Ontologies and Artificial Intelligence Systems for the Cooperative Smart Farming Ecosystem
| dc.contributor.author | Chukkapalli, Sai Sree Laya | |
| dc.contributor.author | Mittal, Sudip | |
| dc.contributor.author | Gupta, Maanak | |
| dc.contributor.author | Abdelsalam, Mahmoud | |
| dc.contributor.author | Joshi, Anupam | |
| dc.contributor.author | Sandhu, Ravi | |
| dc.contributor.author | Joshi, Karuna | |
| dc.date.accessioned | 2020-11-04T17:09:09Z | |
| dc.date.available | 2020-11-04T17:09:09Z | |
| dc.date.issued | 2020-09-08 | |
| dc.description.abstract | Cyber-Physical Systems (CPS) and Internet of Thing (IoT) generate large amounts of data spurring the rise of Artificial Intelligence (AI) based smart applications. Driven by rapid advancements in technologies that support smart devices, agriculture and farming sector is shifting towards IoT connected ecosystem to balance the increase in demand for food supply. As the number of smart farms reach critical mass, it is now possible to include AI assisted systems at a cooperative (co-op) farming level. Today, in the United States alone there are about 1,871 co-ops serving 1,890,057 member farmers. Hence, such advanced technologies and infrastructure when incorporated in the co-op farming ecosystem can immensely benefit small member farmers who operate and maintain these independent co-op entities. In this paper, we develop a connected cooperative ecosystem which defines sensors and their communication among different entities along with cloud supported co-op hub. We develop member farm and co-op ontologies to capture data and various interactions that happen between shared resources, member farms, and the co-op that are stored in the cloud. These can then help generate AI supported insights for farmers and the cooperative. Several co-op farming use case scenarios have been discussed to demonstrate the functioning of our smart cooperative ecosystem. Finally, the paper describes various AI applications that can be deployed at the co-op level to aid member farmers. | en_US |
| dc.description.sponsorship | The authors would like to thank Dr. B. Leckie and Dr. M. Best from the School of Agriculture, Tennessee Tech University. | en_US |
| dc.description.uri | https://ieeexplore.ieee.org/document/9187931 | en_US |
| dc.format.extent | 20 pages | en_US |
| dc.genre | journal articles | en_US |
| dc.identifier | doi:10.13016/m2tduf-egru | |
| dc.identifier.citation | S. S. L. Chukkapalli et al., "Ontologies and Artificial Intelligence Systems for the Cooperative Smart Farming Ecosystem," in IEEE Access, vol. 8, pp. 164045-164064, 2020, doi: 10.1109/ACCESS.2020.3022763. | en_US |
| dc.identifier.uri | https://doi.org/10.1109/ACCESS.2020.3022763 | |
| dc.identifier.uri | http://hdl.handle.net/11603/20011 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | IEEE | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.relation.ispartof | UMBC Student Collection | |
| dc.relation.ispartof | UMBC Information Systems Department | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
| dc.rights | Attribution 4.0 International | * |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | * |
| dc.title | Ontologies and Artificial Intelligence Systems for the Cooperative Smart Farming Ecosystem | en_US |
| dc.type | Text | en_US |