scholarly journals Integrated Visualization Approach for Real-Time and Dynamic Assessment of Storm Surge Disasters for China’s Seas

2020 ◽  
Vol 9 (1) ◽  
pp. 51 ◽  
Author(s):  
Lin Zhou ◽  
Wei Hu ◽  
Zhen Jia ◽  
Xinfang Li ◽  
Yaru Li ◽  
...  
Keyword(s):  
Real Time ◽  
Storm Surge ◽  
Spatial Information ◽  
3D Visualization ◽  
Dynamic Assessment ◽  
Indicator System ◽  
Time Data ◽  
Term Operation ◽  
Visualization Technology ◽  
Assessment Results

For improved prevention and reduction of marine disasters, China’s marine authorities and emergency response agencies require a solution that provides risk assessment, early warning, and decision-making support. This paper proposes a comprehensive approach to disaster assessment that involves automated long-term operation, a spatial information visualization method and systematic integration. The proposed approach provides functions for numerical ocean models with forecast results, automated processing of massive data, multiple disaster/element coupled assessment, and multidimensional display and expression. With regard to storm surge disasters, the approach proposed in this paper adopts a four-tier structure and the functions of each tier are described separately. The original data are comprised of a combination of statistical analysis data and real-time data obtained from the unstructured grid Finite Volume Community Ocean Model. Automated data processing methods and assessment theories incorporating an indicator system and weighted parameters are used for the assessment. By applying 2D/3D visualization technology, assessment results are displayed via several modes for ease of operation and comprehension. The validity of the approach was verified by applying it to Typhoon Hato (No. 1713). Compared with the results of the post-disaster investigation, the assessment results of the proposed approach proved the reliability of the system.

The Application of Real-Time Monitor System Based on 3D Visualization Technology

2013 ◽  
Vol 373-375 ◽  
pp. 888-891
Author(s):  
Fang Liu ◽  
Wei Tong ◽  
Zhi Jun Qian ◽  
Yu Hong Dong
Keyword(s):  
Real Time ◽  
Virtual Environment ◽  
3D Visualization ◽  
Laboratory Model ◽  
Monitor System ◽  
Time Data ◽  
Virtual Scene ◽  
The Real ◽  
Real Time Data ◽  
Visualization Technology

This paper introduced the laboratory model of Real-time monitor system based on the 3D Visualization for calefaction furnace, depicted the process of the model.In this paper we created a virtual environment and transport the real-time data which we collected from the locale to the virtual scene,to realize the real time monitor on the real environment.Through simulating in the lab,the effect of this system was realistic at the same time it arrived at the goal of better monitoring with better real-time.

scholarly journals Tracking and Visualizing Signs of Degradation for Early Failure Prediction of Rolling Bearings

2021 ◽  
Vol 33 (3) ◽  
pp. 629-642
Author(s):  
Sana Talmoudi ◽  
Tetsuya Kanada ◽  
Yasuhisa Hirata ◽  
◽  
Keyword(s):  
Real Time ◽  
Training Data ◽  
High Dimensional ◽  
Time Data ◽  
Early Failure ◽  
Rolling Bearings ◽  
Full Spectrum ◽  
Time Frequency ◽  
Vibration Data ◽  
Visualization Technology

Predictive maintenance, which means detection of failure ahead of time, is one of the pillars of Industry 4.0. An effective method for this technique is to track early signs of degradation before failure occurs. This paper presents an innovative failure predictive scheme for machines. The proposed scheme combines the use of the full spectrum of vibration data from the machines and a data visualization technology. This scheme requires no training data and can be started quickly after installation. First, we proposed to use the full spectrum (as high-dimensional data vectors) with no cropping and no complex feature extraction and to visualize the data behavior by mapping the high-dimensional vectors into a two-dimensional (2D) map. This ensures simplicity of the process and less possibility of overlooking important information as well as provide a human-friendly and human-understandable output. Second, we developed a real-time data tracker that can predict failure at an appropriate time with sufficient allowance for maintenance by plotting real-time frequency spectrum data of the target machine on a 2D map created from normal data. Finally, we verified our proposal using vibration data of bearings from real-world test-to-failure measurements obtained from the IMS dataset.

Quality Based on a Spatial SERVQUAL Model in Healthcare

2012 ◽  
pp. 209-219
Author(s):  
Stelios Zimeras
Keyword(s):  
Performance Management ◽  
Real Time ◽  
Spatial Information ◽  
Spatial Interaction ◽  
Health Sector ◽  
Geographical Location ◽  
Quality Of Healthcare ◽  
Local Health ◽  
Time Data ◽  
Health Trends

The main purpose of this work is to represent an alternative effective model for measuring the quality of healthcare (SERVQUAL) considering the geographical location of the under examination healthcare sectors. Based on that consideration, a new modeling is taking place introducing a spatial interaction between neighboring regions (spatial-SERVQUAL model). New directions are analyzed implementing specific questionnaires taking advantage of the spatial information given by the evaluation of the model. Moreover the role of spatial information in the health sector in relation to, for example, local health improvement performance management, is analyzed to support needs assessment and resource targeting as one of the principal action points in healthcare policies. Finally, the benefits of the GIS systems are illustrated, combined with the spatial assumptions, introducing a real-time health and disease monitoring tool to identify significant health trends in real-time data streams and geographic information systems.

scholarly journals Still normal? Contextualizing real-time data with long-term statistics to monitor anomalies and systematic changes in storm surge activity – Introduction of a prototype web tool storm surge monitor for the German coasts

2021 ◽  
Author(s):  
Xin Liu ◽  
Insa Meinke ◽  
Ralf Weisse
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Storm Surge ◽  
Storm Surges ◽  
Added Value ◽  
Time Data ◽  
Storm Activity ◽  
The Public ◽  
Real Time Data

Abstract. Storm surges represent a major threat to many low-lying coastal areas in the world. While most places can cope with or are more or less adapted to present-day risks, future risks may increase from factors such as sea level rise, subsidence, or changes in storm activity. This may require further or alternative adaptation and strategies. For most places, both forecasts and real-time observations are available. However, analyses of long-term changes or recent severe extremes that are important for decision-making are usually only available sporadically or with substantial delay. In this paper, we propose to contextualize real-time data with long-term statistics to make such information publicly available in near real-time. We implement and demonstrate the concept of a ”storm surge monitor” for tide gauges along the German North Sea and Baltic Sea coasts. It provides automated near real-time assessments of the course and severity of the ongoing storm surge season and its single events. The assessment is provided in terms of storm surge height, frequency, duration, and intensity. It is proposed that such near real-time assessments provide added value to the public and decision-making. It is further suggested that the concept is transferable to other coastal regions threatened by storm surges.

scholarly journals DETECTING FLU OUTBREAKS BASED ON SPATIOTEMPORAL INFORMATION FROM URBAN SYSTEMS – DESIGNING A NOVEL STUDY

2018 ◽  
Vol XLII-3/W4 ◽  
pp. 231-237
Author(s):  
L. O. Grottenberg ◽  
O. Njå ◽  
E. Tøssebro ◽  
G. S. Braut ◽  
R. Tønnessen ◽  
...  
Keyword(s):  
Real Time ◽  
Spatial Information ◽  
Road Traffic ◽  
Epidemiological Data ◽  
Urban Transport ◽  
Urban Systems ◽  
Transport Systems ◽  
Time Data ◽  
Spatiotemporal Information ◽  
Seasonal Flu

<p><strong>Abstract.</strong> This paper explores the application of real-time spatial information from urban transport systems to understand the outbreak, severity and spread of seasonal flu epidemics from a spatial perspective. We believe that combining travel data with epidemiological data will be the first step to develop a tool to predict future epidemics and to better understand the effects that these outbreaks have on societal functions over time. Real-time data-streams provide a powerful, yet underutilised tool when it comes to monitoring and detecting changes to the daily behaviour of inhabitants.<br> In this paper, we describe and discuss the design of the geospatial project, in which we will draw upon data sources available from the Norwegian cities of Oslo and Bergen. Historical datasets from public transport and road traffic will serve as an initial indication of whether changes in daily transport patterns corresponds to seasonal flu data. It is expected that changes in daily transportation habits corresponds to swings in daily and weekly flu activity and that these differences can be measured through geostatistical analysis. Conceptually one could be able to monitor changes in human behaviour and activity in nearly true time by using indicators derived from outside the clinical health services. This type of more up-to-date and geographically precise information could contribute to earlier detection of flu outbreaks and serve as background for implementing tailor-made emergency response measures over the course of the outbreaks.</p>

A Wireless Sensors Network System for Local Multipoint Storm Surge Measurements

2018 ◽  
Vol 52 (4) ◽  
pp. 32-41 ◽  
Author(s):  
Sunil Chintalapati ◽  
Chelakara S. Subramanian
Keyword(s):  
Real Time ◽  
Storm Surge ◽  
Wireless Sensors ◽  
Prediction Models ◽  
Water Levels ◽  
Time Data ◽  
Network Systems ◽  
Efficient System ◽  
Real Time Data ◽  
Wireless Sensors Network

AbstractReal-time data of storm surge are much needed for developing effective prediction models and nowcasting of impending hazard potential. The crucial aspect of monitoring and transmitting information for extreme weather conditions in near real time is vitally important and would benefit from accurate, robust, and relatively inexpensive wireless sensing network systems. This article presents a detailed overview of the design, operation modes, system performance, and field testing of a prototype wireless sensors network (WSN) system for local multipoint storm surge measurements. Key differentiators for the prototype WSN system when compared to the existing infrastructure for monitoring water levels used by National Oceanic and Atmospheric Administration are (1) real-time data transmission, (2) ultra low cost, and (3) power-efficient system. The WSN system offers reliable field measurement employing single or multiple sensors and with features to upload data to either a local laptop or to the cloud for easy concurrent access to data for users located in any part of the world.

scholarly journals IoT Open-Source Architecture for the Maintenance of Building Facilities

2021 ◽  
Vol 11 (12) ◽  
pp. 5374
Author(s):  
Valentina Villa ◽  
Berardo Naticchia ◽  
Giulia Bruno ◽  
Khurshid Aliev ◽  
Paolo Piantanida ◽  
...  
Keyword(s):  
Open Source ◽  
Real Time ◽  
Preventive Maintenance ◽  
3D Visualization ◽  
Predictive Maintenance ◽  
Information Modeling ◽  
Automated System ◽  
Building Structures ◽  
Time Data ◽  
Time Operation

The introduction of the Internet of Things (IoT) in the construction industry is evolving facility maintenance (FM) towards predictive maintenance development. Predictive maintenance of building facilities requires continuously updated data on construction components to be acquired through integrated sensors. The main challenges in developing predictive maintenance tools for building facilities is IoT integration, IoT data visualization on the building 3D model and implementation of maintenance management system on the IoT and building information modeling (BIM). The current 3D building models do not fully interact with IoT building facilities data. Data integration in BIM is challenging. The research aims to integrate IoT alert systems with BIM models to monitor building facilities during the operational phase and to visualize building facilities’ conditions virtually. To provide efficient maintenance services for building facilities this research proposes an integration of a digital framework based on IoT and BIM platforms. Sensors applied in the building systems and IoT technology on a cloud platform with opensource tools and standards enable monitoring of real-time operation and detecting of different kinds of faults in case of malfunction or failure, therefore sending alerts to facility managers and operators. Proposed preventive maintenance methodology applied on a proof-of-concept heating, ventilation and air conditioning (HVAC) plant adopts open source IoT sensor networks. The results show that the integrated IoT and BIM dashboard framework and implemented building structures preventive maintenance methodology are applicable and promising. The automated system architecture of building facilities is intended to provide a reliable and practical tool for real-time data acquisition. Analysis and 3D visualization to support intelligent monitoring of the indoor condition in buildings will enable the facility managers to make faster and better decisions and to improve building facilities’ real time monitoring with fallouts on the maintenance timeliness.

scholarly journals Real-Time Data Visualisation in Collaborative Virtual Environment for Emergency Management

2013 ◽  
Vol 5 (4) ◽  
pp. 13-44 ◽  
Author(s):  
Pan Wang ◽  
Ian Bishop
Keyword(s):  
Emergency Management ◽  
Real Time ◽  
Virtual Environment ◽  
Spatial Information ◽  
System Development ◽  
Research Approach ◽  
Prototype System ◽  
Time Data ◽  
Collaborative Virtual Environment ◽  
Real Time Data

A collaborative virtual environment (CVE) is a shared virtual environment used for collaboration of many participants that may be spread over large distances. CVEs have been widely used in emergency management, especially for education, training and assessment. This paper describes the design and implementation of a prototype system that facilitates emergency management via a CVE using real-time spatial information. In particular, a method for automatic integration, modeling and visual simulation using real-time data from multiple online sources is proposed. Moreover, strategies are presented for using CVE-based scenarios for carrying out training, and testing preparedness measures. A novel technique has also been developed for real-time situation monitoring. Based on a system development (SD) research approach, the performance and functionality of the system was tested and evaluated. The use of real-time data acquisition and simulation was deemed to improve the processes of emergency management by increasing engagement, enhancing training and supporting decision-making of first responders and emergency managers.

Maximizing Net Pay in Penta-Lateral Well With Advanced Proactive Geosteering and 2D Structural Analysis Using Azimuthal Resistivity Measurements

2021 ◽  
Vol 62 (3) ◽  
pp. 311-330
Author(s):  
Yuriy Antonov ◽  
◽  
Dmitry Kushnir ◽  
Sergey Martakov ◽  
Jhonatan Pazos ◽  
...  
Keyword(s):  
Uncertainty Analysis ◽  
Real Time ◽  
3D Visualization ◽  
Service Level ◽  
Appropriate Technology ◽  
Time Data ◽  
Unique Challenge ◽  
Geological Interpretation ◽  
Resistivity Measurements ◽  
Azimuthal Resistivity

A unique challenge for ongoing Schrader Bluff development is to increase field production with the drilling of a high-angle, multilateral producer. To address the challenge, a project was initiated with the primary goal to safely drill five laterals with a key emphasis on maximizing net sand exposure while balancing the short- and long-term value associated with selecting the appropriate technology. This paper focuses on the technical aspects of the proactive geosteering with azimuthal resistivity measurements and multilayered user-guided inversion used in this project. The prewell study based on multiple offset wells is discussed in detail, followed by presenting the highlights of the real-time drilling/geosteering operations, and concluded with the comprehensive post-well analysis study after all five laterals were drilled. The key effort before the drilling was thorough simulation of various scenarios for several target formations. It allowed the selection of the proper geosteering service level (tools and data inversion methods), providing required resolution capabilities but not exceeding the project budget. Value of inversion on real-time data is demonstrated with several examples accompanied by uncertainty analysis of inversion results. Post-well processing included quantification of the main fault amplitude, in-depth uncertainty analysis, and 3D visualization, as well as geological interpretation using an advanced 3D modeling application. The final position and orientation of the major fault were supported with the results of 2D inversion performed in the vicinity of the fault. The integration between advanced geosteering tools and an active team effort helped achieve this complex penta-lateral well, drilling all legs with excellent directional control with numerous steering adjustments and a final net pay of 20,455 ft out of 28,886 ft drilled, which exceeded the operator’s expectations.

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