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All Journal Indonesian Journal of Electrical Engineering and Computer Science Journal of Educational Technology and Learning Creativity
Herdawatie Abdul Kadir
Universiti Tun Hussein Onn Malaysia
Computer Science & IT Education

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Terminal sliding mode control on autonomous underwater vehicle in diving motion control Nira Mawangi Sarif; Rafidah Ngadengon; Herdawatie Abdul Kadir; Mohd Hafiz A. Jalil
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 2: November 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i2.pp798-804

Abstract

In this study, mechanism for reducing chattering in discrete conventional sliding mode controller (DSMC) for autonomous underwater vehicle (AUV) was designed in discrete time domain. The combination of reaching law approach and discrete terminal sliding mode control (DTSMC) scheme was employed to alleviate chattering effect caused by quasi sliding mode (QSM). First, 6 DOF NPS AUV II equation of motion is linearized to diving mode subsystem. Second, linear sliding surface in discrete time domain is designed and reaching law based (RLB) is employed to the control law. Thirdly, discrete nonlinear sliding surface, specifically DTSMC is designed to reduce chattering phenomena and improved precision control simultaneously. Finally, comparative experimental results are presented to illustrate the effectiveness and advantages of the nonlinear sliding surface.
AIoT-Based Digital Monitoring Architectures for Water Quality Index Forecasting: A Critical Media Technology Review Iffan Darwis Mohd Ibrahim; Herdawatie Abdul Kadir
Journal of Educational Technology and Learning Creativity Vol. 4 No. 1 (2026): June
Publisher : Cahaya Ilmu Cendekia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37251/jetlc.v4i1.2953

Abstract

Purpose of the study: This review critically evaluates AIoT-based digital monitoring architectures that integrate edge intelligence and Water Quality Index (WQI) forecasting, in order to identify how distributed media-technology infrastructures can support real-time, predictive, and policy-aligned water quality monitoring across urban and rural environments. Methodology: A PRISMA-guided critical review was combined with VOSviewer 1.6.20 bibliometric mapping. Peer-reviewed articles indexed in Scopus, Web of Science, IEEE Xplore, ScienceDirect, MDPI, and SpringerLink between 2015 and 2025 were systematically screened, quality-appraised using a six-criterion rubric, and thematically synthesised, complemented by a quantitative nine-dimensional technical-performance comparison framework across cloud, edge, hybrid, and federated architectures. Main Findings: Three persistent weaknesses were identified: urban-centric architectural bias, supervised-learning dependence incompatible with rural data scarcity, and weak alignment between AI analytics and regulatory indices. Bibliometric clustering revealed four dominant research themes which is IoT sensing, machine-learning forecasting, edge intelligence, and federated/adaptive analytics. A hybrid edge-cloud AIoT framework with quantitative performance benchmarks is proposed to resolve these gaps. Novelty/Originality of this study: Unlike prior reviews that treat smart water monitoring as a uniform technical problem, this study reframes it as a distributed media-technology challenge, introduces a bibliometric-supported urban-rural taxonomy of AIoT architectures, and explicitly maps AI model placement onto the six-parameter Malaysian WQI computation, converting predictive analytics into a regulatory decision-support instrument with documented system orchestration and technical workflow.
Co-Authors Iffan Darwis Mohd Ibrahim Mohd Hafiz A. Jalil Nira Mawangi Sarif Rafidah Ngadengon