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Generalized domain tutoring framework for AI agents with integrated explainable AI techniques

10.11591/ijeecs.v40.i2.pp860-870
László Csépányi-Fürjes , László Kovács
This paper proposes a novel approach to integrate tutoring functionality into AI systems to counteract the potential decline of human intelligence caused by AI-driven over-automation. Existing explainable AI methods primarily emphasize transparency while lacking inherent educational functionality. Consequently, users are essentially left as passive recipients of AI-driven decisions without any structured learning mechanism in place. To address this, this paper introduces the knowledge-sharing-bridge (KSB), a component designed to transform AI into an active tutor. Unlike traditional intelligent tutoring systems (ITS), which operate separately from AI decision-making processes, the KSB is embedded within AI frameworks, ensuring continuous and context-aware learning opportunities. The proposed framework uses structured knowledge representation tools, such as category maps and word-clouds, to improve the user’s understanding of the decisions made by the AI systems. Prototype implementation demonstrates how these elements work together to provide real-time, interactive learning experiences. The results indicate that integrating KSB into AI enhances both explainability and user learning. This approach promotes a more in-depth interaction with AI insights and enables AI systems to become lifelong learning companions, closing the gap between automation and education.
Volume: 40
Issue: 2
Page: 860-870
Publish at: 2025-11-01

Design of mobile application for communication and user interface of ESP32 potentiostat system

10.11591/ijres.v14.i3.pp725-733
Retno Supriyanti , Wahyu Widanarto , Putra Dwi Susanto , Madya Ardi Wicaksono , Syafrudin Rais Akhdan , Muhammad Alqaaf
The potentiostat utilizing the ESP32 has a 12-bit analog-to-digital converter (ADC), meaning the maximum value for ADC voltage readings on the ESP32 is 4095. These ADC readings are then converted into actual voltage units, ensuring more accurate measurements on the potentiostat. To facilitate the use of the ESP32 potentiostat, a mobile application must be designed as a user interface for data communication. The application will be developed on a mobile platform using a Bluetooth low energy (BLE) communication channel for easier access. The development process will utilize visual studio code as the code editor and programming languages like Dart and Flutter. The resulting application will feature a user-friendly dashboard, display data in a cyclic voltammetry graph, and store data in comma-separated values (CSV) files or images in the phone’s memory. This stored data will simplify observing results obtained from the ESP32 potentiostat.
Volume: 14
Issue: 3
Page: 725-733
Publish at: 2025-11-01

Boosting carbon removal efficiency in wastewater treatment systems using a fuzzy model predictive control stategy

10.11591/ijeecs.v40.i2.pp629-639
Saïda Dhouibi , Raja Jarray , Soufiene Bouallègue
The efficient removal of carbon pollution has always presented a growing challenge facing wastewater treatment plants (WWTPs) operating with activated sludge process (ASP) technology. Enhancing pollution removal efficiency to meet standard wastewater quality limits remains a problematic in water pollution management. Recent progress in modeling and automatic control techniques can significantly improve the hydric pollution removal. In this paper, an effective carbon elimination strategy combining TakagiSugeno (TS) fuzzy modeling and model predictive control (MPC) is proposed to achieve high purification performance in terms of chemical oxygen demand (COD), biochemical oxygen demand (BOD5) and total suspended solids (TSS) indicators. A fuzzy TS model is established based on the concepts of quasi-linear parameter-varying (LPV) forms and convex polytopic transformations of the system nonlinearities. The concentrations of heterotrophic biomass, biodegradable substrate and dissolved oxygen as well as the effluent volume are controlled and maintained around their desired references with the aim of increasing pollution removal. Comparisons with the previously most used state-of-the-art parallel distributed compensation (PDC) are performed. High and competitive pollution removal percentages of 91% for COD and BOD5 indicators, and 92% for TSS metric, are achieved with the proposed MPC-based design, thus complying with the normative limits defined in WWTPs.
Volume: 40
Issue: 2
Page: 629-639
Publish at: 2025-11-01

Improving recommendations with implicit trust propagation from ratings and check-ins

10.11591/ijeecs.v40.i2.pp814-828
Sara Medjroud , Nassim Dennouni , Mourad Loukam
This paper investigates how the propagation of implicit trust between users affects the quality of point-of-interest (POI) recommendations in location-based social networks (LBSNs). Through the analysis of user interactions via ratings and check-ins, this work proposes a recommendation model known as propagation of rating/check-in for implicit trust (PRCT). This model relies on two primary approaches: Similarity trust rating (STR), which utilizes user ratings, and similarity trust check-in (STC), which focuses on check-ins data. Both approaches employ trust propagation to enhance their similarity matrices between users. An evaluation of the PRCT model using the Yelp dataset shows that the STR approach surpasses other variants in terms of PRECISION and RECALL, while the STC approach demonstrates superior performance in terms of RMSE. Furthermore, while trust propagation in the PRCT model increases the density of its similarity matrices, it does not consistently enhance its PRECISION parameter. Only the similarity Jaccard check-in (SJC) and similarity cosine check-in (SCC) approaches show a significant improvement of this parameter. 
Volume: 40
Issue: 2
Page: 814-828
Publish at: 2025-11-01

Room energy management utilizing internet of things technology for decreasing electricity consumption

10.11591/ijres.v14.i3.pp734-744
Winasis Winasis , Suroso Suroso , Azis Wisnu Widhi Nugraha , Priswanto Priswanto
This paper proposes a novel internet of things (IoT)-based control system for energy management to reduce electricity consumption from the two most dominant loads in buildings: air conditioners (AC) and lighting. The proposed system provides a comprehensive operational control strategy that integrates scheduling, human detection, ambient temperature, and light intensity for optimal room-level energy management employed. The proposed system employs wireless fidelity (WiFi)-enabled temperature, presence, and light sensors for comprehensive room conditions monitoring. Additionally, a WiFi-connected infrared module serves as an actuator to regulate the AC unit. Testing results demonstrate compelling energy savings, achieving up to 36% for the AC and 72% for the lighting while maintaining a comfortable indoor environment. These results were obtained from an experimental test in a private room within a residence over an 8-hour daytime period with 50% occupancy time. The proposed IoT system offers a highly effective and easily deployable solution for sustainable energy reduction in residential settings.
Volume: 14
Issue: 3
Page: 734-744
Publish at: 2025-11-01

The impacts of optical display BaF2-Ce materials on solid-state lighting

10.11591/ijres.v14.i3.pp717-724
Luu Hong Quan , Nguyen Thi Phuong Loan
Transparent ceramic doped with barium fluorid cerium (BaF2-Ce) was created via a sintering method and its brightness and scintillation characteristics were examined. The luminescence is associated with the 5d-4f transitions in the Ce3+ ion and exhibits emitting maxima at 310 and 323 nm. For Na-22 radioisotopes, photo-maximum at 511 keV and 1274 keV were achieved using translucent ceramic BaF2-Ce. The translucent ceramic BaF2-Ce has been determined to have a power resolution of 13.5% at 662 keV. A luminescent production rate was measured for the BaF2-Ce (0.2%) ceramic, which is similar to sole crystal. Calculations of the scintillation degradation period beneath 662 keV gamma stimulation reveal a quick part of 58 ns and a somewhat sluggish part of 434 ns. The more gradual part in BaF2-Ce(0.2%) ceramic is linked to the dipole-dipole power transmission from the host structure to the Ce3+ luminous core and is quicker comparing to self-trapped excitons (STE) emitting in BaF2 host. BaF2-Ce offer various qualities, including significant illumination output, rapid degradation duration, and rapid scintillating reaction, which are desirable for many global fields such as medicine, radiation detection, industrial systems and nuclear safety.
Volume: 14
Issue: 3
Page: 717-724
Publish at: 2025-11-01

Enhancing cross-cutting concerns in the internet of things with applying aspect oriented programming

10.11591/ijres.v14.i3.pp745-753
Khalifa Fatiha , Guelta Bouchiba
Aspect oriented programming (AOP) is a new programming model that provides new concepts to handle cross-cutting concerns about code. The idea of introducing AOP in the internet of things (IoT) is inherited from the complexity of sensor operations involving data acquisition, processing, and communication, the need to support multiple simultaneous services for users particularly security services such as authentication, authorization, data traceability, and transaction management, and the challenges posed by the IoT deployments, the treatment of these data volumes lead to problematic code redundancy and cross-cutting concerns that compromise system maintainability. In this context, AOP enables the separation of core functionalities, data management, and cross-cutting concerns, allowing them to be developed and reused independently within the same codebase. To address these issues, this paper proposes an AOP model for IoT systems based on the Petri net representations. The model strategically integrates the core AOP advantages of modularity, reusability, and extensibility, microservices based architectural decomposition and specialized handling of sensor-specific requirements in IoT environments.
Volume: 14
Issue: 3
Page: 745-753
Publish at: 2025-11-01

End-to-end system for translating bahasa isyarat Indonesia sign language gestures into Indonesian text

10.11591/ijeecs.v40.i2.pp719-734
Satria Putra , Erdefi Rakun
This study addresses critical challenges in developing an end-to-end bahasa isyarat Indonesia (BISINDO) SLT by integrating advanced deep learning techniques to overcome complex background interference, transitional gesture recognition, and limitations in dataset availability. While existing SLT systems struggle with isolated word recognition and manual preprocessing, our work introduces three key innovations: (1) implementation of YOLOv8 for optimized object detection, achieving 88% mAP and reducing WER to 11.40%, outperforming YOLOv5/v7 in handling complex backgrounds; (2) automated removal of transitional gestures using Threshold conditional random fields (TCRF), which attained 95.68% accuracy, significantly improving upon MobileNetV2’s performance (WER: 6.89% vs. 93.53%); and (3) end-to-end BISINDO SLT by expansion of the BISINDO dataset to 435 word labels, enabling comprehensive sentencelevel translation. Experimental results demonstrate the system’s robustness, with 8.31% of WER, 84.13% of SAcc, and 87.08% of SacreBLEU after dataset expansion and redundancy elimination through grouping methods. The proposed framework operates without manual intervention, marking a substantial advancement toward real-world applicability.
Volume: 40
Issue: 2
Page: 719-734
Publish at: 2025-11-01

SPARTAN–field programmable gate array implementation for analog waveforms generation by direct digital synthesis

10.11591/ijres.v14.i3.pp597-604
Moulai Khatir Ahmed Nassim , Ziani Zakarya
In the last thirty years, low power field programmable gate arrays (FPGAs) becoming more commonly used to implement a countless of applications in different electronics industry domains. Due to their flexible design, strong compatibility, parallel computing, and compared to the CPU architecture, FPGA accentuate computing efficiency and con sidered as one of the devices with the lowest application risk and the shortest development cycle among the variety of available programmable circuits families. This article details the design and implementation of a direct digital synthesis (DDS) signal generator using the Spartan-6 FPGA, focusing on high-quality sine wave generation. The system utilizes look-up tables (LUTs) and Block RAM (BRAM) for efficient storage and retrieval of sine wave data, while an 8-bit DAC0808 digital-to-analog converter (DAC) ensures precise waveform output. The FPGA's reconfigurable architecture allows real-time adjustments of frequency and phase, making the design suitable for various signal processing applications and modulation techniques like binary phase shift keying (BPSK).
Volume: 14
Issue: 3
Page: 597-604
Publish at: 2025-11-01

Automatic wildlife species identification on camera trap images using deep learning approaches: a systematic review

10.11591/ijeecs.v40.i2.pp968-977
Siyabonga Mamapule , Bukohwo Michael Esiefarienrhe , Ibidun Christiana Obagbuwa
The foundation of systematic research depends on precise species identification, functioning as a critical component in the processes of biological research. Wildlife biologists are prompting for more effective techniques to fulfill the expanding need for species identification. The rise in open source image data showing animal species, captured by digital cameras and other digital methods of collecting data, has been monumental. This rapid expansion of animal image data, integrated with state-of-the-art machine learning techniques such as deep learning which has shown significant capabilities for automating species identification. This paper focuses on the role of deep neural network architectures in furthering technological advancements in automating species identification in recent years. To advocate further investigation in this field, an examination of machine learning architectures for species identification was presented in this work. This examination focuses primarily on image analyses and discusses their significance in wildlife conservation. Fundamentally, the aim of this article is to offer insights into the present advancements in automating species identification and to act as a reference for scholars who are keen to integrate machine learning techniques into ecological studies. Systems designed through Artificial Intelligence are extensive in providing toolkits for systematic identification of species in the upcoming years.
Volume: 40
Issue: 2
Page: 968-977
Publish at: 2025-11-01

Hardware design for fast gate bootstrapping in fully homomorphic encryption over the Torus

10.11591/ijres.v14.i3.pp659-675
Saru Vig , Ahmad Al Badawi , Mohd Faizal Yusof
Fully homomorphic encryption (FHE) is a promising solution for privacy preserving computations, as it enables operations on encrypted data. Despite its potential, FHE is associated with high computational costs. As the theoretical foundations of FHE mature, mounting interest is focused towards hardware acceleration of established FHE schemes. In this work, we present a hardware implementation of the fast Fourier transform (FFT) tailored for polynomial multiplication and aimed at accelerating gate bootstrapping in Torus fully homomorphic encryption (TFHE) schemes. Our study includes an extensive design-space exploration at various implementation levels, leveraging parallel streaming data to reduce computational latency. We introduce a new algorithm to expedite modular polynomial multiplication using negative wrapped convolution. Our implementation, conducted on reconfigurable hardware, adheres to the default TFHE parameters with 1024-degree polynomials. The results demonstrate a significant performance enhancement, with improvements of up to 30-fold, depending on the FFT design parameters. Our work contributes to the ongoing efforts to optimize FHE, paving the way for more efficient and secure computations.
Volume: 14
Issue: 3
Page: 659-675
Publish at: 2025-11-01

Design of a real-time prayer clock using geographic coordinates

10.11591/ijres.v14.i3.pp834-842
Massoum Noreddine‬‏ , Moulai Khatir Ahmed Nassim
Prayer times and calendar clock are a valuable system that relies on programs that we developed in Mikroc that allow to mathematically calculate these prayer times, which differ from one place (city) to another and from one day to another using geographical coordinates. The more precise these coordinates (latitude and longitude), the more precise the prayer times are. The research that we conducted was carried out using a 16F876A microcontroller that uses the 74HC595 circuit, an 8-bit serial input and parallel output shift register for storage. Outputs can be added to the microcontroller thanks to this. It is possible to manage this integrated circuit from three pins of our microcontroller.
Volume: 14
Issue: 3
Page: 834-842
Publish at: 2025-11-01

The novel single-module communication subsystem architecture for industrial digital inkjet

10.11591/ijres.v14.i3.pp696-704
Maksim Popov , Aleksandr Romanov
The typical challenge in embedded hardware development is the data transfer subsystem. As long as the required speeds are low and high latency is acceptable, there is quite a simple solution with serial bus like controller area network (CAN). In case of high speed (hundreds of megabits per second) with the high temporal determinism, the solution becomes significantly more complicated, requiring expensive components and growing complexity of the embedded software/firmware. We consider industrial inkjet as an example. The device typically includes moving carriage (with printheads) to jet along the media. Existing solutions use optical fiber cable or shielded twisted pair (STP) cable to connect modules. So, additional physical and logical devices are required (for example, for buffering or serial-to-parallel data conversion). For a long time, this approach has no valuable alternative. The novel single-module solution involves abandoning the intermediate high-speed channel. Instead of multiple modules and high-speed communication links between them, the single module is installed near the data destination and connected to the master PC via Ethernet. The functionality of high-speed data transfer subsystem is delegated to the shared dynamic random-access memory (DRAM) and controller, implemented with field-programmable gate array (FPGA) resources. So, the connection cable is not needed anymore and the transfer speed is virtually limited only by DRAM performance.
Volume: 14
Issue: 3
Page: 696-704
Publish at: 2025-11-01

Reconfigurable embedded systems for remote health monitoring: a comprehensive review

10.11591/ijres.v14.i3.pp855-876
Tole Sutikno , Aiman Zakwan Jidin , Lina Handayani
The rapid expansion of telemedicine and wearable health devices has intensified the demand for energy-efficient and adaptable embedded systems capable of supporting real-time, reliable remote health monitoring. This review provides a comprehensive survey of reconfigurable embedded platforms—focusing on field-programmable gate arrays (FPGAs), coarse-grained reconfigurable arrays (CGRAs), and heterogeneous system-on-chips (SoCs)—deployed for monitoring critical physiological parameters such as electrocardiogram (ECG), oxygen saturation (SpO₂), and body temperature. We analyze co-design methodologies that integrate artificial intelligence (AI-driven) neural accelerators, quantization strategies, and runtime adaptability to address the competing requirements of low power consumption, data integrity, and latency minimization in diverse telemedicine contexts. The paper highlights the strengths and limitations of conventional versus reconfigurable approaches, reviews case studies in wearable and implantable health devices, and underscores key design trade-offs in performance, scalability, and security. By systematically mapping current innovations and identifying unresolved challenges—including standardization, clinical validation, and secure edge integration—this review positions reconfigurable architectures as a cornerstone for next-generation, patient-centric remote health monitoring. Future directions emphasize AI-enabled adaptability, sustainable and carbon-aware device design, and personalized healthcare through adaptive embedded systems, charting a pathway toward scalable and resilient telemedicine ecosystems.
Volume: 14
Issue: 3
Page: 855-876
Publish at: 2025-11-01

A k-nearest neighbors algorithm for enhanced clustering in wireless sensor network protocols

10.11591/ijres.v14.i3.pp605-613
Adil Hilmani , Yassine Sabri , Abderrahim Maizate , Siham Aouad , Fouad Ayoub
Wireless sensor networks (WSNs) are small, autonomous, battery-powered nodes capable of sensing, storing, and processing data, while communicating wirelessly with a central base station (BS). Optimizing energy consumption is a major challenge to extend the lifetime of these networks. In this study, we propose an innovative approach combining the k-nearest neighbors (KNN) algorithm with hierarchical and flat routing protocols to improve node selection and clustering in three key protocols: low-energy adaptive clustering hierarchy (LEACH), threshold-sensitive energy efficient sensor network protocol (TEEN), and hybrid energy-efficient distributed clustering (HEED). Concretely, KNN is used to rank nodes based on their spatial and energy proximity, thus optimizing the choice of cluster heads (CHs) and reducing long and costly connections. Simulations show a reduction in the inter-CH distance, a decrease in overall energy consumption, and an extension of the network lifetime compared to conventional versions of the protocols. These improvements not only help increase operational efficiency, but also enhance communications stability and security, providing a robust and sustainable solution for critical WSN applications.
Volume: 14
Issue: 3
Page: 605-613
Publish at: 2025-11-01
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