 5G can play an important role. The next paragraph will try to explore that.

How 5G Can Support the Smart Farming Vision

Solving the “Rural Connectivity” problem: the lack of reliable connectivity in rural areas has been a historical hurdle for the development of telecommunications in rural areas and the use of digital technologies in agriculture. The issue of the “digital divide” as an unbalanced distribution of broadband connectivity between urban areas and peripheral areas has characterized telecommunications policy in the new centuries. But, the political objective “broadband for all” has not been fulfilled yet. Based on the Rural, Mountainous, Remote Areas and Smart Village EU Parliament Intergroup (www.smart-rural-intergroup.eu), 25% of the EU rural population does not have access to the Internet. But broadband connectivity is the building block of smart rural areas and smart farming. Continuing the analysis proposed in Figure 2, the US Department of Agriculture also argued that those benefits are possible only if broadband is wider available in the rural US. Figure 3 shows the benefits due to the presence of rural connectivity.

Figure 3: Potential Annual Gross Benefit of Smart Farming and the contribution of broadband1.

Figure 3: Potential Annual Gross Benefit of Smart Farming and the contribution of broadband1.

Unlike the move from 2G to 3G, which was completely city-centric, the move from 4G to 5G can be designed more uniformly giving the same priority to cities and rural areas. That can solve the “rural connectivity” problem and not recreating the digital divide between urban and rural areas. That would be a profound incentive to the economic development of rural areas, the adoption of smart farming practices, and driving innovation in agriculture.

Moving the Smart Farming Vision towards Automation and Prediction: 5G cannot only contribute to solving the “rural connectivity” problem, but it can enable a variety of applications in smart farming, from those which require a small amount of data to the data-rich ones. That is because 5G should not be considered simply as cellular ultra-broadband technology, but as a cellular connectivity framework as it is showed in Figure 4.

Figure 4: The 5G Technology Framework.Figure 4: The 5G Technology Framework.

The two areas of Massive MTC (Machine-type Communication) and the tactile Internet are particularly relevant for smart farming.  The Massive MTC can serve all those low-data, low-power, long-battery life applications such as specialty crop monitoring, precision livestock monitoring, irrigation systems monitor and similar. Those applications are currently served either via 2G – even if 2G is slowly sunsetting – LPWAN (Low Power Wide Area Network) solutions or other forms of mesh networks. Instead, the tactile internet will enable self-driving agriculture vehicles, various forms of robotics, from drones to strawberry picking robots. The Enhanced Mobile Broadband area will be also relevant particularly for video analytics on crops and livestock, but also for market coordination applications.

It is important to highlight that 5G is an important enabler of smart farming applications, but it is not the only one. The role of AI is important for the automation of the processes and for the adoption of a predictive approach to farming. Those require the convergence of IoT-5G-AI as the use of blockchain and DLT (Distributed Ledger Technologies) can enable quality tracking from the farm to the table, and therefore creating new approaches to the market coordination phase described in the first part of this article.

Driving innovation in rural areas and agriculture: in this intersection of emerging technologies (IoT, AI, 5G, DLT, and others), there is also a promising growth of innovative companies that try to bring the benefits of those technologies to farmers. In India, Trringo offers rental models and support services for farming equipment using the IoT. In France, Karnott offers software and hardware solutions to transform legacy agricultural systems into smart farming systems. In Italy, Agricolus and Agri Open Data offer a farm management system solution that brings together smart farming data, AI and blockchain. In the USA, Iron Ox offers a plant grow solutions completely based on robots. Taranis offers a platform that uses a combination of aerial and satellite imagery with AI tools for optimizing the farm management system. In the UK, Hectare Agritech has developed a blockchain-based farm trading platform; and Hands-Free Hectare is testing automated machines growing crops autonomously using 5G.  

Conclusions: The Need for a Multi-Stakeholder 5G Rural and Agriculture Strategy

This article has highlighted three important contributions that 5G can bring to smart rural areas and smart farming.

  1. The planning and deployment of 5G networks is an opportunity for solving the “rural connectivity” problem. 5G cannot solve that entirely but giving 5G a prominent role within a combination of connectivity forms (satellite, fixed, PLC, LPWAN, other wireless forms) for rural areas could be the answer to 20 years and more of lack of connectivity in rural areas.
  2. 5G should be a technology framework enabler for smart farming solutions. In convergence with other emerging technologies (AI, DLT, and others), 5G can bring smart farming to the era of autonomy and predictive and prescriptive maintenance.
  3. 5G can become the innovation enabler in agriculture because of fundamental blocks for exploring applications of emerging technologies in farming. That means driving the establishment of a new flow of agri-tech start-ups, but also expanding digital culture in rural areas.

However, this cannot be done through a push-down approach regarding 5G deployments. Among rural communities, there are doubts about the sustainability of 5G and its impact on the environment and the health of the communities at large. Additionally, the investment requires for 5G deployment can be misread if it does not come with a strong engagement with rural community stakeholders, who are expecting supports and investment for their farming activities. An exogenous push will not reach the results discussed and will not encounter the collaboration of the rural communities. Operators in charge of the 5G rollouts should not think of rural areas as urban areas. If in urban areas, the effect of 5G can be more evident to citizens, in rural areas this is not necessarily the truth. The deployment of 5G should be done in continuous collaboration with an informed rural community. Discussing 5G with communities is essential for making clarity on the value of 5G and on its impact on the environment and health.

5G for rural areas is a fascinating and complicated issue. It can have enormous benefits for rural communities and the agricultural sector. But that can fully happen if the rural communities are informed and strongly involved in the process. 5G deployment in rural areas is not an easy exercise and it should not treat in the same way done in cities. The smart farming industry, national and regional governments, and communities need to come together for designing a 5G Rural and Agriculture Strategy that can fully catch the benefits of 5G and its convergence with other emerging technologies.

 

1 https://www.usda.gov/sites/default/files/documents/case-for-rural-broadband.pdf


 

Saverio RomeoSaverio Romeo is an associate lecturer at Birkbeck College on emerging technologies (IoT, blockchain, and AI) and their impact on innovation and policy. He runs modules for postgraduates and undergraduates on emerging technologies and contribute to research activities on the impact of technologies in business and society. He also runs the Emerging Technology Observatory (ETO), a consultancy outlet working with different organizations (XSure, STL Partners, Augmented Reality Enterprise Alliance, IntentHQ, WoW, Technopolis Group, CSIL Milano, VAA, Club Demeter, IoT Analytics and IoTNow) on the use of emerging technologies such as blockchain, AI, immersive technologies, 5G and IoT. He was also Lead Expert for the EU Digital Cities Challenge Project supporting the city of L’Aquila in defining its digital transformation strategy.

 

 

 


 

Subscribe to the Newsletter

Join our free IoT Technical Community and receive our Newsletter.

Subscribe Now


Calendar of Events

2020 IEEE Virtual World Forum on Internet of Things (WFIoT2020)
2-16 June 2020
Virtual

IEEE International Conference on Omni-layer Intelligent Systems (COINS 2020)
27-29 July 2020
Barcelona, Spain

2020 IEEE International Conference on Internet of Things and Intelligence System (IoTaIS 2020)
3-5 November 2020
Bali, Indonesia

2020 IEEE Global Conference on Artificial Intelligence and Internet of Things (IEEE GCAIoT 2020)
12-15 December 2020
Dubai, UAE

IoT Vertical and Topical Summit on Tourism
TBA

See More Events


Call for Papers

IEEE Internet of Things Journal

Special Issue on Robustness and Efficiency in the Convergence of AI and IoT
Submission Deadline: 15 May 2020
Special Issue on Blockchain Enabled Edge Computing and Intelligence
Submission Deadline: 1 June 2020
Special Issue on AI‐driven IoT Data Monetization: A Transition From “Value Islands” To “Value Ecosystems”
Submission Deadline: 15 June 15, 2020
Special Issue on Industrial Security for Smart Cities
Submission Deadline: 1 July 2020
Special Issue on Age of Information and Data Semantics for Sensing, Communication and Control Co-Design in IoT”
Submission Deadline: 15 July 2020

See More IoTJ Call for Papers


Past Issues
March 2020
January 2020
November 2019
September 2019
July 2019
May 2019
March 2019
January 2019
November 2018
September 2018
July 2018
May 2018
March 2018
January 2018
November 2017
September 2017
July 2017
May 2017
March 2017
January 2017
November 2016
September 2016
July 2016
May 2016
March 2016
January 2016
November 2015
September 2015
July 2015
May 2015
March 2015
January 2015
November 2014
September 2014