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Edge and Cloud Computing in Agriculture: Who Will Prevail?

Learn if edge computing in agriculture is an ephemeral phenomenon or a force that has come to substitute for cloud farming once and for all

October 04, 2021

11 mins read

Many have pondered over the ultimate purpose of technology. Yet, it took people almost 200 years to realize that technology must help folks sustain their lives. Is there a better way to live up to this mission than by ensuring efficient, sustainable, and (almost) zero-waste farming? There is not, and cloud computing in agriculture has already been on the task for years, with cloud software development services booming. Nonetheless, it seems like edge computing is stepping on cloud farming’s throat with the real-time connectivity boot. Cloud computing in agriculture has been a breakthrough, a game-changer for the industry. Still, the set of limitations it featured, especially the lack of real-time connectivity, has had folks come up with edge computing, which turns digital agriculture capable of a faster and fiercer reaction to perils imposed on agribusinesses by weather, soil, poorly automated machinery, etc. Let’s figure out whether edge computing in agriculture will become a substitute or a partner to cloud farming in the future. You’ll find out:

  • Still a second to none cloud farming offering
  • Cloud farming in agriculture: Practical output
  • Challenges on the cloud computing for agriculture agenda
  • Edge computing saving cloud farming?
  • Edge computing farming: It really works
  • So is it cloud farming or edge computing in agriculture?

Still a second to none cloud farming offering

John Deere’s Operations Center, Farmers Business Network, Bayer’s Climate FieldView, and many-many other start-ups and established products have already proved that cloud computing in agriculture is worth our trust. So here comes a bit of jolly allusion for you. The present and future of global farming are in the clouds. Yet, the difference here is that those clouds are free of precipitations but full of valuable data. Besides copious projects, there are also numbers backing the relevance of cloud farming.

According to O’Grady, Langton, and Hare, the digital farming market, estimated at $6.34 billion in 2017, is currently skyrocketing through the capitalization charts with a prognosis of reaching $13.50 billion in 2023. The sum is nothing less but a Compound Annual Growth Rate (CAGR) of 12.39%, which is a fascinating result. Furthermore, Microsoft and Amazon are developing their digital farming platforms, thus once again proving that cloud computing in the agriculture industry is an already established yet unplowed field of benefits and opportunities.

Indeed, the usage of data rises exponentially in the agriculture industry as AI-powered systems change the rules of the game with intelligent automation. Research conducted at the University of Wisconsin-Madison states that: “Data is gathered on the soil within fields, the plants growing on fields, the weather occurring during the growing season, and the machinery used in fields.” That is, data has become ubiquitous, as it makes farmers’ lives even more than easier; it helps them predict and react in time. Cloud computing can help with real-time computation, data access, and storage to users without knowing or worrying about the physical location and configuration of the system that delivers the services.

Cloud farming in agriculture: Practical output

Hence, while we’ve already established the propriety and relevance of cloud technology in farming, let’s move on to discuss the practical output it can provide within the farming framework. Briefly speaking, cloud computing in agriculture can be used to aggregate data from tools like soil sensors, satellite images, and weather stations to help farmers make better decisions about managing their crops. The cloud’s analytic capabilities also aid farmers in understanding their production environment. For example, interpreting drone data for improved crop management decisions is another benefit that cloud computing farming delivers. In general, there are seven major deliverables to tap into.

  1. Crop-related information. Data can help farmers gather and analyze information on the crops grown in the past or presently, thus boosting their decision-making in the future.
  2. Weather information. Edge computing can provide real-time weather region-specific information, which is crucial, especially given the opportunity for receiving forecasts for specific durations.
  3. Soil information. Agricultural decision-making is heavily dependent on soil information, as apart from soil profile, a farmer needs to know the soil’s past behavior and its future trends. Knowing, for example, whether the soil has a tendency for turning acidic or alkaline might be crucial.
  4. Growth monitoring. Controlling the growth of various crops in different regions at regular intervals gives the farmer a lot of information on the growth intervals, which is of essence in sustainable and lucrative farming.
  5. Expert consultation. Edge computing creates an opportunity for a real-time solutions hub, where farmers can discuss their real-time problems.
  6. Farmers’ data. Farmers’ data can be captured region-wise, which means it represents a great opportunity for stepwise agricultural policymaking and strategizing.
  7. E-commerce. Farming businesses from rural areas finding direct paths to the market, which excludes the exploitation scenario for them. An agricultural management information system based on cloud computing helps farmers sell their products directly.

The benefits are obvious. What is more, in accordance with Sourcerace, 73% of cloud and edge computing users from other industries believe that it has reduced the cost of infrastructure, while 74% claim to have experienced alleviated internal resource pressure. Still, when it comes to agriculture, there are challenges that cloud technology farming cannot deal with on its own.

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Challenges on the cloud computing for agriculture agenda

The opportunities that cloud computing in the agriculture industry offers look quite fascinating. However, challenges are brooding over them with three dark clouds of low security, insufficient speed, and high cost. Nonetheless, the industry leaders have managed to deal with those problems with the help of edge computing. So, let’s have a closer look at the issues and solutions mentioned above.

Issue 1: Cloud technology farming security

Where there is data, there are threats, and they will always be there. When discussing cloud computing in the agriculture industry, we shall face the fact that the leakage points come in abundance, as the IoT systems transmitting the data to the cloud consist of many devices. Hence, every time the data travels to and fro, the chance of having it violated, stolen, and misused grows exponentially as you grow your digital farming system.

Solution 1: Edge computing agriculture

Edge computing is the ultimate recipe for minimizing the risk of data theft or violation, as it lets your data stay home – within the boundaries of the device that collects it. Meanwhile, all the calculations and analysis will be carried out locally as the real-time connectivity lets the cloud work the data through without making it travel far. Edge computing agriculture might is a must for improved and custom-built precision mapping that empowers agribusinesses to flourish.

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Problem 2: Speed of cloud computing in the agriculture industry

Slow connections are one of the most widespread issues in today’s digital agriculture. Following The Week, “The current limitation for the adoption of cloud computing services is rural internet speeds. Imagine having gigabytes of image data that takes hours — if not days — to get uploaded to the cloud due to slow internet speeds.” Sounds not that fun, right? For example, custom-built smart irrigation systems might suffer a lot from such a shortcoming. Indeed, collecting, transferring, and analyzing data is a time-consuming task, which is not always “forgivable” in agribusinesses that requires a prompt reaction. Hence, some organizations face the dilemma of choosing between the depth of insight and the processing speed.

Solution 2: Edge computing in agriculture? You’ve got that one right!

Edge computing revolutionizes the data analysis process by rendering it local. Each device in the network can analyze the data it collects, providing immediate feedback, and thus increasing the processing speed and furthering the depth of insight. Yet, there is a need to understand that wireless devices used in the agriculture industry are produced in compliance with various wireless standards. In general, there are seven major types of wireless nodes, which are heavily applied in agribusiness.

Common wireless nodes used in the agriculture domain
Edge and Cloud Computing in Agriculture: Who Will Prevail?
Source: MDPI

Issue 3: Cost of cloud farming

Cloud computing farming expenses depend on the amount of data that is generated by the IoT system and then transferred throughout the network to the cloud and back. With the number of sensors an average digital-driven farm requires on the rise, the cost is only going to get higher. For example, a 2020 report by Agricultural Robotics Laboratory at Valencia Polytechnic University shows that there are 250,000 farms in the United States that cover more than 1200 million hectares of land with the help of IoT solutions, which assist them in advanced crop management. As those farms grow, they need more data points, which require a better “brain” for processing the data, meaning that the cost skyrockets.

Solution 3: Edge computing once again ousting cloud farming

Edge computing in agriculture frees businesses from storing mammoth volumes of irrelevant and useless data, as it discards the need for transferring the data to the main database. With edge computing, everything can be processed on-premises, thus cutting storage and bandwidth cloud costs. For example, in 2014, Fujitsu, a Japanese tech giant, established a state-of-the-art vertical farming system outside Hanoi. Grain claims that the farm has been a success primarily due to the involvement of edge computing, which lets Fujitsu use the Aeon-based cloud for the farm’s macromanagement while covering all the micromanagement tasks with the help of edge computing.

Regardless of how advanced and comprehensive they are, there is a need to understand that the cloud solutions offered by the “industry’s big guys” are too expensive for even average-sized farmers. What is more, their price-quality ratio does not always deliver to its promises due to the Internet speed limitations, which are ubiquitous in rural areas. Hence, edge computing is one of the best solutions, which Intellias perceives viable for rendering agribusinesses’ IoT infrastructures efficient for connected farming. Considering the listed challenges, the advantages of edge computing in agriculture become even more obvious.

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Edge computing saving cloud farming?

In fact, it does not; edge computing cannot save cloud farming as those two are absolutely different. Edge computing is a distributed computing paradigm that moves data storage and computation closer to the data sources, meaning that data does not have to ‘travel’ far. Thus, ad hoc decisions become available for farmers, which is exceptionally valuable in a number of situations. For example, designing and implementing a smart spraying technology system for precise herbicide application requires a lot of relevant real-time information.

Now, getting back to the “saving cloud farming” part, all those “edge computing will supersede the cloud” talks are nothing else but vapid conversations, at least until 5G covers the globe, as per Saguna. Meanwhile, edge and cloud computing in agriculture are two completely different technologies that are non-interchangeable. The pivotal difference between them is that edge computing is used to process time-sensitive data, which is of essence in agriculture, while cloud computing works best for data that is not time-driven.

Hence, edge computing is surely the best solution for remote locations where there is no centralized connection. Local storage and mini data centers will get things done. Indeed, sending real-time images and videos to the public cloud is useless. Meanwhile, harnessing the potential of 5G, edge computing processes the data on the spot, producing rather critical real-time information about crops and livestock.

Edge computing farming: It really works

As of now, edge computing has already proved its worth in cutting costs and optimizing yields with AI-driven automation. The thing is that edge computing enables improved computer vision, which, when empowered by the mix of 5G and IoT, gives farmers an opportunity to get the most efficient way of completing ad hoc tasks automatically, which cloud computing farming is not capable of. For example, analyzing information from drones requires more than masterfully developed software.

Moving on, the so-called agribots (autonomous tractors and robotic machinery) are another vivid instance of edge computing prevalence in today’s digital agriculture. According to Eastern Peak, they run on autopilot while communicating with the nearby sensors to obtain the data about the surrounding environment; calculate the most efficient paths to cover the required area taking into account the type of performed task, number of vehicles currently in the field, size of implements, etc. Furthermore, they are capable of automatic rerouting in case an unexpected obstacle appears on their way. Performing the same task while harnessing the cloud leverages could be harder.

Edge computing offers farmers a plethora of solutions, which might make it easier for them to implement various technologies, such as GPS and GIS, to automate and refine their day-to-day agricultural operations. Below is the table of edge computing features that come in handy in various agriculture domains.

Usage of edge computing techniques in the domain of agriculture
Edge and Cloud Computing in Agriculture: Who Will Prevail?
Source: MDPI

So is it cloud farming or edge computing in agriculture?

Edge computing is good; it is even better than good; it is a marvelous solution that lets farmers deal with their issues, which is crucial for the industry. Nonetheless, it seems like cloud computing for agriculture is here to stay, as there is yet no analytical framework that edge computing could use to substitute for cloud farming ubiquitously. Of course, we will face a long-term dominance of data and IoT in farming. Nowadays, there is no better way towards sustainable agriculture than the one paved with data-driven decisions. Still, we are not going to witness a war between cloud and edge computing.

This is going to be an allied intrusion into the fields around the world, as the edge is going to gain momentum and back cloud up in the locations and areas that still lack speed, security, and reasonable pricing. Finally, given that the number of data points involved in fostering the agricultural sector’s progress is only going to grow, along with the required speed of their interpretation, we might, probably, need even something more than edge and cloud computing. The future’s exciting!


If you are interested in moving faster along the line of agricultural business than your competitors or the weather forecasts do, contact us. We have the solutions you need and we can come up with the new ones, shall the need occur.

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