Digitalization and AI

AI AND ROBOTICS IN AGRICULTURE

AI AND ROBOTICS IN AGRICULTURE

AI and robotics in agriculture include drones, autonomous farming, data-driven crop support software and digital platforms, and a variety of harvesting and sorting robots. An artificial intelligence (AI) software-equipped robot can improve performance by learning from errors. Crop support software, automated guided vehicles (AGV), grippers, and vision and sensing techniques are among the methods frequently used in agriculture robotics. These technologies help increase efficiency and reduce labor costs in agricultural operations. The integration of AI and robotics in agriculture has the potential to revolutionize the industry by streamlining processes and increasing productivity.
REAL-TIME DATA IN AGRICULTURE

REAL-TIME DATA IN AGRICULTURE

Agriculture is already seeing roboticization. Its many benefits include the ability to deal with pests more effectively and easily, harvest crops more quickly and in larger quantities than humans can, and account for a variety of factors like market demand that are challenging for farmers to monitor simultaneously without the aid of technology.

These days, farmers can obtain real-time data by using sensors, drones, and other equipment. This data is then measured and saved to provide the best possible recommendations and action plans. The most recent advancements in this subject include carbon footprint analysis, equipment management, livestock welfare, nitrogen application, and soil moisture monitoring.

Decisions made will be better and less resources will be wasted on trial and error if more and better data is gathered. More accurate and effective agricultural techniques are made possible by the use of cutting-edge technology in agriculture. Farmers may optimize their operations and boost output while reducing their environmental impact by implementing data-driven insights.

FUTURE OF DIGITALIZATION IN AGRICULTURE

FUTURE OF DIGITALIZATION IN AGRICULTURE

The range and inventiveness of digital technology in the agriculture industry are practically limitless. Precision farming technologies enable effective fertilization tailored to the site, using both manure and synthetic/mineral fertilizers. The first step in preventing fertilizer excesses that are released into water bodies and cause eutrophication is needs-based fertilization.

Of course, efficiency gains facilitated by digitalization, such as a reduction in water consumption, pesticide use, and climate-relevant (N) fertilization, or a drop in CH4 emissions from animal digestion, are not unnecessary. They are an addition to existing reducing strategies. In addition, more precise measurements of emissions and environmental effects are made possible by digital and sensor technologies, which is a crucial first step in developing and putting into practice environmental and climate protection policies. Digitalization can play a major role in the phase-out of fossil fuels in relation to the 1.5 °C limit since digital solutions are essential to a decentralized, renewable, and smart energy system – that is, the energy revolution.

Artificial intelligence (AI) has a lot of potential applications in the sustainability field, but its main advantage is that it is one of many strategic tools available for achieving environmental objectives.