Open Access
| Issue |
SHS Web Conf.
Volume 216, 2025
International Conference on the Impact of Artificial Intelligence on Traditional Economic Sectors (ICIAITES 2025)
|
|
|---|---|---|
| Article Number | 01004 | |
| Number of page(s) | 9 | |
| Section | Intelligent Systems and Digital Transformation in Agricultural Economy and Sustainable Development | |
| DOI | https://doi.org/10.1051/shsconf/202521601004 | |
| Published online | 23 May 2025 | |
- P.M. Chukwu, B.A. Adewumi, I.A. Ola, O.D. Akinyemi, Development and Testing of a Coconut Dehusking Machine. Agric. Mech. Asia, Afr. Lat. Am. 51(1), 29 (2020) [Google Scholar]
- B. Tiko, A. Mohamed, Evaluating the Knowledge and Perceptions of Local Farmers in Tanam Village, Morobe Province Regarding Fall Armyworm Infestation, in Proceedings of the International Conference on Smart Technologies and Applied Research (STAR'2023), E3S Web Conf. 477, 00021 (2024). https://doi.org/10.1051/e3sconf/202447700021 [Google Scholar]
- M.A. Azlan, M.F. Ahmad, M.A. Jamaludin, Preliminary Design Concept of Coconut Dehusker Machine. J. Des. Sustain. Environ. 2(1) (2020) [Google Scholar]
- M.F.M. Yunus, S.N.T.M. Yasin, N.K.S.M. Fadzli, S.N.B. Suhaimi, N.H. Zainuddin, Conceptual design of dual purpose coconut dehusking machine. Southeast Asian J. Technol. Sci. 1(2), 42–47 (2020) [Google Scholar]
- M.F.A. bin Istas Fahrurrazi, I. Fahrurrazi, M.A.A. bin Mohd Nasir, A.A. bin Kamal, Coconut Dehusking Machine. Multidiscip. Appl. Res. Innov. 3(1), 565–576 (2022) [Google Scholar]
- B.J. Olorunfemi, A.E. Olumilua, S.E. Kayode, A.A. Arounsoro, Development of a Modified Dehusking Machine for Local Varieties of Coconut. Covenant J. Eng. Technol. (2022) [Google Scholar]
- I. Lekakali, R. Taniyaola, L. Lee, O. Renagi, A. Mohamed, Plan for Developing a Cost-Effective and Sustainable Sago Machine to Increase Productivity and Ingenuity. Eng. Proc. 66, 039 (2024). https://doi.org/10.3390/engproc2024066039 [Google Scholar]
- N.V. Anilbhai, Development of dry coconut dehusking and deshelling machine. Master Thesis, India (2022) [Google Scholar]
- T.M. Langi, Performance of several coconut coir peeling tools for peeling efficiency in coconut production centers. Afr. J. Food Agric. Nutr. Dev. 24(11) (2024) [Google Scholar]
- V.A. Naliapara, V.M. Sejani, N.U. Joshi, Design of dry coconut (Cocos nucifera L.) dehusking and deshelling machine components using solidworks simulation. J. Appl. Hortic. 25(1), 104–109 (2023) [CrossRef] [Google Scholar]
- R. Pandiselvam, M.R. Manikantan, D. Balasubramanian, P.S. Beegum, A.C. Mathew, S.V. Ramesh, V. Niral, Mechanical properties of tender coconut (Cocos nucifera L.): Implications for the design of processing machineries. J. Food Process Eng. 43(2), e13349 (2020) [CrossRef] [Google Scholar]
- A.M. Taufik, H.M. Akhir, Performance evaluation of coconut dehusking machine. (2014) [Google Scholar]
- J.O. Adedipe, Enhancing Coconut Processing Efficiency: Design and Evaluation of A Cost-Effective Coconut De-Husking Machine. J. Riset Perkebunan 5(2), 94–102 (2024) [CrossRef] [Google Scholar]
- M.S. Sheela, S. Gopalakrishnan, I.P. Begum, J.J. Hephzipah, M. Gopianand, D. Harika, Enhancing Energy Efficiency with Smart Building Energy Management System Using Machine Learning and IOT. Babylon. J. Mach. Learn. 2024, 80–88 (2024) [CrossRef] [Google Scholar]
- B.R. Palao, J. Honra, Development and Performance Evaluation of a Coconut Dehusking Machine, in Proceedings of the 2022 IEEE 13th International Conference on Mechanical and Intelligent Manufacturing Technologies (ICMIMT), 247–252 (2022) [Google Scholar]
- A. Mohamed, U. Mogili, Developments of models of tooling for machining centers. AIP Conf. Proc. 2917(1), 040004 (2023). https://doi.org/10.46254/an13.20230681 [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.