The agricultural industry is one of the most critical areas for technological innovation to be effective and successful.

Agriculture has been altered profoundly throughout the last 50 years as a result of machinery improvements that have expanded the scale, speed, and productivity of farm machinery. In addition to increasing yields, seed, irrigation, and fertilisers have also improved.

Now, agriculture is about to experience another revolution, at the heart of which will be data and connectivity.

Artificial intelligence, analytics, connected sensors, and other emerging technologies may increase yields, improve the efficiency of water and other inputs, and enhance sustainability and resilience across crop cultivation.

According to the McKinsey Center for Advanced Connectivity without a solid connectivity infrastructure, none of this can happen.

It reported the agriculture industry could add $500 billion to the global gross domestic product by 2030, if connectivity is properly implemented.

Advanced connectivity is expected to contribute $2 trillion to $3 trillion in additional GDP to the global economy over the coming decade, one of only seven sectors that will be responsible for this.

Rather than applying water, fertilisers, and pesticides uniformly across entire fields, farmers can now target very specific areas or treat individual plants differently.

Agriculture plays a critical role in providing income and food for millions of people across the world. The methods of contemporary agriculture and agricultural operations are strikingly distinctive from those of decades past, thanks to technological advances including sensors, equipment, machines, and information technology.

Land and farming inputs are becoming scarcer at the same time that demand for food is on the rise.

In order to meet the world’s 2050 population of 9.7 billion with the 70% increase in calories needed, the cost of the inputs required to produce those calories is increasing even as the world’s population grows.

Labor, nutrient, and energy costs are already pressuring profit margins, and by 2030, water supply will fall 40% short of meeting global water demands.

Enhanced connectivity in agriculture could increase global gross domestic product by $500 billion by the end of the decade, improving productivity by 7 to 9 percent. Much of this value will require additional connectivity investments, which are currently scarce in agriculture.

Other industries already use LPWAN, cloud computing, and cheaper, higher-quality sensors requiring little hardware, which will significantly reduce the cost of implementing them.

Any innovation in the agribusiness sector (farm to fork) that improves efficiency, profitability, or environmental sustainability is considered AgTech.

AgTech can function independently or in conjunction with an IoT network (see below), in which devices can communicate with one another and the internet.

One of the latest technologies in the agricultural sector is drone technology, which has been applied to different areas of the industry. Drones can be used for pest control, soil analysis, and drone imagery.

Pest control using drones can be a powerful alternative to traditional methods, especially for large commercial farms.

There is a range of pest control drones on the market, such as the autonomous drones that uses a UV light to attract pests and dispense a pesticide that is distributed by a fan and is harmless to people.

Drone images are a cost-effective way to monitor and manage crops. They can be used to assess soil quality, detect pests and diseases, and estimate the volume of produce.

Soil analysis can be conducted by taking a sample of the soil and sending it to a lab. Alternatively, farmers can take an image of the area with a drone and send the image to a company that can analyze it and send the data back to the farmer.

Computer vision may be used by drones to analyze field conditions and deliver the correct nutrients, pesticides, and fertilisers, or to plant seeds in remote locations, lowering equipment and workforce costs. By lowering expenses and increasing yields, drones might generate between $85 billion and $115 billion in value.

Automated farming has been around for years and continues to be one of the most common types of agricultural technology innovations.

It includes a wide range of robots and equipment that perform tasks such as irrigation, soil management, nutrient application, and crop harvesting.

Robot harvesting has been used in commercial farming for decades. In recent years, the technology has also gained popularity in small-scale farming.

Crop Management and Soil Management are other areas where automated farming can make a difference. In crop management, a timing device can be used to trigger the application of fertiliser or pesticides at the optimum time. This can help improve the efficiency of these chemicals and reduce costs.

Soil management systems help create optimal conditions for growing crops by monitoring soil conditions and releasing nutrients as needed.

Autonomous machines are better at working fields than human-operated ones, which could save fuel and generate higher yields.

By increasing the autonomy of machinery through better connectivity, $50 billion to $60 billion in additional value could be produced by 2030.

Robotics has been used in the agricultural sector for many years, mostly in the harvesting of fruits and vegetables. Robotics can also be applied to other agricultural operations such as planting, weeding, and harvesting.

These robotics can also help with repetitive and strenuous tasks, which can improve safety and reduce costs.

Seed planting is a common application of robotic processes. The application of seeds is usually done manually using a process that requires accuracy and precision. Plant weeding is a process that is often done manually, but it can be automated using robotics.

The weeding robots can be programmed to move between different areas, such as between rows of plants.

Harvesting can be a challenging process, especially given the need to be precise, accurate, and careful. For example, harvesting fruits such as apples can be dangerous when done manually due to the risk of falling. Robotics can be used to automate this process and make it safer.

Cloud-based technologies are commonly used in agriculture. This can be used in a variety of applications, such as a centralised data management system, telematics, and customised software.

Cloud-based technology also helps with data collection and management. Data can be collected from different equipment such as sensors and be sent to a centralised system for analysis and modelling. This can be useful for managing large farms with various pieces of equipment.

Advanced data management systems can be used for best management practices (BMPs) and tracking produce.

BMPs refer to management practices designed to reduce pollution and protect public health. These systems can be used to track and trace produce from source to destination, which can be useful in case of food-borne diseases.

Machine vision is a technology that has been used in many industries and is now also beginning to be applied to agriculture. It is the process of using computer vision and image recognition to get information from images or videos.

Machine vision can also be applied to a range of activities in agriculture, such as :

Machine vision can also be used to identify and automate the harvesting of crops such as apples and oranges. This can be done by mounting a camera on the harvesting equipment to detect when the fruit is ripe and ready to be harvested.

A “thing” or “device” that is connected to the internet and equipped with sensors and other technologies is known as an IoT device.

When IoT devices communicate with each other and the internet, they can send notifications or automate other features, such as sprinklers in an orchard.

Farmers often use an interface or dashboard to receive the information generated by IoT devices. This is how farmers receive the information they need to make informed decisions in real-time.

For example, a trough’s water level or wind speed in a paddock can be determined using a smartphone app, saving time and ensuring peace of mind

Farmers may benefit from using crop sensors by effectively applying fertilisers and pesticides, especially the amount required. Variable rate technology is an excellent approach in this scenario. This technology allows you to feel the sensations of plants and then reduce the risk of leaching or runoff. The crops sensor calculates the amount of resources needed for a particular crop and when to apply them.

GPS is becoming an ubiquitous technology in farming. Agriculture is one example where GPS is employed to document the state of the land.

By using GPS, it is simple to record and quantify crop yields from a certain farm, as well as application rates. These technologies are advantageous in that farmers may reference the recorded and documented information for assistance when making any choices.

Yield maps are an excellent method to document yields from a year. These maps may be used to provide a summary of the entire year’s activities. They are very valuable because they may provide a wide variety of data, such as the status of drainage systems.

The agricultural sector has long been the focus of technological innovation, with new technologies emerging all the time.

Technology in the agricultural industry can reap a multitude of benefits thanks to the adoption of modern technology, including increased crop yields, reduced environmental impact, increased worker safety, reduced water, fertiliser, and pesticide use, among others.

From the use of drones and autonomous machines to improve crop management and harvesting, to the implementation of cloud-based technologies to optimse agricultural operations, new technologies have the potential to benefit both farmers and consumers.

Darren is a Agtech enthusiast and former farming electrical engineer.

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