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Mobile agents assisted data collection in wireless sensor networks utilizing ZigBee technology Hoang Thuan Tran; Cuong V. Nguyen; Nghia Trung Phung; Minh T. Nguyen
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4541

Abstract

Wireless sensor networks (WSNs) are being utilized widely in many different industries, including agriculture, medicine, and the military. They contain many distributed sensors to monitor physical or environmental factors, such as temperature, humidity, pressure, etc. and use various communication technologies, including WiFi, radio frequency (RF), Bluetooth, and ZigBee. ZigBee is always a preferred choice for applications in WSNs. ZigBee has remarkable capabilities, such as saving energy and transmitting data over long distances. ZigBee end devices, as well as a ZigBee coordinator (ZC) and a ZigBee router (ZR), are crucial components of the WSNs. This article discusses the fundamentals of the ZigBee network, one of the most popular data transmission technologies in wireless sensor networks (WSNs). Additionally, we want to discuss the ZigBee communication technologies and their applications, particularly in the networks. Different scenarios for mobile agents including their routing protocols in WSNs are considered. Simulation results of different scenarios demonstrate how easily scalability can be achieved and provide a foundation for further ZigBee application development. At last, some conclusions and ideas are presented for considerations.
Field programmable gate array based moving object tracking system for robot navigation Hoang T. Tran; Dong LT. Tran; Quang N. Pham; Thanh C. Vo; Quan NA. Nguyen; Thang K. Nguyen; Duyen M. Ha; Minh T. Nguyen
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4538

Abstract

This paper proposes a method in which an object tracking robot system is implemented on field programmable gate arrays (FPGAs). The OV7670 camera provides real-time object pictures to the system. To improve picture quality, images are put via the median filter phase. The item is distinguished from the backdrop based on color (red), after which it is subjected to a mathematical morphological approach of filtering to eliminate noise. To send the robot control signals, the object's (new) coordinates are found. In this method, the median filter, color separation, hardware IP cores, and morphological filter are all part of the embedded system on FPGA. Through the direct memory access (DMA) controller, these cores may communicate and perform high-speed pipeline computing at higher data rates. The entire system is executed in real-time on Xilinx's spartan-6 FPGA KIT. The results show practical and promise.
Visualization-based monitoring in early warning systems with wireless sensor networks Minh T. Nguyen; Cuong V. Nguyen; Huyen N. Nguyen
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp281-289

Abstract

With the impact of global climate change, natural disasters such as prolonged drought, earthquakes, and tsunamis, have constantly increased over recent decades, putting those living in these areas in great danger. A natural disaster warning system has been established as an indispensable need to minimize possible high risks that cause human casualties. Several current natural disaster warning systems focus on building wireless sensor networks for forecasting and monitoring disasters as well as natural phenomena. This paper aims to develop a comprehensive model that integrates data visualization operations to identify and simultaneously predict threat proceedings in natural disasters. This technique can handle big data based on sensing data from wireless sensor networks and shows overview graphs about disasters' variability, floods, and earthquakes, in the areas. Based on the results collected from data visualization techniques, the system can issue alerts about the interest of the region in real time. In addition, we propose some levels for the warning system in which the networks only focus on the area with essential data that must be warned. This can save energy consumption for other areas of safety. This work shows promising points of effectiveness.
Artificial intelligent based teaching and learning approaches: A comprehensive review Thuong TK. Nguyen; Minh T. Nguyen; Hoang T. Tran
International Journal of Evaluation and Research in Education (IJERE) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v12i4.26623

Abstract

The goal of this study is to investigate the potential effects that Artificial intelligence (AI) could have on education. The narrative and framework for investigating AI that emerged from the preliminary research served as the basis for the study’s emphasis, which was narrowed down to the use of AI and its effects on administration, instruction, and student learning. According to the findings, artificial intelligence has seen widespread adoption and use in education, particularly by educational institutions and in various contexts and applications. The development of AI began with computers and technologies related to computers; it then progressed to web-based and online intelligent education systems; and finally, it applied embedded computer systems in conjunction with other technologies, humanoid robots, and web-based chatbots to execute instructor tasks and functions either independently or in partnership with instructors. By utilizing these platforms, educators have been able to accomplish a variety of administrative tasks. In addition, because the systems rely on machine learning and flexibility, the curriculum and content have been modified to match the needs of students. This has led to improved learning outcomes in the form of higher uptake and retention rates.
Comprehensive Review of Security Problems in Mobile Robotic Assistant Systems: Issues, Solutions, and Challenges Long Q. Dinh; Dung T. Nguyen; Thang C. Vu; Tao V. Nguyen; Minh T. Nguyen
Journal of Computing Theories and Applications Vol. 2 No. 2 (2024): JCTA 2(2) 2024
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.11408

Abstract

Nowadays, robots in the modern world are playing an important and increasingly popular role. MRA (Mobile Robotic Assistant) is a type of mobile robot designed to support humans in many different fields, helping to improve efficiency and safety in daily activities, work, or medical treatment. The number of MRAs is increasing and diverse in function, in addition to the ability to collect and process data, MRAs also have the ability to physically interact with users. Therefore, security is one of the important issues to improve the safety and effective operation of MRA. In this paper, through a comprehensive literature review and detailed analysis of the prominent MRA security attacks in recent years (based on criteria such as: attack targets, technologies used, impact level, feasibility, and contribution to addressing overall MRA security issues), a systematic classification by MRA activity fields is conducted. Security attacks, threats, and vulnerabilities are examined from various perspectives, such as hardware attacks or network/system-level attacks, operating systems/application software. Additionally, corresponding security solutions are proposed, compared, and evaluated to enhance MRA security. The paper also addresses challenges and suggests open research directions for the future.
A Novel Clustering Solution Based on Energy Threshold for Energy Efficiency Purposes in Wireless Sensor Networks Thang C. Vu; Binh D. Do; Mui D. Nguyen; Dung T. Nguyen; Tao V. Nguyen; Long Q. Dinh; Hung T. Nguyen; Minh T. Nguyen
Journal of Computing Theories and Applications Vol. 3 No. 1 (2025): JCTA 3(1) 2025
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.13022

Abstract

In many wireless sensor network (WSN) applications, nodes are randomly deployed and self-organize into a wireless network to perform tasks. In practice, recharging the batteries of network nodes after deployment is often difficult. Network nodes often operate autonomously, so the main focus is on increasing the node lifetime. Data redundancy is another limitation that makes nodes inefficient. In most cases, densely deployed nodes in a monitoring area will have redundant data from neighboring nodes. Therefore, we propose a clustering technique to select the Cluster Head (CH) node in small-scale WSNs. Since transmission consumes more energy than data collection, this protocol enables reactive routing, where transmission occurs only when a certain threshold is reached. In addition, based on their heterogeneous energy levels, nodes can be grouped into three categories: Normal, Intermediate, and Advanced. Simulation results in MATLAB/Simulink show that, after approximately 3000 rounds, the proposed method successfully transmitted about 3.1 × 104 packets to the base station, compared to 2.3 × 104 packets for the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. In addition, the time when the last node died was approximately 3,500 rounds, whereas the LEACH protocol only maintained about 1,500 rounds. The results have shown the effectiveness of this technique in reducing the dead node rate and increasing packet transmission efficiency.
Indoor Positioning using Smartphones: An Improved Time-of-Arrival Technique Thang C. Vu; Trung H. Nguyen; Mui D. Nguyen; Dung T. Nguyen; Tao V. Nguyen; Long Q. Dinh; Minh T. Nguyen
Journal of Computing Theories and Applications Vol. 3 No. 1 (2025): JCTA 3(1) 2025
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.13305

Abstract

Indoor positioning technology based on smartphones plays an important role in the current technological development context. Especially in applications such as warehouses, supermarkets, hospitals, or buildings. While the global positioning system (GNSS) is popular and effective outdoors, it has several limitations when operating in enclosed spaces, such as indoors, due to the complexity of these environments. Smartphones have many built-in sensors (such as light sensors, sound sensors, gyroscopes, accelerometers, and magnetic sensors) and support the connection of various types of wireless communication technologies such as Wi-Fi and Bluetooth. However, such sensors were not initially developed for positioning applications. This study addresses the positioning problem using the MUSIC technique in conjunction with the Time of Arrival (ToA) method. The effectiveness of the positioning solution is evaluated through the signal-to-noise ratio (SNR) index. The absolute error and squared error indices are evaluated through the cumulative distribution function (CDF) to indicate the effectiveness of the proposed solution. Additionally, we propose a Pedestrian Dead Reckoning method to determine a person's position in indoor environments continuously. Based on the segmentation of the moving process by turns, the direction measurements in each segment are processed using a Kalman filter, which is designed to enhance the results achieved by the system. We also discuss the challenges and some future research directions in the field of smartphone-based indoor positioning.
Effectiveness and Limitations of Preprocessing Methods for Proprioceptive Sensor Noise in Quadruped Robots Mui D. Nguyen; Minh T. Nguyen; Ha T. Nguyen; Binh TT. Nguyen; Long Q. Dinh; Dung T. Nguyen; Thang C. Vu; Duc M. Ngo
Journal of Computing Theories and Applications Vol. 3 No. 4 (2026): JCTA 3(4) 2026
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.15921

Abstract

Proprioceptive sensor data, including inertial measurement units (IMU), joint encoders, and torque sensors, plays a critical role in state estimation for quadruped robots operating in dynamic and unstructured environments. However, these signals are often degraded by various sources of error, such as high-frequency noise, bias, drift, and contact-induced disturbances, which directly affect estimation accuracy and stability. This study presents a systematic analysis of sensor-specific noise characteristics and evaluates the effectiveness of preprocessing methods tailored to each sensor modality. Specifically, moving average filtering is applied to encoder signals to mitigate noise amplification during differentiation, while first-order low-pass filtering is employed for IMU and torque signals to suppress high-frequency noise. Experimental results on a publicly available quadruped dataset demonstrate that encoder velocity RMSE is reduced by 12.09%, high-frequency energy decreases by 59.63%, and signal-to-noise ratio (SNR) improves by 145.6%. However, variance reductions remain limited (3.39% for IMU and 4.05% for torque), indicating the persistence of impulsive, non-Gaussian noise caused by contact events. These findings highlight that linear preprocessing methods are effective for attenuating high-frequency noise but insufficient for handling non-Gaussian disturbances. The study provides practical insights into the effectiveness and limitations of preprocessing strategies, serving as a foundation for developing more robust signal processing and state estimation frameworks in quadruped robotics.
AN-RPL: Infrastructure-Assisted RPL Enhancement via Distributed Anchor Nodes for Mobile IoT Networks Thang C. Vu; Minh T. Nguyen; Mui D. Nguyen; Long Q. Dinh; Dung T. Nguyen; Duc M. Ngo
Journal of Computing Theories and Applications Vol. 4 No. 1 (2026): JCTA 4(1) 2026
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.16184

Abstract

The Internet of Things (IoT) has attracted significant attention from the research community due to its wide range of applications. However, the limited energy, processing capability, storage, and communication capacity of IoT devices require routing solutions that are both lightweight and efficient. To address these constraints, the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) was introduced in 2012 as a routing protocol specifically designed for resource-constrained IoT environments. Although RPL performs reliably in static deployments, its performance degrades considerably in mobile environments because of frequent topology changes, slow Trickle timer convergence, and excessive parent churn. This paper proposes Anchor-Node RPL (AN-RPL), an infrastructure-assisted enhancement of RPL that strategically deploys distributed fixed anchor nodes as stable DODAG roots while requiring only minimal firmware modification on mobile sensor nodes, namely a single anchor-flag check during parent selection. Simulation experiments conducted in Cooja using both OF0 and MRHOF objective functions across four scenarios (static, mobile with one, two, and four anchor nodes) demonstrate that AN-RPL with four anchor nodes improves the Data Delivery Ratio (DDR) by up to 30.6 percentage points, reduces the average hop count by up to 51.2%, lowers parent churn by up to 89.5%, and decreases average energy consumption by up to 14.8% compared with conventional single-root mobile RPL. These results demonstrate that infrastructure-assisted anchor deployment provides an effective and practical approach for improving routing reliability and efficiency in mobile RPL-based IoT networks.