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SELLA: An IoT-based smart shopping trolley with real-time RFID tracking and automated checkout

10.12928/telkomnika.v24i1.27464
Hadj; Djillali Liabes University of Sidi Bel Abbes Zerrouki , Salima; Djillali Liabes University of Sidi Bel Abbes Azzaz-Rahmani
The contemporary retail sector faces a persistent challenge in enhancing in store customer experience, primarily due to inefficiencies at checkout. This paper presents smart e-cart for lean logistics application (SELLA), a smart shopping trolley system engineered to eliminate this bottleneck. The system’s architecture is centered on a Raspberry Pi 4 microcontroller, orchestrating an ultra-high frequency (UHF) radio frequency identification (RFID) subsystem for instantaneous, non-line-of-sight product identification, and a responsive 7-inch touchscreen graphical user interface (GUI) developed in PyQt. The core contribution lies in developing a self contained shopping solution with integrated payment processing, supported by comprehensive performance validation. We present a detailed methodology, including the system’s multi-threaded software architecture and core operational algorithm. Experimental evaluation demonstrates a mean tag detection accuracy of 98.2% under optimal conditions, a robust user interface (UI) latency of under 500 ms, and an average central processing unit (CPU) utilization of 28%, proving system efficiency. Comparative analysis confirms that SELLA’s integration of on-trolley automated payment and detailed performance metrics represents a significant advancement over existing prototypes. The system provides a validated, high-performance solution for next-generation smart retail environments.
Volume: 24
Issue: 1
Page: 184-195
Publish at: 2026-02-01

Technology levels in artificial intelligence robotics and industrial automation: impacts and implications

10.12928/telkomnika.v24i1.27253
Ratna; Universitas Esa Unggul Yulika Go , Agnes; National Research and Innovation Agency (BRIN) Sondita Payani , Siti; Universitas Hasanuddin Rabiatul Adawiyah , Ogi; National Research and Innovation Agency (BRIN) Gumelar
Robotics technology has progressed rapidly since its debut in 1922, evolving from simple programmable automation to highly sophisticated systems. This study employs a hybrid methodology, combining qualitative analysis of key robotic components manipulators, controllers, end effectors, and geometric configurations with quantitative comparison of performance metrics to classify robots according to their technological level (low-tech versus high tech). The findings show clear distinctions across these levels. Low-tech robots typically achieve positioning accuracy of about 0.025 mm and rely mainly on single electric motor actuation, making them suitable for simple, repetitive tasks. In contrast, high-tech robots can perform complex operations with positioning accuracy of up to 3 mm, integrating multiple actuation systems such as electric, pneumatic, and hydraulic mechanisms for enhanced flexibility and control. Moreover, high-tech robots exhibit greater manipulative capabilities and advanced control systems that enable multi axis and adaptive operations not feasible for low-tech counterparts. These results demonstrate how the technological level directly shapes a robot’s precision, actuation complexity, and functional range, providing a clear framework for selecting appropriate robotic solutions in both industrial and research settings.
Volume: 24
Issue: 1
Page: 175-183
Publish at: 2026-02-01

Implementation of markerless augmented reality and cyber physical-social systems for smart tourism application

10.12928/telkomnika.v24i1.27414
Ilham; Institut Teknologi Sumatera Firman Ashari , Fanesa; Institut Teknologi Sumatera Hadi Permana , Muhammad; Universitas Muhammadiyah Malang Zainal Arifin , Purwono; Institut Teknologi Sumatera Prasetyawan
Lampung province holds substantial tourism potential that remains underutilized due to fragmented information and limited promotional strategies. This study introduces a smart tourism application integrating markerless augmented reality (AR) with cyber-physical-social systems (CPSS), representing the first implementation of its kind for location-based tourism in the region. The novelty lies in the hierarchical coordinate transformation architecture (HCTA), a multi-layer computational framework employing the Haversine formula to achieve high-precision mapping of geographic coordinates into AR-optimized perceptual views. The system was evaluated for geolocation accuracy, resource utilization, backend scalability, AR rendering robustness, and user experience. Results show strong performance: geolocation tests across seven destinations yielded a mean error rate of 1.5%; AR operations remained efficient with 8–10% central processing unit (CPU) and 140–160 MB random access memory (RAM) usage; and rendering was stable across 360° device orientation. Backend tests confirmed scalability, sustaining 56 requests per second with zero failures under 100 concurrent users. A user study with 20 participants using the user experience questionnaire-short (UEQ-S) revealed highly positive outcomes, with overall scores 2.275, all within the Excellent benchmark. These findings confirm that the application is not only technically robust and efficient but also engaging and enjoyable, offering a scalable framework for immersive smart tourism ecosystems.
Volume: 24
Issue: 1
Page: 71-94
Publish at: 2026-02-01

Optimized IMC with GWO algorithm and variable switching function for voltage regulation of SEPIC converter

10.12928/telkomnika.v24i1.27330
Reza; Shahrood University of Technology Fazeli , Mohammad; Shahrood University of Technology Haddad Zarif , Mahmoud; Islamic Azad University Zadehbagheri , Tole; Universitas Ahmad Dahlan Embedded System and Power Electronics Research Group Sutikno
With the growing application of single-ended primary-inductor converter (SEPIC) converters in power electronic systems, precise output voltage regulation under uncertainties and nonlinear conditions remains a significant challenge. Although internal model control (IMC) effectively addresses issues arising from unstable zeros and fixed time delays in non-minimum phase systems, its performance can degrade under large transient errors or sudden disturbances, leading to control signal saturation and instability. In this study, a modified IMC scheme is proposed, which integrates a variable switching function into the control structure. This addition enhances the robustness of the system by dynamically adapting the control effort to mitigate abrupt changes in the control signal and stabilize the output voltage. Furthermore, it prevents controller saturation during large-signal deviations, thereby improving transient response and maintaining system stability. The design parameters of the controller are optimized using the gray wolf algorithm to achieve an optimal balance between voltage overshoot, settling time, and closed-loop stability. Simulation results under various operating conditions confirm the superior performance of the proposed control method compared to conventional IMC.
Volume: 24
Issue: 1
Page: 258-270
Publish at: 2026-02-01

A practical approach to Candi Siwa 3D reconstruction with COLMAP and Nerfstudio

10.12928/telkomnika.v24i1.27212
Helena; Prasetiya Mulya University Widiarti , Rokhmat; Prasetiya Mulya University Febrianto , Agung; Prasetiya Mulya University Alfiansyah
We demonstrate a practical approach for large-scale object three-dimensional (3D) reconstruction with freely available frameworks, COLMAP and Nerfstudio. We performed the reconstruction of a temple named Candi Siwa, located at Prambanan Site, which is situated between Central Java and Yogyakarta Province, Indonesia. We utilized COLMAP and Nerfstudio as platforms for 3D reconstruction from images captured by an everyday smartphone. In the 3D model construction process, COLMAP generates a dense point cloud, whereas Nerfstudio generates a scene from source images. We selected 96 images of Candi Siwa to perform reconstruction using COLMAP. As a result, a 3D model for the temple with a clear structure and color was observed. A scene rendered in MP4 format was also generated using Nerfstudio. Additionally, we performed the 3D reconstruction from 150 images taken by the public and found them insufficient for constructing the object. This occurred despite the number of images being larger than those used in the previous reconstruction. The results indicate that the success of a crowdsourcing project for reconstructing a large-scale object should consider not only the number of images but also the variation in point of view and the completeness of the whole structure.
Volume: 24
Issue: 1
Page: 249-257
Publish at: 2026-02-01

Enhancing reflective elements of intelligent reflective surfaces in 6G communications using artificial intelligence

10.12928/telkomnika.v24i1.27307
Jehan Kadhim Shareef; University of Thi-Qar Al-Safi , Abbas Thajeel Rhaif; University of Thi-Qar Alsahlanee
The dynamic landscape of 6G communication networks necessitates innovative strategies to address energy inefficiency and signal degradation in densely populated regions with limited line-of-sight (LOS) coverage. A novel technology known as an intelligent reflecting surface (IRS) has emerged; it can dynamically modify the characteristics of electromagnetic waves to enhance signal propagation. Unfortunately, current IRS models frequently neglect the balance between energy efficiency (EE) and the quantity of reflective elements (N) in Rayleigh fading scenarios. This study introduces an algorithm called dynamic-static particle swarm optimization (DS-PSO) aimed at improving EE and decreasing the quantity of reflective components in the performance optimization of IRS. The research assesses the proposed model in comparison to single-input single-output (SISO) systems, conventional IRS models, and IRS models from prior studies within a realistic urban framework. The optimized IRS, which only uses seven reflective elements, has a peak EE of 366 Mbit/Joule. This is a big improvement over IRS models from earlier research, as shown by the numbers. The findings indicate that artificial intelligence (AI)-driven optimization can enhance IRS technology for sustainable and efficient 6G networks.
Volume: 24
Issue: 1
Page: 22-33
Publish at: 2026-02-01

Bridging resilience and mathematics success: the mediating role of teacher emotional support

10.11591/ijere.v15i1.35455
Irene O. Mamites , Jhamm M. Olila , Wendy Q. Aliviano , Gley S. Arañas , Quenie R. Abesia , Emerson D. Peteros
This study investigated the mediating role of teacher emotional support (TES) in the relationship between academic resilience (AR) and mathematics performance (MP) among 563 randomly selected Grade 7 students from public secondary schools in Mandaue City, Cebu, Philippines. Employing a descriptive correlational design, data were collected through an adopted questionnaire—academic resilience scale (ARS-30), emotional support scale, and the students’ first quarter mathematics grade. The data collected were analyzed using frequency, percentage, weighted mean (WM), standard deviation (SD), Pearson r, and multiple regression analysis. Findings indicated high AR, very high TES, and satisfactory MP. Mediation analysis revealed that TES partially mediates the positive association between AR and MP. This analysis offers valuable guidance for educators, researchers, and policymakers in creating supportive learning environments that build AR and enhance TES, leading to better MP.
Volume: 15
Issue: 1
Page: 89-101
Publish at: 2026-02-01

Phygital in games: a systematic review of trends, characteristics, the user experience, technologies, and tools

10.11591/ijere.v15i1.35062
Nurasilah Osman , Nadia Akma Ahmad Zaki , Tengku Siti Meriam Tengku Wook , Maizatul Hayati Mohamad Yatim , Nor Masharah Husain , Norly Jamil
In the 21st century, the evolution of phygital technology has transformed various sectors, including retail, marketing, heritage, education, edutainment, and gaming. However, phygital interfaces are dynamic, continuously evolving alongside technological advancements and user expectations. This study aims to identify trends, characteristics, user experiences, and the tools or technologies used in phygital gaming. A systematic literature review (SLR) was conducted using the preferred reporting items for systematic reviews and meta-analysis (PRISMA) framework, analyzing 26 publications from Web of Science (WoS), Scopus, and IEEE Xplore. The findings revealed seven key characteristics of phygital interfaces and six positive impacts on user experience. Additionally, various phygital technologies and tools were identified as essential in the education, edutainment, and entertainment contexts of gaming. These technologies enhance engagement, interactivity, and immersion by seamlessly integrating physical and digital elements. Therefore, this study contributes to improving user experiences and expanding knowledge in the context of phygital interfaces. Future research should explore potential challenges in adopting phygital technologies, particularly from educators’ perspectives, to uncover new insights into their implementation and effectiveness.
Volume: 15
Issue: 1
Page: 1-15
Publish at: 2026-02-01

A decoupling-based multivariable H∞ controller for PMSM speed and current regulation

10.12928/telkomnika.v24i1.27515
Farid; Higher School of Applied Sciences of Tlemcen Oudjama , Mohammed; University of Tlemcen Messirdi , Mokhtar; University Centre of Maghnia Bourdim , Abelmadjid; University of Tlemcen Boumédiène
High precision speed regulation of the permanent magnet synchronous motor (PMSM) is a critical challenge in modern industrial applications, including electric vehicles and traction systems. This task is significantly affected by external disturbances, such as variable load torque, as well as physical phenomena often neglected in analytical models, such as magnetic circuit saturation or thermal variations in electrical parameters. In this context, conventional control methods often fail to ensure both dynamic performance and robustness. This paper proposes a multivariable H∞ control strategy based on field-oriented control (FOC) and d/q decoupling to design a robust and high-performance controller. The diagonal multiple-input multiple-output (MIMO) model, linking the direct-axis voltage𝑣𝑑to the current 𝑖𝑑and the quadrature-axis voltage 𝑣𝑞to the rotational speed 𝜔𝑟, is derived directly from the decoupling principles of FOC, without relying on linearization around an operating point or modeling of parametric uncertainties. The H∞ controller is synthesized using the standard configuration, with carefully selected weighting functions to ensure dynamic performance, closed-loop stability, and effective disturbance rejection. Numerical simulations demonstrate that the proposed controller achieves accurate speed reference tracking, fine current regulation, and fast load disturbance rejection, confirming its effectiveness and robustness. This approach provides an advanced alternative to conventional control methods by fully exploiting the multivariable structure of the system.
Volume: 24
Issue: 1
Page: 293-301
Publish at: 2026-02-01

Advanced microwave imaging and artificial neural networks for early detection and localization of breast tumors

10.12928/telkomnika.v24i1.27126
Abdelfettah; University of Mustapha Stambouli Miraoui , Lotfi; School of Applied Sciences Tlemcen Merad , Djalal; LARATIC Laboratory at National Institute of Telecommunications and Information Technology and Communication (ENSTTIC) Ziani-Kerarti
This study investigates the detection and localization of breast tumors based on dielectric property differences between cancerous and normal tissues. A microwave imaging technique integrated with artificial neural networks (ANNs) is proposed as a noninvasive alternative to conventional screening methods such as mammography and magnetic resonance imaging (MRI). A breast model with a 2.5 mm spherical tumor was designed using CST Microwave Studio. Simulation results show that the ANN achieves a detection rate close to 100%, providing negative outputs for tumor-free cases and positive outputs for cases with tumors. Additionally, ANN outputs strongly correlate with the actual tumor positions in the simulated environment. These findings suggest that microwave imaging combined with ANNs offers a cost effective, radiation-free, and patient-friendly solution for the early detection and localization of breast cancer, with promising potential for clinical translation.
Volume: 24
Issue: 1
Page: 240-248
Publish at: 2026-02-01

Internet of things heatstroke detection device

10.11591/ijece.v16i1.pp535-544
Swati Patil , Rugved Ravindra Kulkarni , Karishma Prashant Salunkhe , Vidit Pravin Agrawal
The increasing frequency and intensity of heat waves due to climate change underscore the critical need for proactive measures to prevent heat stroke, a life-threatening condition affecting individuals of all demographics, with vulnerability among the elderly and outdoor workers. In response to this pressing public health challenge, we present the internet of things (IoT) based heat stroke prevention device, a comprehensive solution leveraging a suite of sensors including temperature, atmospheric, pulse rate, blood pressure, and gyroscope sensors, seamlessly integrated with an ESP32 microcontroller and Firebase's real-time database. Central to the device's functionality is a random forest classifier machine learning model, trained on historical data and user-specific parameters, to accurately predict the likelihood of heat stroke onset in real-time. Rigorous testing and validation procedures demonstrate the device's high accuracy and reliability in sensor measurements, data transmission, and model performance. The accompanying web-based dashboard provides users with intuitive access to their current health metrics, including temperature, humidity, blood pressure, pulse rate, and personalized predictions for heat stroke risk. This innovative device serves as a versatile tool for public health agencies, occupational safety programs, and individuals seeking to safeguard their well-being in the face of escalating temperatures and climate uncertainties.
Volume: 16
Issue: 1
Page: 535-544
Publish at: 2026-02-01

Cumulative aging effects of five-year intermittent exposure on flexible amorphous solar cells

10.11591/ijece.v16i1.pp65-75
Djerroud Salima , Boudghene Stambouli Amine , Benabadji Noureddine , Lakhdari Abdelghani
Amorphous silicon (a-Si) is rarely used for large scale photovoltaic energy production, it remains relevant in flexible electronic applications, where mechanical flexibility and lightweight design are prioritized, where exposure to sunlight is typically limited or irregular. This study conducts an experimental analysis of the long-term aging effects on the proprieties of an amorphous solar cells, under five years of intermittent outdoor climate conditions. Unlike conventional aging studies that focus on degradation over time, this research highlights the cumulative effects of environmental exposure, considering the discontinuous nature of exposure cycles and the non-linearity of degradation phenomena because of the abrupt transitions between outdoor exposure phases and indoor laboratory rest periods. The results show that nearly 50% of the panel’s performances is reduced, with the losses observed as follows: a substantial decline in the fill factor from 55.3% to 30%, a decrease in energy conversion efficiency from 11.36% to 5.5%. This accelerated deterioration mainly attributed to harsh environmental transitions caused by intermittent exposure, which amplify aging mechanism compared to continuous exposure. Beyond the experimental findings, the approach presented here, constitutes a meaningful scientific contribution. By introducing a realistic and underexplored aging scenario, it lays the groundwork for a new line of research.
Volume: 16
Issue: 1
Page: 65-75
Publish at: 2026-02-01

A comparative MRI-based study of ResNet-152 and novel deep learning approaches for early Alzheimer’s disease classification

10.12928/telkomnika.v24i2.27576
Kelvin Leonardi; STMIK TIME Kohsasih , Octara; STMIK TIME Pribadi , Andy; STMIK TIME Andy , Daniel; STMIK TIME Smith Sunario
Alzheimer’s disease (AD) is the leading cause of dementia, making early-stage detection essential for timely intervention. Most prior studies have focused on binary AD classification, which limits sensitivity to disease progression. This study addressed this gap by evaluating whether tailored convolutional neural network (CNN) architectures could improve stage-aware classification using a publicly available magnetic resonance imaging (MRI) dataset containing 35,984 images across four diagnostic categories. The dataset underwent grayscale conversion, resizing, contrast enhancement, normalization, and class balancing prior to model development. Four models were trained and compared: ResNet-152, a custom multiclass CNN, a one-vs-one (OvO) model, and a one-vs-rest (OvR) model. Performance was measured using accuracy, precision, recall, F1 score, and confusion-matrix–based metrics. The custom multiclass CNN achieved the strongest performance, yielding the highest accuracy and balanced results across all evaluation metrics. These findings demonstrate the value of systematically comparing decomposition strategies for multi-stage Alzheimer’s detection and highlight the potential of the proposed approach to enhance early diagnostic support. Future work may incorporate multimodal inputs or hybrid architectures to improve sensitivity to subtle structural changes and further strengthen clinical applicability.
Volume: 24
Issue: 2
Page: 536-548
Publish at: 2026-01-30

Low-cost ESP32-based sound data acquisition system with MATLAB integration for real-time noise monitoring

10.12928/telkomnika.v24i2.27557
Reymark-John; University of Science and Technology of Southern Philippines Villanueva Campus Macapanas , Adrian P.; Mindanao State University Iligan Institute of Technology (MSU-IIT) Galido , Apple Rose B.; Mindanao State University Iligan Institute of Technology (MSU-IIT) Alce
This study presents the design and implementation of a low-cost ESP32-based sound data acquisition system (SDAS) for real-time noise monitoring. The system integrates a micro-electro-mechanical systems (MEMS) microphone for accurate acoustic data capture, an ESP-WROOM-32 microcontroller for signal processing and wireless data transmission, and MATLAB for real-time visualization and analysis. Designed and simulated in KiCAD 8.0, the SDAS includes a microSD module for local data backup and offline analysis. The system was tested in four indoor locations within Mindanao State University – Iligan Institute of Technology, recording mean noise levels ranging from 14.2 dB in laboratory environments to 32.1 dB in classrooms, with corresponding standard deviations of 1.2–7.0 dB. Expert evaluation from eight assessors confirmed the system’s usability, data reliability, and robustness. The system demonstrates effective monitoring for both quiet and dynamic settings. Limitations include single-node configuration, indoor-only testing, and MATLAB-based USB data transfer. Despite these, the proposed SDAS provides a scalable and reproducible model for smart campus and urban environmental monitoring, supporting sustainable development goals (SDG) 3, 9, and 11.
Volume: 24
Issue: 2
Page: 599-607
Publish at: 2026-01-01

Dynamic behavior of induction machines in ATP-EMTP with space harmonics

10.11591/ijeecs.v41.i1.pp3-17
Jose Manuel Aller , Ruben Nicolas Guevara , Bryam Steven Pulla
This work develops a space-vector model of a squirrel-cage induction machine that incorporates the effects of spatial harmonics arising from the winding distribution. The modeling approach includes the first, fifth, and seventh spatial harmonics, which are the components with the greatest influence on the machine’s magnetic field. Simulation results highlight the impact of these harmonics on the stator and rotor currents, the electromagnetic torque, and the machine’s speed. To build the model, the voltage behind reactances (VBR) technique is employed, enabling a hybrid strategy that combines circuit-based modeling tools—such as ATP-EMTP—with computational programming in models to complement the solution of the differential equations governing the behavior of the electromechanical system. This methodology effectively transforms the induction machine into a dynamic Thevenin-equivalent circuit for each phase of the converter. ` This study provides a useful framework for evaluating how space harmonics affect the performance and operating characteristics of induction machines. The models were implemented using the ATP-EMTP software and its graphical interface, ATPDraw.
Volume: 41
Issue: 1
Page: 3-17
Publish at: 2026-01-01
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