scholarly journals Traffic sensor health monitoring using spatiotemporal graphical modeling

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Linjiang Wu ◽  
Chao Liu ◽  
Tingting Huang ◽  
Anuj Sharma ◽  
Soumik Sarkar
Keyword(s):  
Health Status ◽  
Real Time ◽  
Sensor Network ◽  
Health Monitoring ◽  
Series Data ◽  
Spatiotemporal Pattern ◽  
Graphical Modeling ◽  
Traffic Sensors ◽  
Wide Range ◽  
Sensor Health

Accurate traffic sensor data is essential for traffic operation management systems and acquisition of real-time traffic surveillance data depends heavily on the reliability of the traffic sensors (e.g., wide range detector, automatic traffic recorder). Therefore, detecting the health status of the sensors in a traffic sensor network is critical for the departments of transportation as well as other public and private entities, especially in the circumstances where real-time decision is required. With the purpose of efficiently determining the sensor health status and identifying the failed sensor(s) in a timely manner, this paper proposes a graphical modeling approach called spatiotemporal pattern network (STPN). Traffic speed and volume measurement sensors are used in this paper to formulate and analyze the proposed sensor health monitoring system and historical time-series data from a network of traffic sensors on the Interstate 35 (I-35) within the state of Iowa is used for validation. Based on the validation results, we demonstrate that the proposed approach can: (i) extract spatiotemporal dependencies among the different sensors which leads to an efficient graphical representation of the sensor network in the information space, and (ii) distinguish and quantify a sensor issue by leveraging the extracted spatiotemporal relationship of the candidate sensor(s) to the other sensors in the network.

Dual-mode wireless sensor network for real-time contactless in-door health monitoring

2015 ◽  
Author(s):  
Marco Mercuri ◽  
Mohammad Rajabi ◽  
Peter Karsmakers ◽  
Ping Jack Soh ◽  
Bart Vanrumste ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Health Monitoring ◽  
Wireless Sensor ◽  
Dual Mode

Planning for LOTOS: A New LOwer Troposphere Observing System

2020 ◽  
Author(s):  
Terry Hock ◽  
Tammy Weckwerth ◽  
Steve Oncley ◽  
William Brown ◽  
Vanda Grubišić ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Real Time ◽  
Sensor Network ◽  
Regional Scale ◽  
Lower Troposphere ◽  
Integrated System ◽  
Lower Atmosphere ◽  
Time Data ◽  
Wide Range ◽  
Real Time Data

<p>The National Center for Atmospheric Research Earth Observing Laboratory (EOL) proposes to develop the LOwer Troposphere Observing System (LOTOS), a new integrated sensor network that offers the potential for transformative understanding of the lower atmosphere and its coupling to the Earth's surface. </p><p> </p><p>The LOTOS sensor network is designed to allow simultaneous and coordinated sampling both vertically, through the atmospheric planetary boundary layer, and horizontally, across the surrounding landscape, focusing on the land-atmosphere interface and its coupling with the overlying free troposphere. The core of LOTOS will be a portable integrated network of up to five nodes, each consisting of a profiling suite of instruments surrounded by up to fifteen flux measuring towers. LOTOS will provide an integrated set of measurements needed to address outstanding scientific challenges related to processes within the atmospheric surface layer, boundary layer, and lower troposphere. LOTOS will also enable novel quantification of exchanges of biogeochemical and climate-relevant gases from microscale up to regional scale. </p><p> </p><p>LOTOS’ uniqueness lies in its ability to simultaneously sample both horizontally and vertically as an integrated system, but also in its flexibility to be easily relocated as a portable field-deployable system suitable for addressing a wide range of research needs. LOTOS will provide real-time data quality control, combine measurements from a variety of sensors into integrated data products, and provide real-time data displays. It is envisioned that LOTOS will become part of the deployable NSF Lower Atmosphere Observing Facilities (LAOF) and thus be available to a broad base of NSF users from both observational and modeling communities. LOTOS offers the potential for transformative understanding of the Earth and its atmosphere as a coupled system. This presentation will describe the background, motivation, plan, and timeline for the LOTOS’ proposed development.</p>

scholarly journals A Multiprotocol Wireless Sensor Network for High Performance Sport Applications

2018 ◽  
Vol 1 (4) ◽  
pp. 52 ◽  
Author(s):  
Vincenzo Bonaiuto ◽  
Paolo Boatto ◽  
Nunzio Lanotte ◽  
Cristian Romagnoli ◽  
Giuseppe Annino
Keyword(s):  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
High Performance ◽  
Wearable Sensors ◽  
Real Life ◽  
Wireless Sensor ◽  
Sport Equipment ◽  
Wide Range ◽  
Physiological Sensors

The use of a network of wearable sensors placed on the athlete or installed into sport equipment is able to offer, in a real sport environment rather than in the unspecific spaces of a laboratory, a valuable real-time feedback to the coach during practice. This is made possible today by the coordinate use of a wide range of kinematic, dynamic, and physiological sensors. Using sensors makes training more effective, improves performance assessment, and can help in preventing injuries. In this paper, a new wireless sensor network (WSN) system for elite sport applications is presented. The network is made up of a master node and up to eight peripheral nodes (slave nodes), each one containing one or more sensors. The number of nodes can be increased with second level slave nodes; the nature of sensors varies depending on the application. Communication between nodes is made via a high performance 2.4 GHz transceiver; the network has a real-life range in excess of 100 m. The system can therefore be used in applications where the distance between nodes is long, for instance, in such sports as kayaking, sailing, and rowing. Communication with user and data download are made via a Wi-Fi link. The user communication interface is a webpage and is therefore completely platform (computer, tablet, smartphone) and operating system (Windows, iOS, Android, etc.) independent. A subset of acquired data can be visualized in real time on multiple terminals, for instance, by athlete and coach. Data from kayaking, karting, and swimming applications are presented.

scholarly journals Evolution of Wearable Devices with Real-Time Disease Monitoring for Personalized Healthcare

Nanomaterials ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 813 ◽  
Author(s):  
Kyeonghye Guk ◽  
Gaon Han ◽  
Jaewoo Lim ◽  
Keunwon Jeong ◽  
Taejoon Kang ◽  
...  
Keyword(s):  
Real Time ◽  
Health Monitoring ◽  
Point Of Care ◽  
Monitoring And Evaluation ◽  
The Elderly ◽  
Wearable Devices ◽  
Medical Diagnostics ◽  
Biomedical Monitoring ◽  
Wide Range ◽  
Barriers And Challenges

Wearable devices are becoming widespread in a wide range of applications, from healthcare to biomedical monitoring systems, which enable continuous measurement of critical biomarkers for medical diagnostics, physiological health monitoring and evaluation. Especially as the elderly population grows globally, various chronic and acute diseases become increasingly important, and the medical industry is changing dramatically due to the need for point-of-care (POC) diagnosis and real-time monitoring of long-term health conditions. Wearable devices have evolved gradually in the form of accessories, integrated clothing, body attachments and body inserts. Over the past few decades, the tremendous development of electronics, biocompatible materials and nanomaterials has resulted in the development of implantable devices that enable the diagnosis and prognosis through small sensors and biomedical devices, and greatly improve the quality and efficacy of medical services. This article summarizes the wearable devices that have been developed to date, and provides a review of their clinical applications. We will also discuss the technical barriers and challenges in the development of wearable devices, and discuss future prospects on wearable biosensors for prevention, personalized medicine and real-time health monitoring.

scholarly journals Development of a Cloud-Based Real-Time Building Health Monitoring and Prediction System Using AI and IoT Sensors

2021 ◽  
Vol 21 (6) ◽  
pp. 31-39
Author(s):  
Chang-Wan Ha ◽  
Byungtae Ahn ◽  
Young-Sik Shin ◽  
Jinseong Park ◽  
Jai-Kyung Lee ◽  
...  
Keyword(s):  
Real Time ◽  
Health Monitoring ◽  
Prediction Models ◽  
Time Series Data ◽  
Dimensional Structure ◽  
Series Data ◽  
Prediction System ◽  
Real Earthquake ◽  
Building Condition ◽  
Building Health Monitoring

In this study, a cloud-based real-time building health monitoring and prediction system using AI and IoT sensors was developed. To predict the building condition, which constitutes time-series data, statistical-based ARIMA and AI-based LSTM prediction models were designed, and the effectiveness of the proposed prediction models was experimentally verified using a 1/8-scaled miniaturized structure. The prediction accuracy in terms of MAPE (less than 1%) was experimentally confirmed to be satisfactory. Moreover, a method for analyzing dimensional structure deformation was developed by combining multiple sensor measurements, and its effectiveness was verified through the case study of a real earthquake-damaged building.

scholarly journals Blockchain and IPFS Integrated Framework in Bilevel Fog-Cloud Network for Security and Privacy of IoMT Devices

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Abolfazl Mehbodniya ◽  
Rahul Neware ◽  
Sonali Vyas ◽  
M. Ranjith Kumar ◽  
Peter Ngulube ◽  
...  
Keyword(s):  
Real Time ◽  
Health Monitoring ◽  
Data Security ◽  
Patient Data ◽  
Biological Data ◽  
Security And Privacy ◽  
Complex Data ◽  
Number Of Patients ◽  
Wide Range ◽  
Smart Health

Internet of Medical Things (IoMT) has emerged as an integral part of the smart health monitoring system in the present world. The smart health monitoring deals with not only for emergency and hospital services but also for maintaining a healthy lifestyle. The industry 5.0 and 5/6G has allowed the development of cost-efficient sensors and devices which can collect a wide range of human biological data and transfer it through wireless network communication in real time. This led to real-time monitoring of patient data through multiple IoMT devices from remote locations. The IoMT network registers a large number of patients and devices every day, along with the generation of huge amount of big data or health data. This patient data should retain data privacy and data security on the IoMT network to avoid any misuse. To attain such data security and privacy of the patient and IoMT devices, a three-level/tier network integrated with blockchain and interplanetary file system (IPFS) has been proposed. The proposed network is making the best use of IPFS and blockchain technology for security and data exchange in a three-level healthcare network. The present framework has been evaluated for various network activities for validating the scalability of the network. The network was found to be efficient in handling complex data with the capability of scalability.

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