Intelligent System for Management of Agricultural Processes

The social systems have faced more challenges over the last decades – increase in population and consumption, deficit of natural recources, environmental pollution, climate changes, more frequent natural disasters, more aggressive diseases on humans, animals and plants.

Science, education, traditions, innovations and new technologies must be united in a conceptual frame for achieving long-term sustainable development and prosperity at micro and macro level.

The resource base of agricultural manufacturing is limited. A large part of the production factors in use are exhaustible and unrenewable (mineral oil, natural gas, coal). Some of the incoming resources are renewable but at particular exploitation conditions. Still, there are not enough effective technologies for transition to unrenewable natural resources (solar, wind, or earth energy).

The capital resources have the biggest potential for development in the next years (innovative machines and technologies), as well as human resources (new knowledge, skills, practices). Modern technologies use natural resources more rationally and more effectively turning them into desired products. In the future they will allow the increase of productivity of a resource unit, they will minimize losses from the improper use of fertilizers and preparations, they will limit the environmental pollution, they will decrease the necessity of physical work.

A basis for each project development in agriculture is the technological cards, which give the technology and resources for the production of a particular agricultural product. The technological cards give relatively constant information for the cultivation of a given crop – agrotechnical terms for the operations, the number, and duration of working days, the composition of the machine-tractor aggregate (MTA) or a robotized drone system, the necessary number of working machines, the necessary number of workers and mechanics, allowances for depreciation of the machinery, labour and energy expenses, materials expenses, etc.

Preservation of the biological diversity and ecosystems is directly related to the applied agricultural practices in the different types of crops. The interest to cultivate medicinal and etheric-oil plants, as well as cereal and orchard crops in Bulgaria has increased in the last few years.

In the conditions of intensive pomiculture (fruit-growing), there is success in the production process based on the best-quality planting material. In relation to this, important conditions for the production of apple root-stocks in uterine planting are the air and water regime of soil and its supply with organic substance.
Today, along with the dominating intensification and bioproduction in fruit-growing, another important factor is the quality of the source material. There should be no compromises in this respect. Therefore, soil conditions play a main role – a factor for good rooting and high quality of material, respectively. Over the last years researchers of the Agricultural University – Plovdiv have successfully realized numerous projects on the optimization of different stages in apple production. It has been proved that there is a potential for improving the technical and economical results in the formation of planting material, as well as in fruit-tree cultivation. Furthermore, the innovative approaches in cultivation have a positive effect on the ecosystems. The environmental pollution has been reduced, the water necessity has been lowered, a number of ecosystem indicators have been improved.

Optimization is a purposeful activity for obtaining the best result in a particular meaning and particular conditions.

For this reason, the use of mathematical methods for the analysis and synthesis of complex systems is necessary, as well as scientific-reasoned solutions in production management (Ivanova, 2019).

There are a number of programs and applications for solving optimization problems – SPSS, Statistica, MS Excel, TRIZ, etc.

The research work is most often related not to the objects under study, but to their models. The mathematical model of a particular object is its description by means of mathematics and the use of regularities from one or several sciences with the chosen description aspect.

For one year in the National Institute for Meteorology and Hydrology (NIMH) there has been working a fоrecast system in order to evaluate the conditions for plant protection activities using the information of the European Center for Medium-Range Weather Forecasts within 5 days forward. http://agro.meteo.bg/bg/asenovgrad. It is possible that the forecast period could be expanded to 10 days. In this case, the possibility for realization decreases. A global numerical model works in ECMWF, which does a weather forecast for the whole earth globe. Within this program, the ALADIN regional numerical forecast model will be used to give forecast information within 72 hours in advance. The information is updated 4 times per day.

Within the present project, the team aims at expanding the research demands. There will be developed sustainable technological models for the production of wheat, coriander, and apple rootstocks with the application of different optimization methods for their digitalization.

Cloud technology will be developed in order to exchange data in real time through the environment of Dassoul systems. A system for management of the working processes will be created, which will receive information from DASSOULT SYSTEMS cloud. The team will explore the coordination between the separate system units (irrigation, spraying, weeding, fertilization, etc.) depending on the diagnosis data of the fauna and microclimate. There is an idea for creating optimum algorithms for the management of the separate working processes in the cultivation of wheat, coriander and the production of apple root-stocks, and these algorithms to be integrated in drones or robots.

This will be combined with the opportunities of DASSOULT SYSTEMS and the information technologies. A database will be created consisting of ready solutions (artificial intelligence), which will help people – producers of wheat, coriander and planting material for apple plantations.

These models will be based on the gained past experience of the scientific team, as well as the opportunities of the new technologies.