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Wan Nor Munirah Ariffin
Preferred name
Wan Nor Munirah Ariffin
Official Name
Wan Nor Munirah, Ariffin
Alternative Name
Munirah, Wan Nor
Ariffin, Wan Nor Munirah
Ariffin, W. N.M
Main Affiliation
Scopus Author ID
56442390400
Researcher ID
FMB-9023-2022
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1 - 2 of 2
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PublicationBioeconomy sustainability integrating circular economy principles with big data and IoT for sustainable farming in agriculture 4.0( 2024-07)
;Ahmad Tajudin BaharinThis concept paper explores the synergy between Bioeconomy sustainability and advanced technologies, specifically the integration of circular economy principles with big data and the Internet of Things (IoT), in the context of sustainable farming within Agriculture 4.0 in Malaysia. Despite limited understanding, the study aims to unveil the potential benefits of this integration and assess the current state of technology adoption, bioeconomic practices, and sustainable farming in Malaysia. Challenges faced by Malaysian farmers, such as awareness gaps and resistance to change, are identified, and strategies, including targeted education and financial incentives, are proposed to overcome these barriers. While acknowledging potential limitations in universality due to data access constraints and the dynamic nature of technology and agriculture, the study emphasizes the importance of integrating these innovative approaches to propel Malaysian agriculture toward sustainability within the Agriculture 4.0 framework. -
PublicationReview Study of Image De-Noising on Digital Image Processing and Applications( 2023-03-01)
;Abdulah C.S.K.Jamil M.K.M.This paper reviews several studies of image de-noising on digital image processing and applications. Noisy images contain different noise that exist either due to environment or electronic interferences. Ergo, de-noising is crucial to eliminate the noise that disturb data collecting process. The impact of de-noising on image processing can result for accurate and precise data collected from the image. Additionally, de-noising process required several crucial steps that help to enhance knowledge on digital image and its application. Hence, study and understanding de-noising can improve multiple aspect such as image quality, data sensitivity and specificity, accuracy of the collected data, and increase the percentage of each parameter.1