Your browser is not supported. Please update it.

6 December 2022

Ericsson highlights impact of 5G agriculture on developing economies

Last week, Ericsson released the results of a study  on the economic prospects of 5G in the developing world. This identified significant potential economic growth driven by 5G, with 80% of that tied to midband spectrum deployments, and up to 90% linked to smart industry and smart agriculture services.

The report, commissioned from management consulting firm Analysys Mason, is titled ‘The future value of mobile in emerging markets’ and points to the potential for economic growth associated with 5G mobile network infrastructure deployments, from fixed wireless access (FWA) to freight and logistics, smart factories and agriculture.

Various 5G spectrum deployment models were considered and analyzed for their impact. Population distribution, existing infrastructure, and other governmental or national statistics were additionally considered to calculate the overall cost-benefit equation for the spectrum deployments. 5G spectrum deployment was considered on top of existing radio network infrastructure, alongside a bonus extension primarily in midband and low-band frequencies

While both midband and low-band 5G were assessed to bring economic benefits, 80% of 5G-driven economic growth was tied to the midband. In terms of the sectors studied and modelled, 85% to 90% of overall economic benefits were seen in the Smart Industry and Smart Rural clusters, as defined by the report.

The study was conducted for Bangladesh, Brazil, Chile, Columbia, Egypt, India, Indonesia, Malaysia, Mexico, Morocco, Nigeria, Pakistan, South Africa, Thailand and Turkey.

Accounting for up to 10% of national GDP in the assessed countries, agriculture was identified as one of the main potential drivers of economic growth, with an estimated increase of up to 1.8% in long-term GDP, alongside more difficult-to-monetize benefits such as reduced environmental damage from more efficient resource use.

The model estimated a $3bn-$8bn price tag for the baseline 5G deployment, and an additional 20%-35% investment for extended low- or midband coverage. The researchers found these costs to be dwarfed by the value of the long-term benefits, by factors of 3 to 7. Other benefits included between$1bn and $10bn in consumer surplus, with an additional 20%-30% from coverage extension deployments.

Agriculture is one of the many industries that stands to benefit from the integration of a new generation of wireless technologies. As with other sectors, productivity and efficiency improvements will mainly come, not from futuristic applications such as fully autonomous fleets of semi-sentient machines, but through an enhanced ability to collect, transport and process data and information across a farmer’s wholeecosystem.

‘Smart farming’, ‘precision agriculture’, ‘climate-smart farming’ and ‘advanced agriculture’ are some terms that denote this set of data- and insight-based farm management strategies and technologies, which aim to increase output, efficiency, and sustainability through the use of new technologies.

While a wide range of use cases have emerged and will continue to do so as technology advances, 5G and the IoT are currently the key enablers of advances in this market. Similar to Industry, 4.0, this agricultural revolution is driven in large part by the growing availability and increasing reliability of cellular connectivity. Combined with the growth of the IoT device market, for the first time ever, it is possible to harvest not just vegetables and fruit, but information on a large scale, in turn increasing efficiency and yields.

In contrast to other industries, manufacturing for example, agriculture is one of the few where mature technologies and products leveraging recent cellular advances already exist. IoT sensors and AI/ ML data analytics in particular are among the most mature and commercially viable advanced technologies available to farmers. Some of the most important use cases include soil and crop monitoring for pests, disease, and irrigation levels/ quality.

Fitting seamlessly into this scheme is the use of satellite and drone imagery for the creation of digital twin models of farming operations. An increasing number of management and analytics platforms allow the augmentation of the digital twin model with different types of soil, crop and weather data. AI/ ML then does the rest to improve forecasting and suggest more optimized land use.

Taken together, these IoT sensor-driven additions have the potential to greatly increase input resource efficiency. Input resources here mainly refer to water, pesticide, herbicide, seed and fertilizer use. Herbicides and pesticides, when used indiscriminately, as is currently often the case, have a serious adverse impact on the land, degrading its quality and causing health complications for humans.

Another important benefit is the ability to better manage land based on the sensor data gathered. Crops may be rotated based on sensor data monitoring soil quality and nutrient levels, rather than along one-size-fits-all static rotations. For example, particular crops can be suggested for planting, based on land quality and needs. Alternatively, given the havoc that climate change will wreak on local weather patterns and associated traditional farming techniques, these insights may help mitigate climate-related changes to the land.

Other use cases and room for technological improvements in agriculture exist, of course. This can refer to all sorts of 5G-enabled heavy machinery, sometimes even autonomous vehicles – although heavy machinery, especially high-end autonomous vehicles such as tractors and harvesters, are anything but affordable, especially to farmers in the considered markets. On top of this, there are technical challenges associated with autonomous capabilities, which have limited the deployment of this technology in more affluent economies to heavily industrialized/ mechanized farming operations.

One promising tool which might straddle the two main drivers of 5G-driven improvements to agriculture is drones. While flying harvesting machines are unlikely to be relevant to the considered markets in the short to medium term, the use of drones, due to high commercial availability, low cost, and ease of use, could see many economic benefits materialize as well, though the focus in the short term is squarely on IoT sensors and associated data analytics and management tools.

The Ericsson-Analysys Mason reports comes at an interesting time for IoT technology. Initially integrated into the 5G architecture through the massive machine-type communications (mMTC), and mission-critical IoT pillars, these two use cases represent extremes on both ends of the required IoT quality of service spectrum, and as a result, vary widely in terms of their demands on the network.

While mission-critical devices require very low latencies, high throughput and high reliability for their use cases – for example, autonomous rescue vehicles or remote-controlled assets – mMTC devices are at the opposite end. Latencies factor little into consideration, while data throughput rates are generally low, nothing like the live video and command and control feeds required for mission-critical applications. Additionally, due to their massive numbers,  devices and sensors need to be low-cost and low-complexity, which places very different constraints on the network from high bandwidth or low latency. Battery life is perhaps the most important aspect, as a large number of connected devices and sensors is highly impractical to collect and charge manually. While additions such as small solar panels might be worthwhile in some applications, adverse solar conditions might be chronic for others.

While these two aspects of IoT connectivity are relevant and will see a great many important applications, there are also many use cases with less stringent restrictions and constraints on the networks.

For example, while emergency drones might require ultra-high-definition video feed and ultra-low latency to coordinate and interact with human operators working alongside them on rescue operations, the types of agricultural drones proposed earlier, for use in aerial data gathering, have far less constrained demands. Latency, while still a consideration, would be tolerable up to the 100ms mark. Similarly, throughput requirements may well be lower for selected use cases. This is not only down to the lower-quality video, or non-video, feed, but also reduced complexity in terms of the flight control data it may have to transmit via its command-and-control link.

Similarly, while some sensors in extremely remote locations such as long-term volcanic or high-altitude observation posts may need years of battery life, necessitating extremely low power usage, other sensors may only have to remain operational over weeks or months. In agriculture, sensors may have to be removed once a year from the fields anyhow to avoid the further integration of plastics and silicon into the human food pyramid.

In recognition of these less stringent use cases, 3GPP, in its 5G NR standards Release 17, introduced a new tier of reduced capability (RedCap) devices, also known as NR-Light. NR-Light devices are to support 150Mbps and 50Mbps in the downlink and uplink respectively, while also having accommodations for low-power modes to conserve battery life (see Wireless Watch November 28 issue).

While IoT demands are currently adequately met by low-power WAN (LPWAN) variants such as NB-IoT and LTE-M, RedCap provides a 5G migration path. At the same time, there is an explosion in the number of connected IoT devices, in particular in China, but also around the world.  This counts not only connected sensors and smart meters but increasingly also wearables such as smartwatches. These wearables already have higher throughput and lower latency requirements than current low-power sensors, and consequently, there could be serious growth in demand for RedCap in the short to medium term.

Expected to hit products around 2024, RedCap should be an excellent solution for modern farming’s connectivity requirements. While it might not be able to support advanced use cases such as fully autonomous hybrid ground-air drone fleets, those use cases that are already commercially viable and affordable today, such as sensors and small drones, are well within the regime of supported applications.

With climate change wreaking havoc on ecosystems and farming operations around the world, the use of LPWAN IoT devices may be one of the most important and cost-effective tools available to governments to mitigate the impact of changing weather patterns.

When viewed through the lens of national interest, higher yields, better land health, and lower use of water, fertilizer, seed, herbicides and pesticides, can translate directly to better food security for a growing population. In turn, with conflicts over arable land and water becoming more frequent, this could also contribute to improvements in political stability. Recent examples of the political consequences of food insecurity include the Arab Spring, where poor harvests were one of the catalysts sparking popular uprisings across the Middle East and North Africa. Water conflicts include historic ones between Pakistan and India over the waters of the Indus river, and such problems will become more frequent in the future and represent a serious risk to regional stability.