Adaptive Computing System for Distributed Process Control

Victor Ababii, Viorica Sudacevschi, Rodica Braniste, Ana Turcan, Constantin Ababii, Silvia Munteanu

Abstract


This paper is dedicated to solve some issues related to climate change that negatively affect the productivity and quality of agricultural products. Agricultural production processes are spatially distributed processes and require a special approach in the development of control systems. The paper proposes the development of an adaptive computing system based on Intelligent Agents. Two types of Agents are defined with functions of perceiving the controlled process and with functions of action on the process. The set of Agents forms a mesh network that ensures the communication between them in order to exchange the decisions taken by each Agent. The decisions generated by the multitude of Agents are based on the application of the knowledge and mathematical models on which the Fuzzy Logic and the Neural Networks are based. The functionality of the Agents and the system as a whole is demonstrated on the basis of the functional schemes and the sequence diagram specifying the mode of communication and the sequence of operations performed by the set of Agents. The adaptation of the system to the agricultural production process takes place by updating the knowledge at each decision-making cycle.


Keywords


Climate change, Intelligent Agents, Intelligent Agriculture, Distributed Process, Fuzzy Logic, Neural Networks.

Full Text:

PDF

References


Niemeyer S., Petts J., Hobson K. Rapid Climate Change and Society: Assessing Responses and Thresholds. Risk Analysis, Vol. 25, No. 6, 2005, pp. 1443-1456. DOI: 10.1111/j.1539-6924.2005.00691.x.

Hobson K., Niemeyer S. Public responses to climate change: The role of deliberation in building capacity for adaptive action. Global Environmental Change, Vol. 21, Issue 3, August 2011, pp. 957–971. DOI: 10.1016/j.gloenvcha.2011.05.001.

Lidskog R., Elander I., Standring A. COVID-19, the Climate, and Transformative Change: Comparing the Social Anatomies of Crises and Their Regulatory Responses. Sustainability 2020, 12, 6337. pp. 1-21. DOI: 10.3390/su12166337.

Russell S., Norving P. Artificial Intelligence: A Modern Approach. 3rd Edition. Prentice Hall, 2009. 1133p.

Wooldridge M. An Introduction to Multi-Ageent Systems. 2nd ed. England: John Wiley & Sons, 2009. p. 453.

Duan Yan-e. Design of Intelligent Agriculture Management Information System Based on IoT. In Proceedings of the Fourth International Conference on Intelligent Computation Technology and Automation, 2011. pp. 1045-1048. DOI: 10.1109/ICICTA.2011.262.

Siddique A., Prabhu B., Chaskar A., Pathak R. A Review on Intelligent Agriculture Service Platform with LORA based Wireless Sensor Network. International Research Journal of Engineering and Technology (IRJET), Vol. 06, Issue 02, Feb 2019, pp. 2539-2542. ISSN: 2395-0072.

Bagal S., More T., Paranjape A., Yadav S. Intelligent Architecture Mechanism using Internet of Things and Image Processing. International Journal of Trend in Scientific Research and Development (IJTSRD). Vol 3, Issue 2, Jan-Feb 2019, pp. 798-800. ISSN: 2456-6470.

Dhekane A., Chavan R., Chavan A., Thakur P. Survey on Intelligent IoT Based System for Agriculture. International Journal of Innovative Research in Technology (IJIRT). Vol. 6, Issue 7, Dec 2019, pp. 229-232. ISSN: 2349-6002.

Safonov Gh., Ababii V., Sudacevschi V. Analysis of distributed computing architectures for synthesis of multi-agent systems. European Applied Sciences Journal, № 9 2016 (September), pp. 34-37, ISSN 2195-2183.

Ababii V., Sudacevschi V., Safonov Gh. Designing a Collective Agent for synthesis of Adaptive Decision-Making Systems. Sciences of Europe (Praha, Chech Republic), Vol. 1, No 17(17), 2017, pp. 70-75, ISSN 3162-2364.

Ababii V.; Sudacevschi V.; Melnic R.; Munteanu S. Multi-Agent System for Distributed Decision-Making. National Science Journal (Ekaterinburg, Russia), Vol. 2, No 45, 2019, pp. 19-23, ISSN 2413-5291. DOI: 10.31618/nas.2413-5291.2019.2.45.

Ababii V., Sudacevschi V., Alexei V., Melnic R., Bordian D., Nistiriuc A. Fuzzy Sensor Network for Mobile Robots Navigation. In Proceedings of the 12th International Conference and Exibition on Electromecanical and Energy Systems, SIELMEN-2019, 9 October 2019, Craiova, Romania, 10-11 October 2019, Chisinau, Republic of Moldova, pp. 540 – 543. DOI: 10.1109/SIELMEN.2019.8905829, (IEEE: https://ieeexplore.ieee.org/document/8905829).

Ababii V., Sudacevschi V., Osovschi M., Turcan A., Nistiriuc A., Bordian D., Munteanu S. Distributed System for Real-Time Collective Computing. In Proceedings of the Fifth Conference of Mathematical Society of Moldova, IMCS-2019, September 28 – October 1, 2019, Chisinau, Republic of Moldova, pp. 267-274. ISBN 978-9975-68-378-4.

Sudacevschi V., Ababii V., Munteanu S. Distributed Decision-Making Multi-Agent System in Multi-Dimensional Environment. ARA Journal of Sciences, 3/2020, pp. 74-80, ISSN 0896-1018.

https://create.arduino.cc/projecthub/ (Accesed: 15.08.2020).


Refbacks

  • There are currently no refbacks.


Copyright (c) 2020 Victor Ababii, Viorica Sudacevschi, Rodica Braniste, Ana Turcan, Constantin Ababii, Silvia Munteanu

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.