[vc_row][vc_column][vc_column_text]<\/p>\n
[\/vc_column_text][vc_tta_tour][vc_tta_section title=”\u0410\u043d\u043e\u0442\u0430\u0446\u0438\u044f” tab_id=”1547399039570-cd4ef4e9-e6dc”][vc_column_text]Increasing the planet’s population poses a serious problem with its nutrition. Agriculture is the sector responsible for this task. One way to tackle this problem is to find new ways to improve the efficiency of agriculture. A major problem is the provision of labor. In countries where this is difficult, production is more expensive than the cost of hiring workers. However, in these countries there is a high production yield and a tendency to automate work processes. Automation can take place both during the entire period of crop cultivation and in the harvesting and storage of production.
\nThe use of robots in agriculture is not a new idea. There are developments in agricultural machinery without human intervention, but they can take on the complex real world with all modern technology. Therefore, these machines are used in agriculture with great success. The current understanding is to create intelligent machines that are capable of making independent decisions and operating in the natural environment without taking over the human control functions. At the same time, these machines must be capable of operating for an extended period of time without supervision.
\nThere is a wide range of technologies that are used in robots and lead to the possibility of a rapid transition of Industry 4.0 to enter the agricultural activity through robotics. Some technologies will need to be developed specifically for agriculture, while other technologies have already been developed for other areas can be adapted to the agricultural domain, such as autonomous vehicles, artificial intelligence and machine vision. Here, however, it is necessary to use the different capabilities and current state of various enabling technologies from hardware to software, multi-robot systems and humanrobot inteligents systems.
\nOur main goal is to provide an innovative solution to support farmers in order to optimize the working processes and reduce the influence of the human factor on Bulgarian farms. The modern development of IoT and the entry of Industry 4.0 into the agricultural sector should help simplify and diagnose individual diseases and carry out the necessary operations with a minimum of means.
\nDifferent models of application will be developed in the forecasting and management of farm processes. A model of the aquatic state of plants will be created and no irrigation regime of tomatoes will be predicted for precise irrigation. A system for the study and collection of microclimate data in vegetable cultivation will also be developed.
\nOn the other hand, at the current rate of development of climate change, snow cover has decreased in recent years, which negatively affects crops. The assessment of the snow cover and snow water equivalent is an important parameter for agroproteics.
\nPlant production is an area where activities and efficiency directly depend on the current and correct data on the state of the environment, the crops grown and the work of the service equipment. The monitoring and analysis process is key to achieving optimal results. In this context, the development of such a local field network of IoT will increase communication between the ground or air equipment implementing units with which data is collected and the server through which artificial intelligence communicates between the different units and monitors the correct execution of operations.[\/vc_column_text][\/vc_tta_section][vc_tta_section title=”\u041d\u0430\u0443\u0447\u043d\u0438 \u0437\u0430\u0434\u0430\u0447\u0438” tab_id=”1547399039592-c0893926-4bf3″][vc_column_text]<\/p>\n
SCIENTIFIC TASKS:<\/p>\n
1.1.1. Research on the energy independence and quality of operations carried out using robotic technologies in the cultivation of crops and equipment in a universal agricultural robot<\/strong><\/em><\/p>\n ACTIVITIES 1.1.2. Exploring the capabilities of artificial intelligence to determine the accuracy and coordination of an agricultural robot in positioning and movement through a navigation system and digital vision.<\/strong><\/em><\/p>\n ACTIVITIES 1.1.3. Development of advanced technologies for monitoring soil and crop parameters.<\/strong><\/em><\/p>\n ACTIVITIES
\n\u2022 Design of an agricultural robot.
\n\u2022 Production and functional tests of an agricultural robot.
\n\u2022 Study of the resistance of an agricultural robot when moving in polish conditions.
\n\u2022 Study of the energy independence of an agricultural robot when carrying out work operations.
\n\u2022 Examination of the quality of the work operations carried out.<\/p>\n
\n\u2022 Integration of a global satellite radio navigation system (GSRS) GALILEO receiver to the agrorobot navigation system.
\n\u2022 Study of the accuracy of an agrorobot in determining its location by using different GSCI (NAVSTAR-USA, GLONASS-Russia, GALILEO-EU) or in their joint use.
\n\u2022 Development of a methodology for determining the space-time characteristics of constellations of navigation satellites and their accessibility when sharing the NAVSTAR-USA, GLONASS-Russia, GALILEO-EU GSCI.
\n\u2022 Develop a 3D model of the area (field) using drone-orthophotogrametry technology and visualization of the agrorobot according to its GPS data.
\n\u2022 Installation of the elements of digital vision of the robot.
\n\u2022 Coordination and optimization of the movement of the robot to the resulting position by working together on the navigation system, the map from the locality model and the images from the digital vision of the robot.
\n\u2022 Develop an algorithm to create a computer program to select a turning trajectory and generate a turning strip when moving an autonomous agricultural ro\u2022 Integration of a global satellite radio navigation system (GSRS) GALILEO receiver to the agrorobot na\u2022 Integration of a global satellite radio navigation system (GSRS) GALILEO receiver to the agrorobot navigation system.
\n\u2022 Study of the accuracy of an agrorobot in determining its location by using different GSCI (NAVSTAR-USA, GLONASS-Russia, GALILEO-EU) or in their joint use.
\n\u2022 Development of a methodology for determining the space-time characteristics of constellations of navigation satellites and their accessibility when sharing the NAVSTAR-USA, GLONASS-Russia, GALILEO-EU GSCI.
\n\u2022 Develop a 3D model of the area (field) using drone-orthophotogrametry technology and visualization of the agrorobot according to its GPS data.
\n\u2022 Installation of the elements of digital vision of the robot.
\n\u2022 Coordination and optimization of the movement of the robot to the resulting position by working together on the navigation system, the map from the locality model and the images from the digital vision of the robot.
\n\u2022 Develop an algorithm to create a computer program to select a turning trajectory and generate a turning strip when moving an autonomous agricultural ro\u2022 Integration of a global satellite radio navigation system (GSRS) GALILEO receiver to the agrorobot navigation system.
\n\u2022 Study of the accuracy of an agrorobot in determining its location by using different GSCI (NAVSTAR-USA, GLONASS-Russia, GALILEO-EU) or in their joint use.
\n\u2022 Development of a methodology for determining the space-time characteristics of constellations of navigation satellites and their accessibility when sharing the NAVSTAR-USA, GLONASS-Russia, GALILEO-EU GSCI.
\n\u2022 Develop a 3D model of the area (field) using drone-orthophotogrametry technology and visualization of the agrorobot according to its GPS data.
\n\u2022 Installation of the elements of digital vision of the robot.
\n\u2022 Coordination and optimization of the movement of the robot to the resulting position by working together on the navigation system, the map from the locality model and the images from the digital vision of the robot.
\n\u2022 Develop an algorithm to create a computer program to select a turning trajectory and generate a turning strip when moving an autonomous agricultural robot in an irregularly shaped field.
\n\u2022 Design and modeling of an autonomous system with increased accuracy and ground station for the management of a coaxial helicopter for agricultural purposes.
\nDevelop machine learning algorithms that are based on information from large databases that are derived from the digital vision of the helicopter for agricultural purposes.
\n\u2022 Create a protocol for collecting and analyzing a large amount of data for the detection of plant pests through the digital vision of the helicopter for agricultural purposes.
\n\u2022 Monitoring the quality of the operations performed through the digital vision of the robot and helicopter.<\/p>\n
\n\u2022 Development of a methodology for examining the relationship between the color of the leaves of greenhouse tomato plantations (and other greenhouse vegetables) and microclimatic parameters (soil moisture and temperature).
\n\u2022 Research and selection of digital color components under different quality factors in greenhouse tomato plantations (before\/after watering, young\/old leaves).
\n\u2022 Create digital models using standard statistical methods using data mining and mashine learning algorithms in greenhouse tomato plantations.
\n\u2022 Forecasting soil moisture (the need for watering) based on leaf color, soil temperature and quality factors (based on models created) when growing greenhouse tomatoes.
\n\u2022 Development of an alternative methodology for remote monitoring of the microclimate in Polish tomato production.
\n\u2022 Remote monitoring of the microclimate in Polish tomato production through the various phenophases and the manifestation of diseases.
\n\u2022 Modeling of snow coating parameters.
\n\u2022 Analysis of the snow coating relationship (Globsnow) and crop development through satellite measurements of the Finnish Space Agency.
\n\u2022 Analysis of calculated snow water equivalent, snow cover and duration with the developed model using satellite data of the Copernicus Land Monitoring Services program.<\/p>\n