First came mechanisation. Then the Green Revolution with high-yielding crop varieties. Industrialisation increased the scale of operations. Farming is now ushering in the next revolution, Agriculture 4.0.
Using a slew of technologies from artificial intelligence to robotics and more, the future of farming is about precision agriculture – optimising crop growth in the face of unprecedented challenges.
Agriculture is at a crossroads facing multiple headwinds at once. First, climate change leads to unpredictable weather patterns, intensifying droughts and hurricanes and bringing dwindling water supply and crop damage. At the same time, the world’s population continues to grow. It is expected to reach 9.7 billion by 2050, according to forecasts from the United Nations. From 2030 to 2050, for example, we will add 1.2 billion more people in just twenty years. Food security challenges will exacerbate.
Increased food production when finite resources such as arable land and freshwater dwindle will continue to be challenging. The labour migration from rural areas to the cities decreases the delivery available to work in the fields.
These challenges might seem daunting, but relatively new technologies woven into Agriculture 4.0 promise to solve them all – or at least be a powerful ally. Using modern information technology to address the world’s population challenges is not new. Still, the principles of this next revolution apply quite literally from the ground up – from sensors in the soil and monitoring large herds of livestock to drones that survey widespread crop plantings. It all starts with digitising records to quickly gather and analyze information, leading to sharper insights.
The future of farming is about digital transformation as the root cause for growth.
Advanced Technologies and the Future of Farming
Data-driven decision-making is revolutionising a range of sectors, from healthcare to manufacturing, and it forms the backbone of Agriculture 4.0.
Once all crop information is digitized and moved over from pen and paper, advanced technologies can work in precision farming. The many technological developments that can work in concert with future agriculture technology are:
Data analytics is not so much a technology as what Agriculture 4.0 can do with data. When the future of farming depends on optimising scarce resources like arable land, water, and labour, data-driven decisions are critical. Data analytics leave no room for double-guessing and give farmers the confidence to make vital business decisions and improve crop growth.
The Internet of Things (IoT)
In the next iteration of the agricultural information technology revolution, the data comes not from the usual places but from “things” like sensors in the soil – in real-time. IoT sensors can measure moisture and let farmers know when it reaches below a certain predetermined level as a gauge of soil health.
Temperature and moisture sensors can deliver an early warning when they spot the early stages of the disease. Thermal sensors can even help keep an eye on animal health. They can detect the presence of mastitis, a condition that affects cows’ udders.
Massive IoT sees widespread adoption of IoT in farms and promises to fine-tune practically every parameter worth measuring, including fruit ripeness indicators, animal welfare, and health and plant disease detection.
Data from various sensors feed analysis models that can crunch the numbers and deliver real-time insights about soil properties and other relevant parameters. Such fine-tuned data science helps farmers optimise their yields instead of making educated guesses.
Drones and Multispectral Cameras
Farming operations demand coverage of acres upon acres of land; keeping an eye on crops in that area is often tricky. Airborne drones are very effective at data collection – they can tell whether crops are showing early signs of disease – using onboard sensors. In such cases, drones with cheaper sensors can complement IoT installations.
The future of farming will see accelerated deployments for drones, including using them for delivering precise doses of insecticides only in select crop areas and for planting seeds in remote locations. Drones have the data-gathering mettle to cover large distances, an attractive feature in agriculture.
Artificial Intelligence and Machine Learning
While IoT sensors might measure, gather, and route data, AI can analyse it for immediate problems and long-term trends. AI can make sense of images gathered from drones and study them for spots on crops that indicate signs of fungal disease and other indicators of problems. Fertilisers can lean on such intelligent perception and be customised for issues and locations if needed. Such an approach carefully uses all raw materials instead of wasting applications on areas that might not need them.
The most basic versions of trained AI models rely on remembered memory. They compare what they see today with what they already know. If, for example, farmers need information about the ripeness of fruits, AI helps by comparing the image feed from the fruit trees today and contrasting it against established learnt images of ripe fruit. More advanced AI models don’t need such deep banks of known data. Instead, they learn on the job with a small starter dataset.
Agriculture is full of repetitive and dull tasks – the seeding of fields, weeding, and picking of produce are just three examples – that would make agricultural engineering an ideal fit for autonomous machines. The future of farming will see robots taking on dull (often hazardous) jobs while hard-to-find workers can be assigned to more exciting projects.
Robots can be programmed to perform specific tasks at specific times, which also makes them reliable in addition to being efficient. Already, robots are milking cows and picking strawberries and other fruit. Expect to see more implementations of field robotics soon, especially in agriculture organisations, as connectivity infrastructure improves and labour costs increase.
Farmers need access to many data points and digital tools in the fields. They might need to check watering schedules, check livestock for signs of bacterial infection, reassess repair contracts of ageing equipment, or sign off on a track record for workers. Accessing decisions and information in real-time means that data must be stored in the cloud so farmers and all authorised staff can track the real-time data from a central location.
Rugged Solutions in the Agriculture Industry
The digital transformation that underpins Agriculture 4.0 is about data-driven insights using relatively emerging technologies. These insights must be accessed in real-time and mobile for maximum utility in future agriculture.
Rugged mobile devices and computing units from Getac are built for precisely this purpose. Onboard connectivity features help with access, while ruggedness helps the devices operate despite challenging weather conditions and rough handling. Getac devices are also made so users can work with them despite harsh sunlight.
Agriculture’s future is leveraging information technology’s power to make farmers realise higher yields and associated food security. At the same time, the food industry has to tackle the challenges ahead. This includes climate change, food, decreased food security, and a shortage of manual labour.
With rugged mobile devices, farmers can use data-driven insights harnessed by modern technology to make the right decisions at the right time in a complex environment. Doing so can help reap the benefits of precision agriculture and Agriculture 4.0.