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International Journal of Reconfigurable and Embedded Systems (IJRES)
Published by Institute of Advanced Engineering and Science
ISSN : 20894864     EISSN : 27222608     DOI : -
Core Subject : Economy,
Economics, Econometrics & Finance
The centre of gravity of the computer industry is now moving from personal computing into embedded computing with the advent of VLSI system level integration and reconfigurable core in system-on-chip (SoC). Reconfigurable and Embedded systems are increasingly becoming a key technological component of all kinds of complex technical systems, ranging from audio-video-equipment, telephones, vehicles, toys, aircraft, medical diagnostics, pacemakers, climate control systems, manufacturing systems, intelligent power systems, security systems, to weapons etc. The aim of IJRES is to provide a vehicle for academics, industrial professionals, educators and policy makers working in the field to contribute and disseminate innovative and important new work on reconfigurable and embedded systems. The scope of the IJRES addresses the state of the art of all aspects of reconfigurable and embedded computing systems with emphasis on algorithms, circuits, systems, models, compilers, architectures, tools, design methodologies, test and applications.
Arjuna Subject : -
Articles 456 Documents
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Systematic review of a lightweight convolutional neural network architectures on edge devices Abu Talib, Muhammad Abbas; Setumin, Samsul; Abu Bakar, Siti Juliana; Che Ani, Adi Izhar; Cahyani, Denis Eka
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 14, No 2: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v14.i2.pp339-352

Abstract

A lightweight convolutional neural network (CNN) has become one of the major studies in machine learning field to optimize its potential for employing it on the resource-constrained devices. However, a benchmark for fair comparison is still missing and thus, this paper aims to identify the recent studies regarding the lightweight CNN architectures including the types of CNN, its applications, edge devices usage, evaluation types and matrices, and performance comparison. The preferred reporting items for systematic reviews and meta-analysis (PRISMA) framework was used as the main approach to collect and interpret the literature. In the process, 37 papers were identified as meeting the criteria for lightweight CNNs aimed at image classification or regression tasks. Of these, only 20 studies explored the use of these models on edge devices. To conclude, MobileNet appeared as the most used architecture, while the types of CNN focused on image classification for the general-purpose application. Following that, the NVIDIA Jetson Nano was the most utilized edge device in recent research. Additionally, performance evaluation commonly included measures like accuracy and time, along with metrics such as recall, precision, F1-Score, and other similar indicators. Finally, the average accuracy for performance comparison can serve as threshold value for future research in this scope of study.
On time audio alert automated intelligent system for visually impaired people Pretty Diana Cyril, Cyriloose; Vethanayagam, Sumathy; Geetha, Sundararajan; Krishna, Brahmadesam Viswanathan
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 14, No 2: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v14.i2.pp428-439

Abstract

India is the home of the world’s blind population. The country has around 12 million individuals with visual impairment against a global total of 39 million according to a report published by the National Programme for Control of Blindness. Visually impaired people cannot live independently. They have to depend on others for their daily activities. The major problem occurs when blind people walk on the road, they cannot detect any obstacle which puts them at risk. sometimes it causes major injuries and accidents. With the proposed system, visually impaired people can walk on the road independently. A device with internet of things (IoT) technology where smart glass is embedded with an ultrasonic sensor, sunglasses, Raspberry Pi, voice module ISD1820, and Bluetooth. This device alerts the user with audio guidance. When people walk in front of an obstacle, the device detects the obstacle and tells the user at what distance the obstacle is there. They can walk on the road comfortably and fearlessly. It gives audio alerts about obstacles to the user. The key features are it is easy to wear, lightweight, and cost-effective. Wearing smart glasses, they can walk on the road confidently like a normal human being without any guilt.
Real-time face detection and local binary patterns histograms-based face recognition on Raspberry Pi with OpenCV Chandrasekaran, Bharanidharan; Karunkuzhali, D.; Kandasamy, V.; DIllibabu, M.; Rama Devi, K.
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 14, No 2: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v14.i2.pp527-537

Abstract

This paper presents a practical end-to-end paper demonstrating real-time face recognition using a Raspberry Pi and open source computer vision library (OpenCV) consisting of three main stages: training the recognizer, real-time recognition, and face detection and data gathering. The paper offers a comprehensive guide for enthusiasts venturing into computer vision and facial recognition. Employing the Haar Cascade classifier for accurate face detection and the local binary patterns histograms (LBPH) face recognizer for robust training and recognition, the paper ensures a thorough understanding of key concepts. The step-by-step process covers software installation, camera testing, face detection, data collection, training, and real time recognition. With a focus on the Raspberry Pi platform, this paper serves as an accessible entry point for exploring facial recognition technology. Readers will gain insights into practical implementation, making it an ideal resource for learners and hobbyists interested in delving into the exciting realm of computer vision.
A k-nearest neighbors algorithm for enhanced clustering in wireless sensor network protocols Hilmani, Adil; Sabri, Yassine; Maizate, Abderrahim; Aouad, Siham; Ayoub, Fouad
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 14, No 3: November 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v14.i3.pp605-613

Abstract

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.
Clustering with hierarchical routing (GMMCHR): a new gaussian mixture model for wireless sensor networks Sikarwar, Neetu; Tomar, Ranjeet Singh
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 14, No 3: November 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v14.i3.pp785-809

Abstract

Military surveillance, industrial applications, and real-time environmental monitoring all depend on wireless sensor networks (WSNs). However, due to insufficient power sources for sensor nodes, energy efficiency (EE) and network lifetime (NL) extension are significant challenges. To vanquish these constraints, this investigation suggests a new GMMCHR (Gaussian Mixture Model Clustering with Hierarchical Routing) protocol that combines energy-aware routing with probabilistic clustering. The approach segregates network into NC (Near Clusters) and FC (Far Clusters) based on node distance from the BS. CHs are selected using a fitness function incorporating residual energy and spatial proximity, with FCs formed via Enhanced Gaussian Mixture Models (EGMM) and routing managed through a hierarchical structure. Simulations conducted in MATLAB R2021a under two scenarios—100 nodes in a 100×100 m² region and 200 nodes in a 200×200 m² region—demonstrate significant improvements over the benchmark EEHCHR protocol. In the 100-node scenario, GMMCHR delays the FND (First Node Dead) to 66 rounds, HND (Half Node Dead) to 911 rounds, and LND (Last Node Dead) to 1601 rounds, compared to EEHCHR’s 45, 735, and 1359, respectively. In the 200-node setup, GMMCHR achieves FND at 48 rounds, HND at 904, and LND at 1231, outperforming EEHCHR’s 31, 731, and 1024 rounds. Additionally, GMMCHR maintains over 70% coverage beyond 1200 rounds in Scenario 1 and delivers over 17,000 packets to the base station, significantly higher than EEHCHR. Moreover, the combination of soft clustering in GMM with the hierarchical routing would allow dynamic flexibility, superior load balancing, and improved scalability. Overall, GMMCHR provides an effective and capable method of enhancing the lifetime of the WSN in both small-scale and large-scale systems.
Smart irrigation system with internet of things for rose cultivation in a basic greenhouse in Canchis, Cusco, 2025 Benique, Marco Antonio Roque; Teves, Luis Enrique Falcon; Ortiz, Eduar Anibal Vasquez
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 14, No 3: November 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v14.i3.pp754-765

Abstract

A large percentage of the world’s freshwater is allocated to agriculture, which presents a significant challenge for the future in light of a growing global population and climate change. In this context, it is essential to implement technologies that enable more efficient water resource management. Consequently, a smart irrigation system with internet of things (IoT) was developed for rose cultivation in a basic greenhouse located in Canchis, in the Cusco region, in 2025. This project integrated sensors for data acquisition, ESP32 modules for control, and solenoid valves as actuators. Additionally, the ThingSpeak platform was used for monitoring. The implementation of the system in the basic greenhouse demonstrated reliable communication between the different nodes and the virtual platform, as well as full automation through the solenoid valve’s response to a defined threshold. Finally, it showed an average water consumption savings per irrigation of up to 46.26% compared to the previous system.
The novel single-module communication subsystem architecture for industrial digital inkjet Popov, Maksim; Romanov, Aleksandr
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 14, No 3: November 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v14.i3.pp696-704

Abstract

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.
Hardware design for fast gate bootstrapping in fully homomorphic encryption over the Torus Vig, Saru; Al Badawi, Ahmad; Faizal Yusof, Mohd
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 14, No 3: November 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v14.i3.pp659-675

Abstract

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.
Design of a real-time prayer clock using geographic coordinates Noreddine‬‏, Massoum; Nassim, Moulai Khatir Ahmed
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 14, No 3: November 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v14.i3.pp834-842

Abstract

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.
Reconfigurable embedded systems for remote health monitoring: a comprehensive review Sutikno, Tole; Zakwan Jidin, Aiman; Handayani, Lina
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 14, No 3: November 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v14.i3.pp855-876

Abstract

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.

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