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p-Index From 2021 - 2026
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This Author published in this journals
All Journal Journal of Innovation in Applied Natural Science Journal on Informatics Visualization and Social Computing
Anwar Ali Sathio
Benazir Bhutto Shaheed University
Aerospace Engineering Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Energy Environmental Science Immunology & microbiology Materials Science & Nanotechnology Mathematics Physics

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Renewable Energy Systems of Smart Grids and DL scheme Anwar Ali Sathio; Tehreem Hingora; Raja Vavekanand; Sameer Ali
Journal of Innovation in Applied Natural Science Vol. 2 No. 1 (2026): Journal of Innovation in Applied Natural Science
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jinas.v2i1.153

Abstract

Background: Solar energy systems are expanding rapidly, which increases the need for efficient power extraction and accurate power forecasting. Conventional maximum power point tracking methods show reduced performance under varying meteorological conditions, which leads to power losses. Machine learning offers data driven models that adapt to changing environmental patterns and improve system performance. Aim and Scope: The study aims to enhance solar power harvesting and forecasting through machine learning techniques. Multiple predictive models are evaluated to identify reliable approaches for photovoltaic system applications. Methodology: Solar and meteorological datasets were preprocessed through data cleaning, removal of missing values, and extraction of time based features to support time series modeling. Linear regression, random forest, and artificial neural network models were trained and evaluated through mean absolute error, root mean square error, coefficient of determination, and graphical performance analysis to achieve accurate solar power prediction and effective maximum power point tracking. Results: The proposed framework improves solar power collection and contributes to grid stability. Machine learning based models demonstrate fast and accurate maximum power point tracking with consistent power output and improved efficiency. Conclusion: The integration of intelligent control and machine learning techniques enhances the efficiency and reliability of solar energy systems. The proposed approach supports increased power generation, improved grid stability, and stronger sustainability of renewable energy utilization
Next-Generation Digital Twin UX: IoT-Driven Smart and Interactive Design ANWAR ALI SATHIO; MUHAMMAD MALOOK RIND; SAMEER ALI
Journal on Informatics Visualization and Social Computing Vol. 1 No. 1 (2025): Journal on Informatics Visualization and Social Computing (JIVSC)
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jivsc.v1i1.106

Abstract

Background of study: The rapid development of IoT-enabled systems has transformed user interaction by enabling intelligent, responsive, and interconnected digital environments. However, existing studies often emphasize traditional usability factors while overlooking emerging interaction attributes essential for next-generation Digital Twin and IoT-based interfaces. Aims and scope of paper: This study aims to investigate next-generation Digital Twin user experience (UX) by exploring interactive IoT design attributes, including gesture-based interaction, gaze tracking, multimodal interfaces, and AR-assisted usability. The research also develops an enhanced usability framework that integrates efficiency, cognitive load, and user satisfaction metrics. Methods: Using a mixed-method approach, the study integrates quantitative evaluations (task completion time, error rates) and qualitative assessments (NASA-TLX, SUS). Data were collected from open-source IoT usability datasets and supported by prototype testing, including touch-based, voice-assisted, gesture-controlled, and AR-enhanced interfaces. Result: Findings show that AR-enhanced and touch-based interfaces significantly improve task efficiency, reduce cognitive load, and increase user satisfaction. Gesture-based systems, while offering immersive interaction, exhibit higher error rates and cognitive strain. Users also expressed concerns regarding data security and interface complexity in IoT-enabled environments. Conclusion: IoT-enabled Digital Twin interaction offers substantial improvements in usability and engagement, particularly through AR and touch-based designs. However, challenges persist in gesture accuracy, voice recognition consistency, and privacy risks. This research establishes a structured framework for future IoT-UX development, emphasizing adaptive, intuitive, and user-centered design principles.
The IoT-enabled Interactive Design Investigation in User-Centered Design MUHAMMAD MALOOK RIND; ANWAR ALI SATHIO; SHAFIQUE AHMED AWAN; GHULAM AHMED
Journal on Informatics Visualization and Social Computing Vol. 1 No. 1 (2025): Journal on Informatics Visualization and Social Computing (JIVSC)
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jivsc.v1i1.107

Abstract

Background of study: IoT enabled systems such as mobile phones, smart homes, and medical applications play a significant role in improving convenience and usability in everyday life. The combination of IoT networks with graphical user interface designs, including websites and online applications, continues to grow rapidly. Despite this progress, interactive usability challenges remain, especially in aligning IoT technologies with human centered interaction principles. Aims and scope of paper: This study explores the usability of interactive design and identifies new attributes that contribute to improving user experience in IoT enabled systems. It aims to classify logical and physical attributes that influence usability and to propose new interactive dimensions for IoT based design. Methods: The study uses a descriptive and analytical approach based on a review of relevant literature and conceptual analysis. Logical and physical usability attributes were examined to understand their roles in interactive design and user experience across IoT environments. Result: The results reveal that two major factors, logical and physical attributes, are fundamental to interactive design. These attributes can guide new rules for IoT based usability, expanding human computer interaction beyond traditional interfaces such as keyboard, mouse, and screen, and including motion, gaze, and posture as part of new interaction mechanisms. Conclusion: This study focuses on interface usability to help developers create more attractive and user friendly designs. The findings open new research areas in interactive IoT systems and contribute to the development of adaptive, efficient, and human oriented interface design principles for future IoT applications.
Co-Authors GHULAM AHMED MUHAMMAD MALOOK RIND Raja Vavekanand Sameer Ali Sameer Ali SHAFIQUE AHMED AWAN Tehreem Hingora