IET Wireless Sensor Systems最新文献_第5页

Evaluation and calibration of low-cost off-the-shelf particulate matter sensors using machine learning techniques 使用机器学习技术评估和校准低成本的现成颗粒物传感器

IF 1.9

IET Wireless Sensor Systems Pub Date : 2022-11-04 DOI: 10.1049/wss2.12043

Mohammad Ghamari, Hamid Kamangir, Keyvan Arezoo, Khalil Alipour

{"title":"Evaluation and calibration of low-cost off-the-shelf particulate matter sensors using machine learning techniques","authors":"Mohammad Ghamari, Hamid Kamangir, Keyvan Arezoo, Khalil Alipour","doi":"10.1049/wss2.12043","DOIUrl":"https://doi.org/10.1049/wss2.12043","url":null,"abstract":"The use of inexpensive, lightweight, and portable particulate matter (PM) sensors is increasingly becoming popular in air quality monitoring applications. As an example, these low-cost sensors can be used in surface or underground coal mines for monitoring of inhalable dust, and monitoring of inhalable particles in real-time can be beneficial as it can possibly assist in preventing coal mine related respiratory diseases such as black lung disease. However, commercially available PM sensors are not inherently calibrated, and as a result, they have vague and unclear measurement accuracy. Therefore, they must initially be evaluated and compared with standardised instruments to be ready to be deployed in the fields. In this study, three different types of inexpensive, light-scattering-based widely available PM sensors (Shinyei PPD42NS, Sharp GP2Y1010AU0F, and Laser SEN0177) are evaluated and calibrated with reference instruments. PM sensors are compared with reference instruments in a controlled environment. The calibration is done by means of different machine learning techniques. The results demonstrate that the calibrated response obtained by fusion of sensors has a higher accuracy in comparison to the calibrated response of each individual sensor.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.12043","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91800940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Applications of wireless sensor systems to sleep stage estimation for home sleep monitoring 无线传感器系统在家庭睡眠监测中睡眠阶段估计的应用

IF 1.9

IET Wireless Sensor Systems Pub Date : 2022-10-11 DOI: 10.1049/wss2.12042

Jin-Shyan Lee, Ming-Feng Dong

{"title":"Applications of wireless sensor systems to sleep stage estimation for home sleep monitoring","authors":"Jin-Shyan Lee, Ming-Feng Dong","doi":"10.1049/wss2.12042","DOIUrl":"https://doi.org/10.1049/wss2.12042","url":null,"abstract":"In recent years, research on sleep monitoring and analysis has attracted many scholars. Among them, the polysomnography (PSG) is performed more accurately. However, PSG is not suitable to be used at home due to its complicated operation and expensive cost. On the other hand, although the Pittsburgh sleep quality index (PSQI) is a standardized form for sleep quality assessment, the subjective and backward evaluation may lead to intuitive results. Therefore, this paper is intended to develop a sleep stage estimation system for home health care services. In the proposed platform, the sleep conditions, including the heart rate (HR) and body movement, are collected by an HR monitor and a force sensor array, respectively. Also, the fuzzy inference system is applied to the sleep depth evaluation, and then, the finite state machine is utilised to estimate the sleep stage. Experimental results show that the developed platform not only reduces the burden of PSG measurements, but also provides more convincible and reasonable results, presenting as an assistive tool of the conventional PSQI tests.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2022-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.12042","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91558901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Applications of wireless sensor systems to sleep stage estimation for home sleep monitoring 无线传感器系统在家庭睡眠监测中睡眠阶段估计的应用

IF 1.9

IET Wireless Sensor Systems Pub Date : 2022-10-11 DOI: 10.1049/wss2.12042

Jin-Shyan Lee, M. Dong

引用次数: 0

LoRaWAN-implemented node localisation based on received signal strength indicator LoRaWAN基于接收信号强度指示符实现节点定位

IF 1.9

IET Wireless Sensor Systems Pub Date : 2022-09-15 DOI: 10.1049/wss2.12039

Ibrahim Aqeel, Ephraim Iorkyase, Hussein Zangoti, Christos Tachtatzis, Robert Atkinson, Ivan Andonovic

{"title":"LoRaWAN-implemented node localisation based on received signal strength indicator","authors":"Ibrahim Aqeel, Ephraim Iorkyase, Hussein Zangoti, Christos Tachtatzis, Robert Atkinson, Ivan Andonovic","doi":"10.1049/wss2.12039","DOIUrl":"https://doi.org/10.1049/wss2.12039","url":null,"abstract":"Long Range Wireless Area Network (LoRaWAN) provides desirable solutions for Internet of Things (IoT) applications that require hundreds or thousands of actively connected devices (nodes) to monitor the environment or processes. In most cases, the location information of the devices arguably plays a critical role and is desirable. In this regard, the physical characteristics of the communication channel can be leveraged to provide a feasible and affordable node localisation solution. This paper presents an evaluation of the performance of LoRaWAN Received Signal Strength Indicator (RSSI)-based node localisation in a sandstorm environment. The authors employ machine learning algorithms, Support Vector Regression and Gaussian Process Regression, which turn the high variance of RSSI due to frequency hopping feature of LoRaWAN to advantage, creating unique signatures representing different locations. In this work, the RSSI features are used as input location fingerprints into the machine learning models. The proposed method reduces node localisation complexity when compared to GPS-based approaches whilst provisioning more extensive connection paths. Furthermore, the impact of LoRa spreading factor and kernel function on the performance of the developed models have been studied. Experimental results show that the SVR-enhanced fingerprint yields the most significant improvement in node localisation performance.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.12039","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50134090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

WLS algorithm for UAV navigation in satellite-less environments 无卫星环境下无人机导航的WLS算法

IF 1.9

IET Wireless Sensor Systems Pub Date : 2022-08-04 DOI: 10.1049/wss2.12041

Ricardo Santos, J. Matos-Carvalho, Slavisa Tomic, M. Beko

引用次数: 3

Use of wireless sensor network system based on water level, rain, conductivity, oil and turbidity sensors to monitor the storm sewerage 采用基于水位、雨量、电导率、油和浊度传感器的无线传感网络系统对暴雨污水进行监测

IF 1.9

IET Wireless Sensor Systems Pub Date : 2022-07-12 DOI: 10.1049/wss2.12040

Javier Rocher, A. Rego, Jaime Lloret, Luís M. L. Oliveira

引用次数: 1

Wireless IoT universal approach based on Allan variance method for detection of artificial vibration signatures of a DC motor's shaft and reconstruction of the reference signal 基于Allan方差法的无线物联网通用方法，用于检测直流电机轴的人工振动特征并重建参考信号

IF 1.9

IET Wireless Sensor Systems Pub Date : 2022-05-04 DOI: 10.1049/wss2.12038

Mohamed Hayouni, T. Vuong, F. Choubani

引用次数: 2

IF 1.9

IET Wireless Sensor Systems Pub Date : 2022-04-14 DOI: 10.1049/wss2.12037

Ayesha Shafique, Muhammad Asad, M. Aslam, Saima Shaukat, Guo Cao

{"title":"Multi-hop similarity-based-clustering framework for IoT-Oriented Software-Defined wireless sensor networks","authors":"Ayesha Shafique, Muhammad Asad, M. Aslam, Saima Shaukat, Guo Cao","doi":"10.1049/wss2.12037","DOIUrl":"https://doi.org/10.1049/wss2.12037","url":null,"abstract":"The performance of Internet of Things (IoT) ‐ based Wireless Sensor Networks (WSNs) depends on the routing protocol and the deployment technique in modern applications. In a plethora of IoT ‐ WSNs applications, the IoT nodes are essential equipment to prolong the network lifetime with limited resources. Data similarity ‐ based clustering protocols exploit the temporal correlation among the neighbouring sensor nodes through the subset of data. In bendy supervision, IoT ‐ based Software Defined WSNs provide an optimistic resolution by allowing the control logic to be separated from the sensor nodes. The benefit of this SDN ‐ based IoT architecture, allows the unified control of the entire IoT network, making it easier to implement on ‐ demand network management protocols and applications. To this end, in this paper, we design a Multi ‐ hop Similarity ‐ based Clustering framework for IoT ‐ oriented Software ‐ Defined wireless sensor Networks (MSCSDNs). In particular, we construct data ‐ similar application ‐ aware clusters in order to minimise the communication overhead. Also, we adapt inter ‐ cluster and intra ‐ cluster multi ‐ hop communication using adaptive normalised least mean square and merged them with the proposed MSCSDN framework that helps prolong the network lifespan. The proposed framework is compared with the state ‐ of ‐ the ‐ art approaches in terms of network lifespan, stability period, instability period, report delay, report delivery, and cluster leader nodes generations. The MSCSDN achieves optimal data accuracy concerning the collected data.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81275562","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: 4

Sectored LEACH (S-LEACH): An enhanced LEACH for wireless sensor network 分段滤出(S-LEACH):无线传感器网络的增强型滤出

IF 1.9

IET Wireless Sensor Systems Pub Date : 2022-04-11 DOI: 10.1049/wss2.12036

F. A. Mohammed, N. Mekky, Hassan Hussein Suleiman, N. A. Hikal

引用次数: 4

An ensemble approach to deep-learning-based wireless indoor localization 基于深度学习的室内无线定位集成方法

IF 1.9

IET Wireless Sensor Systems Pub Date : 2022-03-01 DOI: 10.1049/wss2.12035

Juthatip Wisanmongkol, A. Taparugssanagorn, Le Chung Tran, Anh Tuyen Le, Xiaojing Huang, Christian Ritz, E. Dutkiewicz, S. L. Phung

引用次数: 3