The agriculture sector is involved in a revolution driven by data and connectivity. Artificial intelligence, increasingly interconnected sensors and new emerging technologies help increase crop productivity by optimizing water resources, developing sustainability in harvests and animal husbandry.
Compared to other industries, in the recent past, agriculture has been little affected by digitization. Progress in this area, historically, has always been mostly defined by mechanics, in the form of more complex machinery, and by genetics, in the form of more productive seeds and fertilizers. Digital tools enable a quantum leap: New technologies, in fact, favour the ability to make more rational decisions and more effective management of risk and variability to optimize yields and improve the economy.
In recent years, many farmers have begun to use the data to gather essential information on soil, crops, livestock and weather conditions. Current IoT technologies on 3G and 4G networks allow advanced monitoring of harvests and livestock. In the past, the higher cost of hardware and the implementation steps of these tools in agriculture was not cost effective. Today the costs of devices and applications are decreasing, becoming accessible on a large scale, and so that various suppliers can offer solutions that can guarantee the return on investment from the first year. Low-power networks and cheaper sensors are paving the way for the spread of IoT in many areas of agriculture such as precision irrigation of crops in fields, surveillance of large herds of cattle, control of use and remote building performance, monitoring of large fleets of machinery.
The integration of meteorological data, on irrigation, nutrient and other systems improves resource use and increase yields, through the identification and anticipation of shortages. For example, sensors used to monitor soil conditions can communicate via LPWAN (Low-Power Wide-Area Network – type of wireless telecommunication network designed to allow long range and low bit rate communications between various connected objects), managing sprinklers to regulate water and nutrient supply. The sensors can also take images of the most critical areas of the affected territories and send farmers, quickly, alerts on the onset of problems such as diseases, pests or droughts, helping them to make wiser and timely decisions. Intelligent monitoring also allows to optimize the harvest period, providing information on the sugar content and colouring of fruits.
Preventing disease outbreaks and identifying animals in distress are key in large-scale livestock management, where most animals live at close range in a highly automated farming system. Body chips and sensors allow to measure temperature and blood pressure. Other indicators can detect diseases early, preventing herd infection and improving food quality. Environmental sensors control the automatic adjustments of ventilation or heating in the stables, improving the living conditions that increasingly worry consumers.
Chips and sensors to monitor and measure silo and warehouse levels can trigger automated inventory reordering, reducing inventory costs for farmers. Similar tools allow to reduce post-harvest losses by automatically controlling and optimizing storage conditions. Monitoring the condition and use of buildings and equipment reduces energy consumption. Machine vision and sensors attached to equipment and predictive maintenance systems can lower repair costs and extend the life of machinery and equipment.
Agriculture has been using drones for several years. The new generation of drones is starting to influence the industry with the ability to detect crops and herds over large areas quickly and efficiently. In addition, they can be used as a transmission system to transfer data in real time to other connected equipment and installations. Drones can also use artificial vision to analyse the conditions of the territory and provide precise indications on the interventions to be carried out where the crops need it most, using fertilizers, nutrients and pesticides. They also find application to plant seeds in remote places, reducing the costs of equipment and manpower.
More precise GPS controls coupled with machine vision and sensors are leading to the development of intelligent and autonomous agricultural machinery, capable of operating without the guidance of an operator. This will allow farmers to use more equipment in the field at the same time, without human intervention, optimizing time and resources. Autonomous machines can also be more efficient and accurate than human-powered ones. They are able to reduce fuel consumption and have higher efficiencies. The use of these technologies will also lead to greater integration between the different systems. The data collected by autonomous tractors is seamlessly transferred to the computer that controls the irrigation devices, which in turn receives data from the weather stations to optimize on and off schedules.
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