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Designing and Evaluating a Collaborative Knowledge Management Framework for Leaf Disease Detection7.47 MB
Published VersionCC BY V4.0, Open Access
Journal article
Designing and Evaluating a Collaborative Knowledge Management Framework for Leaf Disease Detection
Computer Systems Science and Engineering, Vol.42(2), pp.751-777
2022
Abstract
Knowledge Management (KM) has become a dynamic concept for inquiry in research. The management of knowledge from multiple sources requires a systematic approach that can facilitate capturing all important aspects related to a particular discipline, several KM frameworks have been designed to serve this purpose. This research aims to propose a Collaborative Knowledge Management (CKM) Framework that bridges gaps and overcomes weaknesses in existing frameworks. The paper also validates the framework by evaluating its effectiveness for the agriculture sector of Pakistan. A software LCWU aKMS was developed which serves as a practical implementation of the concepts behind the proposed CKMF framework. LCWU aKMS served as an effective system for rice leaf disease detection and identification. It aimed to enhance CKM through knowledge sharing, lessons learned, feedback on problem resolutions, help from co-workers, collaboration, and helping communities. Data were collected from 300 rice crop farmers by questionnaires based on hypotheses. Jennex Olfman model was used to estimate the effectiveness of CKMF. Various tests were performed including frequency measures of variables, Cronbach’s alpha reliability, and Pearson’s correlation. The research provided a KMS depicting KM and collaborative features. The disease detection module was evaluated using the precision and recall method and found to be 94.16% accurate. The system could replace the work of extension agents, making it a cost and time-effective initiative for farmer betterment.
Details
- Title
- Designing and Evaluating a Collaborative Knowledge Management Framework for Leaf Disease Detection
- Authors
- Komal Bashir (Author) - Lahore College for Women UniversityMariam Rehman (Author) - Government College University, FaisalabadAfnan Bashir (Corresponding Author) - University of the Sunshine Coast, Queensland, School of Law and SocietyFaria Kanwal (Author) - Lahore College for Women University
- Publication details
- Computer Systems Science and Engineering, Vol.42(2), pp.751-777
- Publisher
- C R L Publishing Ltd.
- Date published
- 2022
- DOI
- 10.32604/csse.2022.022247
- ISSN
- 0267-6192
- Copyright note
- This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Organisation Unit
- University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; School of Law and Society
- Language
- English
- Record Identifier
- 99608307602621
- Output Type
- Journal article
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web Of Science research areas
- Computer Science, Hardware & Architecture
- Computer Science, Theory & Methods
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Source: InCites