International Journal of Reconfigurable and Embedded Systems

The fast expansion of wireless sensor network-internet of things (WSN-IoT) in recent years has led to the adoption of a vital infrastructure. Adversaries who work together to carry out privacy-related attacks and capture sensitive information from critical infrastructure for a range of personal, political, and commercial purposes, thus security and node preserving have been one of the key areas of research in WSN-IoT. Existing security and privacy research work focuses on cryptography, either which is less efficient, or it majorly focuses on securing the network, which further leads to exposing the nodes to the vulnerability in terms of privacy in the network. This research develops condition-based distributed privacy-preserving (CDPP) approach to preserve the sensor node privacy; the CDPP algorithm develops a condition based on which the nodes' vulnerable information is preserved and not accessed by the compromised nodes. CDPP architecture is evaluated considering the amount of misclassified nodes for safeguarding the node in the network. CDPP is evaluated by inducing the corrupt nodes and further comparing the model with existing low energy adaptive clustering hierarchy (LEACH) based on classification, misclassification and throughput. Furthermore, comparative analysis proves the marginal improvisation in terms of discussed parameter against existing protocol.

Bharat Kumara

S. Anantha Padmanabhan

International Journal of Reconfigurable and Embedded Systems (IJRES)

A condition-based distributed approach for secured privacy preservation of nodes in wireless sensor networks IoT

基于条件的无线传感器网络物联网节点安全隐私保护分布式方法

A technology called an alcohol detection driver system is used to stop drunk driving by identifying alcohol in a motorist's breath or blood. This technology correctly measures the amount of alcohol a driver has in their system using sensors and algorithms, and it stops the car from starting if the amount is more than the legal limit. The number of fatal accidents and traffic fatalities caused by drinking could be greatly decreased thanks to this technology. The main focus of this project is to carry out the experiment in lowering the number of alcohol-related incidents on the road. Alcohol detection devices come in a variety of forms right now, including ignition interlocks, passive alcohol sensors, and in-car breathalyzers. Although these systems have reduced the number of drunk driving accidents, there remain questions about their efficiency, dependability, and cost. According to the sensor's specs, the output voltage of the MQ-3 sensor reduces by 69% during the sensor's recovery period of 30 seconds at 69% of baseline resistance. To assess the long-term viability and efficiency of these systems in lowering alcohol-related accidents and enhancing traffic safety, more research is required.

Oluwaseyi Omotayo Alabi

Oyetunde Adeoye Adeaga

Sunday Adeola Ajagbe

Esther Oluwayemisi Adekunle

Matthew Olusegun Adigun

Design and implementation of an alcohol detection driver system

酒精检测驾驶员系统的设计与实现

The North Sumatra region is an area with the potential for earthquakes originating from volcanic and oceanic eruptions which have resulted in many fatalities. Therefore, through the application of automatic monitoring and control system technology connected to the internet of things (IoTs), it is the right solution to provide efforts to increase security for residents of the house to always be vigilant. The security enhancement method referred to in this study is a home security system protection system by anticipating earthquakes. The advantage of this tool is that it applies a notification security system method with a sensitivity sensor which is automatically sent via email and sonor buzzer which also acts as sound vibrations due to an earthquake. The test results show that when a vibration occurs, the system will send a short email message to the user's smartphone so that the user will receive an email in the form of a warning message that the state of the house has an earthquake and the light-emitting diode (LED) interrupts and the buzzer is also on so that the alarm sounds which has been integrated into IoT. Then an integrated security monitoring system using the web can be monitored in real time.

Habib Satria

Indri Dayana

Rahmad B. Y. Syah

Dian Noviandri

Muhammad Khahfi Zuhanda

Syafii Syafii

Rudi Salam

Earthquake detection in mountainous homes using the internet of things connected to photovoltaic energy supply

利用光伏能源供应的物联网在山区住宅中的地震检测

&lt;p&gt;Solar energy has the potential to meet the entire world's energy requirements. Previous study revealed that photovoltaic (PV) panel monitoring methods are far more difficult and exclusive. This study examines and proposes an automated internet of things (IoT)-based PV panel monitoring system that allows autonomous monitoring of solar panel properties such as voltage, temperature, humidity, and sun irradiation from anywhere over the internet. Excessive human demand can be reduced by collecting data from solar panels. Many data sets can be collected frequently; for example, thousands of data points can be collected each minute. Continuous monitoring is achievable by gathering real-time data. Because there is no possibility of human error, highly accurate data can be generated.&lt;/p&gt;

Arcot Ramakrishnan Kalaiarasi

Ayyadurai Chinnadurai Vasunthira Devi

Vijayan Yeshwanth

Samuthiraraj Pravinraj

Muthu Prabakaran

Internet of things based smart photovoltaic panel monitoring system

基于物联网的智能光伏板监测系统

Recent development in internet of things (IoT) has been generating huge data due to the large number of nodes deployed and utilized for different applications. In addition, these applications utilize big data and require a more efficient mechanism for data sensing and data transmission. This research work proposes dual step hybrid routing (DSHR) protocol for efficient cluster-based routing. It comprises a two-phase algorithm, which aims at finding the optimal path considering clustering. It further comprises several processes such as cluster head selection, optimal path construction, integrating of nodes to cluster head and sensing range optimization. DSHR is evaluated considering the network lifetime; thereafter model is compared with the existing low energy adaptive clustering hierarchy (LEACH) protocol to prove the efficiency.

Kalpavi C. Yankanaik

Sujatha B. Munivenkatappa

Dual step hybrid routing protocol for network lifetime enhancement in WSN-IoT environment

用于延长WSN-IoT环境中网络寿命的双步混合路由协议

&lt;p&gt;&lt;span&gt;Scene segmentation is an essential step in a wide range of video processing applications, for instance, object recognition and tracking. The Gaussian mixture model (GMM) for background subtraction (BS) has gained widespread usage in scene segmentation, despite its known computational intensity. To tackle this challenge, we propose a practical solution to accelerate processing through a parallel implementation on an embedded multicore platform. In this paper, we present an improved automated parallel implementation of the GMM algorithm using the Orphan directive provided by open multiprocessing (OpenMP). Experimental assessments conducted on the eight cores of the C6678 digital signal processor (DSP) demonstrate significant advancements in parallel efficiency, particularly when handling high-resolution frames, including high-definition (HD) and full-HD resolutions. The achieved parallel efficiency surpasses the results obtained with classical OpenMP scheduling modes, encompassing dynamic, static, and guided approaches. Specifically, the parallel efficiency reaches approximately 82% for full-HD resolution frames and, 99.3% for low-resolution frames, respectively.&lt;/span&gt;&lt;/p&gt;

Smail Bariko

Abdessamad Klilou

Abdelouahed Abounada

Assia Arsalane

International Journal of Reconfigurable and Embedded Systems/International Journal of Reconfigurable & Embedded Systems (IJRES)

Improved automated parallel implementation of GMM background subtraction on a multicore digital signal processor

多核数字信号处理器上改进的GMM背景减除自动化并行实现

&lt;span&gt;Stroke, a prevalent nerve disorder in Indonesia, necessitates post-stroke rehabilitation like physical and occupational therapy. Hand and finger muscle training, crucial for restoring movement, often involves innovative solutions like finger prosthetic robotics arms. In particular, the advancement in thumb robotics emphasizes the estimation of thumb motion, where the ensemble Kalman filter square root (EnKF-SR) and H-infinity methods are deemed dependable for both linear and nonlinear models. Simulation results, using 400 ensembles, demonstrated nearly identical accuracy between the methods, exceeding 99%, with a 6-7% increase in accuracy compared to 200 ensembles. These advancements offer promising prospects for effective post-stroke rehabilitation and improved thumb movement restoration.&lt;/span&gt;

Teguh Herlambang

Fajar Annas Susanto

Aji Akbar Firdaus

Vicky Andria Kusuma

Sena Sukmananda Suprapto

Muhaimin Muhaimin

Hamzah Arof

Optimized Kalman filtering in dynamical environments for thumb robot motion estimation

动态环境中拇指机器人运动估计的优化卡尔曼滤波

&lt;span&gt;The most important aspects of computer vision are moving object detection (MOD) and tracking. Many signal-processing applications use regional image statistics. Compute-intensive video and image processing with low latency and high throughput is done with field programmable gate array (FPGA) image processing. Local image statistics are used for edge identification and filtering. The histogram of oriented gradients (HoG) algorithm extracts local shape characteristics by equalizing histograms. The objective of the work is to design the hardware chip of the algorithm and perform the simulation in the Xilinx ISE 14.7 simulation environment. The performance of the chip is evaluated in Modelsim 10.0 simulation software to check its feasibility. The performance of the chip design is estimated on Viretx-5 FPGA and compared with the MATLAB-2020 image processing tool-based response time. This form of tracking typically deals with identifying, anchoring, and tracking images and videos. A mask made from a cut-out of the object can then determine the plane's coordinates depending on its position. This type of object tracking is frequently utilized in the field of augmented reality (AR). The algorithm is most suited for object detection using hardware controllers in haze and foggy environments.&lt;/span&gt;

Monika Sharma

Kuldeep Singh Kaswan

Dileep Kumar Yadav

Moving objects detection based on histogram of oriented gradient algorithm chip for hazy environment

基于梯度方向直方图算法的雾天运动目标检测芯片

Efficient acquisition of channel state information (CSI) is quite complicated process but immensely essential to exploit probable benefits of massive multiple input multiple output (MIMO) systems. Therefore, a deep learningbased model is utilized to estimate channel feedback in a massive MIMO system. The proposed improvised deep learning-based channel estimation (IDLCE) model enhances channel reconstruction efficiency by using multiple convolutional layers and residual blocks. The proposed IDLCE model utilizes encoder network to compress CSI matrices where decoder network is used to downlink reconstruct CSI matrices. Here, an additional quantization block is incorporated to improve feedback reconstruction accuracy by reducing channel errors. A COST 2,100 model is adopted to analyse performance efficiency for both indoor and outdoor scenarios. Further, deep learning-based model is used to train thousands of parameter and correlation coefficients much faster and to minimize computational complexity. The proposed IDLCE model evaluate performance in terms of normalized mean square error (NMSE), correlation efficiency and reconstruction accuracy and compared against varied state-of-art-channel estimation techniques. Excellent performance results are obtained with large improvement in channel reconstruction accuracy

Parinitha Jayashanka

Byrappa Nanjundaiah Shobha

Channel reconstruction through improvised deep learning architecture for high-speed networks

高速网络中通过即兴深度学习架构进行信道重构

&lt;span&gt;This study focuses on the design and development of programmable frequency generator using embedded devices that are able to produce square wave signals in the wireless power transfer (WPT) transmitter. We validate the accuracy of the output signal by measuring distance error. We validate that our system can change and sweep the frequency and produce high power by measuring the absorbed power in the load. We conduct the frequency sweep analysis to find optimal frequency and the frequency splitting phenomenon. The experiments show that the system can produce and sweep the square wave signals with less than 1% error. We also find that the frequency splitting occurred when distance among two coils in the range 0.5-6.5 cm and the splitting disappeared when the distance is above 7.5 cm. The frequency splitting shows that the measured optimum frequency differs from the calculation. The difference confirms that the programmable frequency generator is needed to adjust the frequency that can transfer maximum power to the load.&lt;/span&gt;

Sabriansyah Rizqika Akbar

Eko Setiawan

Achmad Basuki

Embedded systems as programmable square wave generator in wireless power transfer

嵌入式系统作为无线电力传输中的可编程方波发生器

出版信息	出版商: Institute of Advanced Engineering and Science (IAES)，出版周期: ，期刊类型: journal，开源期刊: 否
基本数据	创刊年份: 2019，原创研究文献占比: ，自引率:， Gold OA占比:

International Journal of Reconfigurable and Embedded Systems

期刊引文格式

有 1 位以上作者的期刊

有 2 位作者的期刊

有 3 位作者的期刊

有 5 位以上作者的期刊

书籍引用格式

学位论文引用格式

网页引用格式

专利引用格式

手工熬夜修改参考文献？研飞自动匹配期刊，一键轻松成稿，支持 Word/WPS

投稿经验分享