Methods and Tools for Designing a Multi-Service Platform for Agricultural Enterprises
Petr Skobelev1, Igor Mayorov2, Dmitry Novichkov3, Elena Simonova4

1Petr Skobelev, Professor, Department of Electronic Systems and Information Security, Samara State Technical University, Samara, Russia.
2Igor Mayorov, Ph.D., Chief Engineer, Institute for the Control of Complex Systems of Russian Academy of Sciences, University, Samara, Russia.
3Dmitry Novichkov, Software Developer, Aeropatrol, Ltd., Russian Federation, 443013 Samara, Moskovskoe shosse 17, Business center “Vertical”, office 35,
4Elena Simonova*, Ph.D., Associate Professor, Department of Information Systems and Technologies, Samara National Research University, Samara, Russia.
Manuscript received on November 22, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 1660-1667 | Volume-9 Issue-2, December, 2019. | Retrieval Number:  B3267129219/2019©BEIESP | DOI: 10.35940/ijeat.B3267.129219
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Abstract: The paper dwells on the problems of developing an internet platform for support of decision-making and production management for an agricultural enterprise. The described system is an open environment which is capable of integrating third-party services with the application-programming interface (API), each service being an autonomous software component (agent) with its own criteria and target. Thus, planning is done through continuous interaction of agents within the multi-service platform, using the knowledge base for storing various data on crops, such as conditions of crop growing, characteristics and peculiarities of crop production, pests, plant diseases, soil types and their specific features, technological processes (maps) for crop growing, application of fertilizers and plant protection products, crop production economy, classes of agricultural machines and equipment. Thus, the result of scheduling is the work plan for a given time horizon. On top of that, the paper describes the first prototypes of smart services and their interaction, as well as the next steps for future research.
Keywords: Precision agriculture, Agricultural management, Decision-making support, Multi-agent coordination, Multi-service platform, Ontology.