All models have boosted productivity and freed labour for industry. However, the current model is seen as unsustainable and damaging to health and the environment owing to hidden costs, such as acute poisoning and long-term chronic illnesses from herbicides and insecticide toxicity, water pollution from fertilizer runoff, animal waste (that may contain hormones and antibiotics), land depletion, erosion and loss of biodiversity.
Automation, AI and big data – a possible paradigm shift?
Food production across the world faces many challenges: it must meet the need to feed a rapidly-growing global population by boosting production with a shrinking workforce, cut waste (estimated at some 30 per cent of global production) and minimize environmental damage. Modern technologies, such as robots, AI and processing huge amounts of relevant data (big data) can now be applied to farming, which they are set to transform radically allowing more efficient and sustainable food production.
There are several kinds of farm robots, a handful of autonomous robots that can move around and work without human intervention, and others.
Dutch company Cerescon developed an asparagus harvester attached to a tractor. It can look deep underground and harvest asparagus that manual harvesters wouldn’t see emerge until the next day, the day after that, or even three days later. This enables the machine to harvest in one go everything that 60 to 75 manual harvesters would, but having to return on one to three consecutive days. This represents a huge improvement.
Enter Tom, Dick and Harry, with Wilma, and other workfellows
In industry, robots are designed and programmed to execute a limited number of tasks in a set environment, they can be reprogrammed for other tasks. In agriculture the wide variety of operations required, even for a specific crop on a single field, and the variable locations mean that several robots are currently needed for different tasks, such as planting, tendering or harvesting.
The need to have different machines for these tasks means that robot manufacturers have designed bespoke devices. The British based Small Robot Company has developed three small autonomous robots, Tom, Dick and Harry, which it offers through its Farming as a Service (FaaS) model.
Tom monitors soil and plants on an individual basis, keeping track of the health and development of each plant. It collects data and works closely with Wilma, the company's AI driven operating system. Following its surveying task, Tom downloads the gigabytes of data it has collected for analysis by Wilma, which provides comprehensive digital crop models than can be used by Tom's stable mates, Dick and Harry.
Dick micro-sprays each plant with fertilisers or chemicals as required, to help it thrive. Dick also has three ways to deal with weeds. It can micro-spray a tiny amount of herbicide on each weed, burn it, or crush it as it comes out of the ground.
Harry is a robotic drill for various crops. It places individual seeds in the ground using accurate drilling for minimal soil disturbance and records exactly where it has placed them.
These agribots return to their "kennel" when they need power, where they are recharged or their battery replaced with a fully charged one.
A French company, Naio Technologies has produced three autonomous weeding robots, to which tools can be attached. They are used by wine growers, market and large-scale vegetable farmers. These agribots, being light and "intelligent", have a much-reduced environmental footprint compared to traditional machines and methods used in industrial agriculture. For vegetable crops, weeds can be eradicated individually using mechanical implements or using very small amounts of herbicides, replacing the need to spray large surfaces using tractors, crop dusters or helicopters. Operating costs (like fuel) are also much lower as they are electrically-powered.
IEC Standards central to agribot development
All these autonomous robots depend on technologies and systems that rely on standards developed by IEC technical committees (TCs) and subcommittees (SCs).
Standards for primary and secondary batteries needed to power agribots are developed by TC 35, TC 21 and TC 69. Agribots use laser-based light imaging detection and ranging (LIDAR) systems to find their way around fields, and video and infrared/visible wavelength image sensors to identify plants and weeds, using computer-based image analysis, to apply fertilizer or herbicides, if needed, or remove weeds mechanically. TC 76 develops standards for laser applications, while TC 47 and its subcommittees, develop standards for semiconductors used in sensors.
Standards for AI and big data, increasingly important for Agriculture 4.0, are prepared by ISO/IEC JTC 1/SC 42, a SC of the Joint Technical Committee for Information Technology set up by IEC and ISO.
Milking robots still make up some 85% of all farming robots. Most other agribots are still limited to specific tasks or crops, but they are rapidly evolving and will be able to work on many more in the near future, replacing large and expensive farm equipment or hard to find farm labourers. They will have a much lower environmental impact on the land itself and also reduce the need for fossil-based fuels to power large machines or produce herbicides and fertilizers.