Smart Solutions in Agricultural Robotics

Abstract The article contains an overview and prospects for the introduction of smart and robotic technologies in the agricultural industry. Today, robotization of agriculture and food technology is not a leading industry compared to robotization of other sectors of the economy. Analytical review of the global robotics market revealed that robots in the food industry account for 2% of the total, and robots for agricultural operations account for less than 1%. We analyzed global trends in robotization and the introduction of artificial intelligence in agriculture in various countries. A review of smart robotic technologies, in particular, smart sensors and actuators, the Internet of Things, cloud technologies, methods of data analysis, forecasting, classification, and image recognition using neural networks, is provided. Methods and means are considered in relation to both crop production and livestock production. Four main classes of intelligent technologies in agriculture were identified: robotics, Internet of Things, machine learning, and UAVs. In crop production, robots are common in harvesting, controlling weeds, processing trees, monitoring trees at different stages of the growing season, including leaf and fruit diseases, counting the number of flowers and fruits, and other operations. Identification of fruits, leaves, weeds, as well as diseases of fruits and leaves is performed using computer vision, and in recent years convolutional neural networks have become widespread. Field monitoring is performed using UAVs with subsequent image processing using spectral analysis methods. In livestock farming, smart technologies are represented by feeding and milking robots, livestock monitoring, detection of predators, navigation in livestock buildings, monitoring animal health and behavior. Smart technologies are also used in fish farming to create smart farms. In this mini review, we have tried to integrate advanced smart and robotic technologies for various agricultural operations.

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Publication Details

Journal
Agricultural Engineering/Inżynieria Rolnicza
Published
2025-01-01
DOI
https://doi.org/10.2478/agriceng-2025-0010
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Smart Solutions in Agricultural Robotics

Taras Hutsol, Iryna Horetska, Zbigniew Skibko, Anatolii Panchenko et al.
Agricultural Engineering/Inżynieria Rolnicza
Smart Agriculture and AI
article

Smart Solutions in Agricultural Robotics

Taras Hutsol, Iryna Horetska, Zbigniew Skibko, Anatolii Panchenko, Sergii Slobodian, Oksana Vasylenko, Nikolay A. Kiktev, Maciej Kuboń
article en

Abstract

Abstract The article contains an overview and prospects for the introduction of smart and robotic technologies in the agricultural industry. Today, robotization of agriculture and food technology is not a leading industry compared to robotization of other sectors of the economy. Analytical review of the global robotics market revealed that robots in the food industry account for 2% of the total, and robots for agricultural operations account for less than 1%. We analyzed global trends in robotization and the introduction of artificial intelligence in agriculture in various countries. A review of smart robotic technologies, in particular, smart sensors and actuators, the Internet of Things, cloud technologies, methods of data analysis, forecasting, classification, and image recognition using neural networks, is provided. Methods and means are considered in relation to both crop production and livestock production. Four main classes of intelligent technologies in agriculture were identified: robotics, Internet of Things, machine learning, and UAVs. In crop production, robots are common in harvesting, controlling weeds, processing trees, monitoring trees at different stages of the growing season, including leaf and fruit diseases, counting the number of flowers and fruits, and other operations. Identification of fruits, leaves, weeds, as well as diseases of fruits and leaves is performed using computer vision, and in recent years convolutional neural networks have become widespread. Field monitoring is performed using UAVs with subsequent image processing using spectral analysis methods. In livestock farming, smart technologies are represented by feeding and milking robots, livestock monitoring, detection of predators, navigation in livestock buildings, monitoring animal health and behavior. Smart technologies are also used in fish farming to create smart farms. In this mini review, we have tried to integrate advanced smart and robotic technologies for various agricultural operations.

Agricultural Engineering/Inżynieria RolniczaVol. 29(1)
Bialystok University of Technology (PL), National University of Life and Environmental Sciences of Ukraine (UA), University of Agriculture in Krakow (PL), Kamianets-Podіlskyi Ivan Ohiienko National University (UA), Odesa State Agrarian University (UA), Anhalt University of Applied Sciences (DE), Dmytro Motornyi Tavria State Agrotechnological University (UA), Państwowa Akademia Nauk Stosowanych w Przemyślu (PL)
Zero hunger
Openalex Percentile: Top 90%
Smart Agriculture and AI
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