Digital Farming: The MacDonalds meet the Jetsons

Stephen DeAngelis

June 29, 2018

When (if ever) people think about agriculture, Old MacDonald’s farm or Grant Wood’s American Gothic are more likely images to come to mind than the Jetsons. But farming is moving into the Digital Age. It’s an Age when discussions about paperless offices and robotic factory floors are far more likely to be heard than digital transformation on the farm. “The world talks a lot about the digital revolution,” write World Bank analysts Heinz Strubenhoff (@HStrubenhoff) and Roy Parizat, “but few connect it to the coming agriculture revolution, especially in Africa. Digital solutions have huge potential for helping farmers boost productivity and connect to financial tools and markets around the world.”[1] Two global trends are exacerbating future food security concerns. The first concern is the global population which is predicted to increase to 11.2 billion people by 2100.[2] That’s a 47% increase from today’s population of 7.6 billion people. The second concern is urbanization which is seeing more people leave the farm and head for the city. Today just over half the world’s population lives in urban areas. The United Nations predicts that percentage will rise to 68% by the year 2050.[3] Without Digital Age tools and techniques, feeding more people with fewer workers would be an impossible task.

Agriculture in the Digital Age

Heidi Vella (@Heidivel) notes, “Efficiency gains need to be made in the agriculture sector if it is to feed the [additional] two billion people that will be on the planet by 2050. Farming is often a delicate balancing act of doing something at exactly the right time; get it wrong and an entire crop can be ruined. This is why the industry needs innovation to improve processes and output and to make more accurate predictions and decisions.”[4] Like any business, agriculture involves a lot of decisions. Make those decisions better and the business improves. That’s where cognitive computing, a subset of artificial intelligence (AI), comes into play. Vella explains, “According to a report by Mind Tree, agriculture is seeing rapid adoption of AI and machine learning for both agricultural products and in-field farming techniques, with cognitive computing to become the most disruptive technology in the sector. … The use cases for AI are far and wide. Potentially algorithms can also help identify plant disease, detect pest infestations and help automate farm equipment.”

Analysts from the Australian firm CSIRO observe, “Digital transformation is everywhere and, as we have seen, agriculture is no exception.”[5] They identify three opportunities digital technologies present farmers: 1) increasing management precision, with producers able to use better information to make more timely decisions with more predictable outcomes; 2) automating tasks using sensing technologies and machine learning could cut costs and increase reliability; and 3) better categorizing, differentiating and tailoring of agricultural products and services, which will open up new markets. Some of the digital age technologies now in use or predicted to improve the agricultural sector include:

Sensing systems. CSIRO analysts point to the European Sentinel satellites, as one type of sensor providing data to farmers. They note, “Satellite imagery can identify what is growing in each paddock and then forecast a yield or feed availability. This information can have a wide range of end uses: farm management, farm advice, input supplies, risk assessment, planning for logistics and handling and assessment for drought relief.” Ground-based or proximal sensors will also be widely used in agricultural settings. The analysts note these devices, “such as handheld devices or even cameras on smartphones,” can help with precision irrigation and fertilizing. They go on to note, “While sensors abound on the market, there are still some notable gaps. For instance, we still don’t have a sensing system that can non-invasively measure soil fertility nor diagnose animal health.”

Knowledge discovery and management. Like Vella, CSIRO analysts see great potential in the agricultural use of cognitive technologies. They explain, “The use of artificial intelligence, machine learning and natural language processing will streamline the discovery, access, usability, and confidence farmers place in data. We should grasp the big opportunities in synthesizing disparate information that resides in often fragmented and difficult locations, such as government agencies, research and development funding bodies, product manufacturers and distributors, and on-farm data. Doing this could unlock information for farmers and advisers.”

Advanced analytics. Cognitive technologies advance the state of analytics by providing four types of analytics: 1) Descriptive Analytics that can determine what happened; 2) Diagnostic Analytics that explain why something happened; 3) Predictive Analytics that use advanced algorithms to forecast what might happen next; and, 4) Prescriptive Analytics that recommend steps to take to achieve a desired result. CSIRO analysts note, “At the moment our ability to collect vast amounts of data easily outstrips our ability to convert it into usable information. Predictive analytics can play a critical role for decision makers who need to interpolate and forecast from a current situation to an alternative state.”

Blockchain. Today, much food is wasted as a result of recalls or because it spoils en route. Blockchain technology can help with both challenges. CSIRO analysts note, “Agriculture and food are ideal domains to exploit the potential of distributed ledgers or blockchain. … Blockchain technology allows information to be carried along a supply chain; to match product to processing demands; to enable traceability, verify provenance and monitor quality and safety.”

Value-adding to farm data. CSIRO analysts assert, “There is a huge opportunity in pooling data currently held in thousands of private hands to create products and services that farmers can use to improve their businesses. … Governments and research bodies already pool lots of ‘small data’ and use it to monitor performance trends in the industry. The innovation challenge in agriculture is finding the right business model for farmers to participate in.” Farmers want to be justly compensated for providing data that profits corporations that use that data to create products or advance proprietary business models.

Automation and robotics. Farmers are already using GPS data to drive tractors and urban farmers are using numerous Digital Age technologies to grow crops indoors under precise conditions. Every year, larger numbers of robots are being put to use in fields and orchards to accomplish tasks historically requiring human hands. In addition, drones are now used to map fields and monitor crops.

Summary

Most the Digital Age technologies used in agricultural rely on the Internet of Things (IoT). Sensors gather data and the IoT transmits it to an analytic platform. Daisy Ridley, a Senior Data Analyst at Mindmajix.com, observes, “Farmers are getting more connected as they realize the potential of IoT technologies in enabling [them] to minimize operational costs while still attaining better results. The examples include less water usage, lower livestock losses, and higher crop [yields].”[6] Strubenhoff and Parizat conclude, “While these innovations only scratch the surface of the coming digital revolution, it’s clear that digital solutions will transform agriculture with great benefits for smallholders.” In the years ahead, George Jetson will probably be more comfortable on the farm than Old MacDonald.

Footnotes
[1] Heinz Strubenhoff and Roy Parizat, “Can the digital revolution transform agriculture?” The Brookings Institution, 28 February 2018.
[2] United Nations, “World population projected to reach 9.7 billion by 2050,” United Nations Department of Economic and Social Affairs, 29 July 2015.
[3] United Nations, “2018 Revision of World Urbanization Prospects,” United Nations Department of Economic and Social Affairs, 16 May 2018.
[4] Heidi Vella, “The digital farmer: How AI enabled agriculture will help feed the world,” TechHQ, 16 may 2018.
[5] Michael Robertson, Andrew Moore, Dave Henry, and Simon Barry, “Digital agriculture: what’s all the fuss about?CSIROscope, 20 March 2018.
[6] Daisy Ridley, “4 Ways in Which IoT is Revolutionising Agriculture,” Datafloq, 12 December 2017.