Component 3 as a part of the NSP Intelligent Crop Production is related to the development of concepts, models and prototypes of intelligent systems for process management in crop production. To achieve the goals of the NSP, Component 3 includes four Work Packages:
WP 3.1. Intelligent system for crop growing technology management, WP Leader – Assoc. Prof. Velika Kuneva, PhD.
In this WP are defined the following scientific tasks:
• Identification of opportunities for digitalization of management processes in agriculture and development of multi-layered supporting infrastructure of intelligent agriculture in accordance with the specifics and dynamics of the sector.
• Development of a software environment for artificial intelligence for management of the work processes in agriculture through the “3D Experience” environment of “DASSOULT SYSTEMS”.
• Study of the coordination between the individual units of the work process management system (watering, spraying, weeding, fertilizing, etc.) depending on the data from the diagnostics of the vegetation and the microclimate.
• Development of algorithms for training of artificial intelligence to support the farmer by developing a basic scheme of the work processes depending on the crop grown and its subsequent adaptation.
WP 3.2. Convergence of the Internet of Things and Big Data in Intelligent Agricultural Process Management, WP Leader – Assoc. Prof. Katya Uzundzhalieva, PhD.
In this WP are defined the following scientific tasks:
• Study of the convergence of the digital and agricultural ecosystem in Bulgaria.
• Study of the data infrastructure for the transition to Bulgarian intelligent agriculture.
• Research of the quality of own and satellite data for intelligent plant growing.
• Study of the areas and trends in the application of machine self-learning in the technological and management processes in agriculture.
WP 3.3. Virtual Operations Centre for Overall Management of Intelligent Agriculture, WP Leader – Prof. Stanimir Stoyanov, PhD.
In this WP are defined the following scientific tasks:
• Development of the general architecture of the center.
• Components for analysis and decision making – presentation of knowledge in the field of agriculture, 3D and semantic modeling (soil, air, climate, plant physiology, developmental stages), machine learning technologies (including deep learning), cross-country technologies (virtual reality, augmented reality).
• Personal assistants for operators of intelligent agricultural applications and systems.
• Intelligent human-machine interfaces.
• Interfaces to external systems.
WP 3.4. Block Chains for Intelligent Agriculture, WP Leader – Assoc. Prof. Irina Radeva, PhD.
In this WP are defined the following scientific tasks:
• Research for the specification of appropriate applications of block chains as part of intelligent agriculture.
• Pilot block chains design for selected areas.
• Analysis and development of models for efficient block chains for intelligent agriculture.
The scientific team responsible for the implementation of scientific tasks is interdisciplinary and includes prominent scientists from the following scientific organizations: Agricultural University of Plovdiv, Bulgarian Academy of Sciences – Institute of Information and Communication Technologies and Space Research and Technology Institute, Agricultural Academy – Institute of Plant Genetic Resources – Sadovo (IPGR-Sadovo) and Maritsa Vegetable Crops Research Institute – Plovdiv, Nikola Vaptsarov Naval Academy and National Institute of Meteorology and Hydrology.
