J. Sens. Actuator Networks最新文献_第9页

A Mathematical-Based Model for Estimating the Path Duration of the DSDV Routing Protocol in MANETs 基于数学模型的manet中DSDV路由协议的路径持续时间估计

J. Sens. Actuator Networks Pub Date : 2022-05-12 DOI: 10.3390/jsan11020023

Saeed Salah, R. Zaghal, Mada Abdeljawad

{"title":"A Mathematical-Based Model for Estimating the Path Duration of the DSDV Routing Protocol in MANETs","authors":"Saeed Salah, R. Zaghal, Mada Abdeljawad","doi":"10.3390/jsan11020023","DOIUrl":"https://doi.org/10.3390/jsan11020023","url":null,"abstract":"Mobile Ad Hoc Networks (MANETs) are kind of wireless networks where the nodes move in decentralized environments with a highly dynamic infrastructure. Many well-known routing protocols have been proposed, with each having its own design mechanism and its own strengths and weaknesses and most importantly, each protocol being mainly designed for specific applications and scenarios. Most of the research studies in this field used simulation testbeds to analyze routing protocols. Very few contributions suggested the use of analytical studies and mathematical approaches to model some of the existing routing protocols. In this research, we have built a comprehensive mathematical-based model to analyze the Destination-Sequenced Distance Vector protocol (DSDV), one of the main widely deployed proactive protocols and studied its performance on estimating the path duration based on the concepts of the probability density function and the expected values to find the best approximation values in real scenarios. We have tested the validity of the proposed model using simulation scenarios implemented by the Network Simulator tool (NS3). The results extracted from both the mathematical model and the simulation have shown that the path duration is inversely proportional to both the speed of the node and the hop count. Furthermore, it had shown that the path duration estimated from the DSDV protocol is less than the actual path duration, due to the implementation of the settling time concept and keeping the “periodic routes’ update” parameter at a constant level, despite the fact that the node’s speed reduces the effective path utilization.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121511031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Sensitivity of Machine Learning Approaches to Fake and Untrusted Data in Healthcare Domain 医疗保健领域机器学习方法对虚假和不可信数据的敏感性

J. Sens. Actuator Networks Pub Date : 2022-03-30 DOI: 10.3390/jsan11020021

F. Marulli, S. Marrone, Laura Verde

{"title":"Sensitivity of Machine Learning Approaches to Fake and Untrusted Data in Healthcare Domain","authors":"F. Marulli, S. Marrone, Laura Verde","doi":"10.3390/jsan11020021","DOIUrl":"https://doi.org/10.3390/jsan11020021","url":null,"abstract":"Machine Learning models are susceptible to attacks, such as noise, privacy invasion, replay, false data injection, and evasion attacks, which affect their reliability and trustworthiness. Evasion attacks, performed to probe and identify potential ML-trained models’ vulnerabilities, and poisoning attacks, performed to obtain skewed models whose behavior could be driven when specific inputs are submitted, represent a severe and open issue to face in order to assure security and reliability to critical domains and systems that rely on ML-based or other AI solutions, such as healthcare and justice, for example. In this study, we aimed to perform a comprehensive analysis of the sensitivity of Artificial Intelligence approaches to corrupted data in order to evaluate their reliability and resilience. These systems need to be able to understand what is wrong, figure out how to overcome the resulting problems, and then leverage what they have learned to overcome those challenges and improve their robustness. The main research goal pursued was the evaluation of the sensitivity and responsiveness of Artificial Intelligence algorithms to poisoned signals by comparing several models solicited with both trusted and corrupted data. A case study from the healthcare domain was provided to support the pursued analyses. The results achieved with the experimental campaign were evaluated in terms of accuracy, specificity, sensitivity, F1-score, and ROC area.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129798338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Blockchain as IoT Economy Enabler: A Review of Architectural Aspects 区块链作为物联网经济的推动者:架构方面的回顾

J. Sens. Actuator Networks Pub Date : 2022-03-29 DOI: 10.3390/jsan11020020

Diego Pennino, M. Pizzonia, A. Vitaletti, Marco Zecchini

{"title":"Blockchain as IoT Economy Enabler: A Review of Architectural Aspects","authors":"Diego Pennino, M. Pizzonia, A. Vitaletti, Marco Zecchini","doi":"10.3390/jsan11020020","DOIUrl":"https://doi.org/10.3390/jsan11020020","url":null,"abstract":"In the IoT-based economy, a large number of subjects (companies, public bodies, or private citizens) are willing to buy data or services offered by subjects that provide, operate, or host IoT devices. To support economic transactions in this setting, and to pave the way for the implementation of decentralized algorithmic governance powered by smart contracts, the adoption of the blockchain has been proposed both in scientific literature and in actual projects. The blockchain technology promises a decentralized payment system independent of (and possibly cheaper than) conventional electronic payment systems. However, there are a number of aspects that need to be considered for an effective IoT–blockchain integration. In this review paper, we start from a number of real IoT projects and applications that (may) take advantage of blockchain technology to support economic transactions. We provide a reasoned review of several architectural choices in light of typical requirements of those applications and discuss their impact on transaction throughput, latency, costs, limits on ecosystem growth, and so on. We also provide a survey of additional financial tools that a blockchain can potentially bring to an IoT ecosystem, with their architectural impact. In the end, we observe that there are very few examples of IoT projects that fully exploit the potential of the blockchain. We conclude with a discussion of open problems and future research directions to make blockchain adoption easier and more effective for supporting an IoT economy.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116145059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Wearable Sensors for Vital Signs Measurement: A Survey 用于生命体征测量的可穿戴传感器:综述

J. Sens. Actuator Networks Pub Date : 2022-03-11 DOI: 10.3390/jsan11010019

Zhihan Lv, Yuxi Li

{"title":"Wearable Sensors for Vital Signs Measurement: A Survey","authors":"Zhihan Lv, Yuxi Li","doi":"10.3390/jsan11010019","DOIUrl":"https://doi.org/10.3390/jsan11010019","url":null,"abstract":"With the outbreak of coronavirus disease-2019 (COVID-19) worldwide, developments in the medical field have aroused concerns within society. As science and technology develop, wearable medical sensors have become the main means of medical data acquisition. To analyze the intelligent development status of wearable medical sensors, the current work classifies and prospects the application status and functions of wireless communication wearable medical sensors, based on human physiological data acquisition in the medical field. By understanding its working principles, data acquisition modes and action modes, the work chiefly analyzes the application of wearable medical sensors in vascular infarction, respiratory intensity, body temperature, blood oxygen concentration, and sleep detection, and reflects the key role of wearable medical sensors in human physiological data acquisition. Further exploration and prospecting are made by investigating the improvement of information security performance of wearable medical sensors, the improvement of biological adaptability and biodegradability of new materials, and the integration of wearable medical sensors and intelligence-assisted rehabilitation. The research expects to provide a reference for the intelligent development of wearable medical sensors and real-time monitoring of human health in the follow-up medical field.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130206227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Bio-Signals in Medical Applications and Challenges Using Artificial Intelligence 生物信号在医学中的应用和人工智能的挑战

J. Sens. Actuator Networks Pub Date : 2022-02-25 DOI: 10.3390/jsan11010017

Mudrakola Swapna, Uma Maheswari Viswanadhula, Dr Rajanikanth Aluvalu, Vijayakumar Vardharajan, K. Kotecha

引用次数: 17

Combining 10 Matrix Pressure Sensor to Read Human Body's Pressure in Sleeping Position in Relation with Decubitus Patients 结合10矩阵压力传感器读取与卧位患者有关的人体压力

J. Sens. Actuator Networks Pub Date : 2022-02-25 DOI: 10.3390/jsan11010016

H. Pranjoto, Andrew Febrian Miyata, L. Agustine

{"title":"Combining 10 Matrix Pressure Sensor to Read Human Body's Pressure in Sleeping Position in Relation with Decubitus Patients","authors":"H. Pranjoto, Andrew Febrian Miyata, L. Agustine","doi":"10.3390/jsan11010016","DOIUrl":"https://doi.org/10.3390/jsan11010016","url":null,"abstract":"This work uses piezoresistive matrix pressure sensors to map the human body’s pressure profile in a sleeping position. This study aims to detect the area with the highest pressure, to visualize the pressure profile into a heatmap, and to reduce decubitus by alerting the subject to changes in position. This research combines ten matrix pressure sensors to read a larger area. This work uses a Raspberry Pi 4 Model B with 8 GB memory as the data processor, and every sensor sheet uses ATMEGA 2560 as the sensor controller for data acquisition. Sensor calibration is necessary because each output must have the same value for the same weight value; the accuracy between different sensors is around 95%. After the calibration process, the output data must be smoothed to make visual representations more distinguishable. The areas with the highest pressure are the heel, tailbone, back, and head. When the subject’s weight increases, pressure on the tailbone and back increases, but that on the heel and head does not. The results of this research can be used to monitor people’s sleeping positions so that they can reduce the risk of decubitus.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124522209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Novel Road Maintenance Prioritisation System Based on Computer Vision and Crowdsourced Reporting 基于计算机视觉和众包报告的道路养护优先排序系统

J. Sens. Actuator Networks Pub Date : 2022-02-14 DOI: 10.3390/jsan11010015

Edwin Salcedo, Mona Jaber, Jesús Requena-Carrión

{"title":"A Novel Road Maintenance Prioritisation System Based on Computer Vision and Crowdsourced Reporting","authors":"Edwin Salcedo, Mona Jaber, Jesús Requena-Carrión","doi":"10.3390/jsan11010015","DOIUrl":"https://doi.org/10.3390/jsan11010015","url":null,"abstract":"The maintenance of critical infrastructure is a costly necessity that developing countries often struggle to deliver timely repairs. The transport system acts as the arteries of any economy in development, and the formation of potholes on roads can lead to injuries and the loss of lives. Recently, several countries have enabled pothole reporting platforms for their citizens, so that repair work data can be centralised and visible for everyone. Nevertheless, many of these platforms have been interrupted because of the rapid growth of requests made by users. Not only have these platforms failed to filter duplicate or fake reports, but they have also failed to classify their severity, albeit that this information would be key in prioritising repair work and improving the safety of roads. In this work, we aimed to develop a prioritisation system that combines deep learning models and traditional computer vision techniques to automate the analysis of road irregularities reported by citizens. The system consists of three main components. First, we propose a processing pipeline that segments road sections of repair requests with a UNet-based model that integrates a pretrained Resnet34 as the encoder. Second, we assessed the performance of two object detection architectures—EfficientDet and YOLOv5—in the task of road damage localisation and classification. Two public datasets, the Indian Driving Dataset (IDD) and the Road Damage Detection Dataset (RDD2020), were preprocessed and augmented to train and evaluate our segmentation and damage detection models. Third, we applied feature extraction and feature matching to find possible duplicated reports. The combination of these three approaches allowed us to cluster reports according to their location and severity using clustering techniques. The results showed that this approach is a promising direction for authorities to leverage limited road maintenance resources in an impactful and effective way.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132395942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Discrete-Time Takagi-Sugeno Stabilization Approach Applied in Autonomous Vehicles 离散时间Takagi-Sugeno镇定方法在自动驾驶汽车中的应用

J. Sens. Actuator Networks Pub Date : 2022-02-09 DOI: 10.3390/jsan11010012

M. Jemmali, H. Mouftah

引用次数: 0

An AI-Empowered Home-Infrastructure to Minimize Medication Errors 人工智能支持的家庭基础设施可最大限度地减少用药错误

J. Sens. Actuator Networks Pub Date : 2022-02-09 DOI: 10.3390/jsan11010013

Muddasar Naeem, A. Coronato

{"title":"An AI-Empowered Home-Infrastructure to Minimize Medication Errors","authors":"Muddasar Naeem, A. Coronato","doi":"10.3390/jsan11010013","DOIUrl":"https://doi.org/10.3390/jsan11010013","url":null,"abstract":"This article presents an Artificial Intelligence (AI)-based infrastructure to reduce medication errors while following a treatment plan at home. The system, in particular, assists patients who have some cognitive disability. The AI-based system first learns the skills of a patient using the Actor–Critic method. After assessing patients’ disabilities, the system adopts an appropriate method for the monitoring process. Available methods for monitoring the medication process are a Deep Learning (DL)-based classifier, Optical Character Recognition, and the barcode technique. The DL model is a Convolutional Neural Network (CNN) classifier that is able to detect a drug even when shown in different orientations. The second technique is an OCR based on Tesseract library that reads the name of the drug from the box. The third method is a barcode based on Zbar library that identifies the drug from the barcode available on the box. The GUI demonstrates that the system can assist patients in taking the correct drug and prevent medication errors. This integration of three different tools to monitor the medication process shows advantages as it decreases the chance of medication errors and increases the chance of correct detection. This methodology is more useful when a patient has mild cognitive impairment.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123987864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Acknowledgment to Reviewers of JSAN in 2021 感谢2021年JSAN审稿人

J. Sens. Actuator Networks Pub Date : 2022-01-29 DOI: 10.3390/jsan11010011

引用次数: 0