TY - JOUR
T1 - ISOF
T2 - Information Scheduling and Optimization Framework for Improving the Performance of Agriculture Systems Aided by Industry 4.0
AU - Manogaran, Gunasekaran
AU - Hsu, Ching Hsien
AU - Rawal, Bharat S.
AU - Muthu, Balaanand
AU - Mavromoustakis, Constandinos X.
AU - Mastorakis, George
N1 - Funding Information:
Manuscript received May 5, 2020; revised August 28, 2020 and November 23, 2020; accepted November 30, 2020. Date of publication December 17, 2020; date of current version February 19, 2021. This work was partially supported by the National Natural Science Foundation of China under Grant 61872084. (Corresponding author: Ching-Hsien Hsu.) Gunasekaran Manogaran is with the Department of Computer and Information Science, University of California, Davis, Sacramento, CA 95833 USA, and also with the College of Information and Electrical Engineering, Asia University, Taichung 41354, Taiwan (e-mail: [email protected]).
Publisher Copyright:
© 2014 IEEE.
PY - 2021/3/1
Y1 - 2021/3/1
N2 - Industry 4.0 is a promising evolution in the field of smart farming by improving the productivity and reducing human intervention to modernize agriculture. This smart paradigm incorporates different levels of the automation from cropping to production yield through sophisticated techniques. Different intelligent computing techniques and communication technologies are augmented with the industry paradigm for improving the efficiency of agriculture systems. This letter introduces information scheduling and optimization framework (ISOF) for optimizing the communication and information layer process in industry 4.0 architecture. Information scheduling and classification of agriculture information are optimized through this framework for reducing process latency and stagnancy. The control flexibility of a smart farm is determined using the latency and stagnancy at the end of yields. The classification part segregates information based on processing and completion time to reduce backlogs through offloading process. The advantage of this framework is that it inherits the advantages of Internet of Things (IoT) and edge computing (EC) technologies with interoperable feature to aid information processing, information classification, offloading, and periodic updates. The performance of the proposed framework is tested in a corn farm and some common metrics, such as delayed information, processing time, audit data, and information distribution, are analyzed for proving the reliability of the framework.
AB - Industry 4.0 is a promising evolution in the field of smart farming by improving the productivity and reducing human intervention to modernize agriculture. This smart paradigm incorporates different levels of the automation from cropping to production yield through sophisticated techniques. Different intelligent computing techniques and communication technologies are augmented with the industry paradigm for improving the efficiency of agriculture systems. This letter introduces information scheduling and optimization framework (ISOF) for optimizing the communication and information layer process in industry 4.0 architecture. Information scheduling and classification of agriculture information are optimized through this framework for reducing process latency and stagnancy. The control flexibility of a smart farm is determined using the latency and stagnancy at the end of yields. The classification part segregates information based on processing and completion time to reduce backlogs through offloading process. The advantage of this framework is that it inherits the advantages of Internet of Things (IoT) and edge computing (EC) technologies with interoperable feature to aid information processing, information classification, offloading, and periodic updates. The performance of the proposed framework is tested in a corn farm and some common metrics, such as delayed information, processing time, audit data, and information distribution, are analyzed for proving the reliability of the framework.
UR - http://www.scopus.com/inward/record.url?scp=85098768683&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85098768683&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2020.3045479
DO - 10.1109/JIOT.2020.3045479
M3 - Article
AN - SCOPUS:85098768683
SN - 2327-4662
VL - 8
SP - 3120
EP - 3129
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 5
M1 - 9296855
ER -