Safety Monitoring Information Research Articles

A Dam Safety State Prediction and Analysis Method Based on EMD-SSA-LSTM

The safety monitoring information of the dam is an indicator reflecting the operational status of the dam. It is a crucial source for analyzing and assessing the safety state of reservoir dams, possessing strong real-time capabilities to detect anomalies in the dam at the earliest possible time. When using neural networks for predicting and warning dam safety monitoring data, there are issues such as redundant model parameters, difficulty in tuning, and long computation times. This study addresses real-time dam safety warning issues by first employing the Empirical Mode Decomposition (EMD) method to decompose the effective time-dependent factors and construct a dam in a service state analysis model; it also establishes a multi-dimensional time series analysis equation for dam seepage monitoring. Simultaneously, by combining the Sparrow Optimization Algorithm to optimize the LSTM neural network computation process, it reduces the complexity of model parameter selection. The method is compared to other approaches such as RNN, GRU, BP neural networks, and multivariate linear regression, demonstrating high practicality. It can serve as a valuable reference for reservoir dam state prediction and engineering operation management.

BIM and ontology-based knowledge management for dam safety monitoring

Dam Safety Monitoring Systems (DSMSs) are crucial in evaluating the operational state of dams. However, heterogeneous monitoring data distributed from multiple sources during the dam operation lacks a unified data integration method and prohibits knowledge extraction and intelligent analysis, which currently poses a labor-intensive task. To address this issue, a solution relying on Building Information Modeling (BIM) and domain ontologies is proposed. Specifically, a DSMS domain ontology (OntoDSMS) is developed by comprehensively collecting domain knowledge and extracting context information from the dam information model. Furthermore, a rule-based reasoner and SPARQL queries are implemented. The proposed approach facilitates the effective integration of dam safety monitoring information while reducing retrieval time effectively compared with traditional databases. A case is illustrated to demonstrate the feasibility and practicality of the proposed approach.

Visual analysis method of foundation pit monitoring information based on BIM platform

In order to visually express the safety monitoring information of foundation pits and underground engineering, realize the efficient management of massive dynamic safety monitoring information during the construction of foundation pits and underground engineering, as well as assist safety analysis, a building information model (BIM)-based Foundation pit and underground engineering dynamic safety monitoring information integration and network visualization method is proposed in the article. Firstly, the research builds a three-dimensional BIM model of foundation pit engineering based on the analysis of the element composition of the three-dimensional virtual scene of the foundation pit and underground engineering. Then, apply the method of key field mapping to establish the dynamic coupling between the BIM model and the safety monitoring information. Finally, the research realizes the virtual display of the construction process based on the three-dimensional visualization function of BIM technology. Furthermore, combined with the actual situation, the corresponding system is developed and applied in a certain project, which realized the visual integration of dynamic information of engineering safety monitoring and BIM under the network environment, and provided a support platform for the safety analysis of foundation pits and underground engineering.

Tourism safety monitoring information service system based on internet of things and block-chain

Tourism safety is the lifeblood of national tourism development, and tourism safety information monitoring is an important foundation for tourism safety management. The maturity of Internet information technology has led to the rapid rise of blockchain and the Internet of Things. In essence, the blockchain is a shared database. The Internet of Things can access all kinds of necessary information through various networks, such as heat, electricity, dynamics, chemistry, biology, realize the ubiquitous connection between things and people, and realize the recognition and intelligent perception of objects. This article aims to study a tourism safety monitoring information service system based on the Internet of Things and blockchain. This paper uses the principle of sensor ranging and electromagnetic induction, acoustic calculation, sensor calculation, and RFID tag distance to measure the real-time position of the person’s RFID tag information and continuous monitoring information of infrasound intensity to monitor and pre-warn natural disasters in the scenic area. Research results, it shows that this system can monitor disaster information in time and can effectively reduce the risk of injury by 10% –20% of tourists.

Three-dimensional Visualization of Expansive Soil Channel Slope Monitoring in the Middle Route of South-to-North Water Diversion Project

The deformation of expansive soil canal slope in the middle route of South-to-North Water Transfer Project is obvious under the action of dry-wet cycles such as atmospheric rainfall and evaporation. By means of three-dimensional visualization, the deformation trend and characteristics of canal slope in three-dimensional on-line can provide more intuitive and clear basis for the stability evaluation and rapid disposal of canal slope. Based on the self-developed three-dimensional geographic information platform -3D GIS-Ark, this paper studies the three-dimensional visualization expression method of channel and safety monitoring information in the middle route of South-to-North Water Transfer Project, and realizes the three-dimensional model of Nanyang Expansive Soil Canal section, the visualization expression and early warning of monitoring equipment management and section monitoring information. The three-dimensional visualization results studied in this paper can provide visual decision support for engineering safety analysis, intelligent evaluation and early warning, and have significant application value in the field of engineering safety monitoring.

Research on Intelligent Supervision Technology of Power Operation Security Risk Based on Internet of Things

According to the situation of power production safety and existing problems, this paper proposed a security intelligent monitoring solution for power grid based on Internet of things. The solution integrates the perception, communication and analysis technologies with the characteristics of the Internet of things. In the field, intelligent mobile terminals, intelligent security tools and other multi-source sensing equipment are used for on-site safety monitoring information collection, and data communication is realized by integrated application of 4G and narrowband Internet of things (NB-IoT). On this basis, cloud computing and edge computing are used to jointly analyse and evaluate security risk big data.

The Development and application of 3-D visual display platform for safety monitoring information of hydropower project

In the long-term project operation and safety management, the safety monitoring is used to monitor the project safety change and to identify and avoid project risk. As the eyes, ears and technical means of administration department, it can ensure the safety and can improve the efficiency of the project. How to display the monitoring information and results intuitively has been a constant pursuit of monitoring technicians. This paper introduces a kind of the monitoring data display platform based on the virtual reality technology and the interactive simulation technology. The platform will have a unified expression of the hydropower project applying the TST-VR virtual reality tools and 3-D modelling technology. It will set up the integrated visible virtual environment and realize the 3-D scene roaming, monitoring information query and other interactive control. The platform integrates the existing data resources of information system and displays all the information in an intuitive way, which is convenient for managers to query and manage, and can also meet the macro-control of superior management departments.

An Efficient Network Coding-Based Fault-Tolerant Mechanism in WBAN for Smart Healthcare Monitoring Systems

As a key technology in smart healthcare monitoring systems, wireless body area networks (WBANs) can pre-embed sensors and sinks on body surface or inside bodies for collecting different vital signs parameters, such as human Electrocardiograph (ECG), Electroencephalograph (EEG), Electromyogram (EMG), body temperature, blood pressure, blood sugar, blood oxygen, etc. Using real-time online healthcare, patients can be tracked and monitored in normal or emergency conditions at their homes, hospital rooms, and in Intensive Care Units (ICUs). In particular, the reliability and effectiveness of the packets transmission will be directly related to the timely rescue of critically ill patients with life-threatening injuries. However, traditional fault-tolerant schemes either have the deficiency of underutilised resources or react too slowly to failures. In future healthcare systems, the medical Internet of Things (IoT) for real-time monitoring can integrate sensor networks, cloud computing, and big data techniques to address these problems. It can collect and send patient’s vital parameter signal and safety monitoring information to intelligent terminals and enhance transmission reliability and efficiency. Therefore, this paper presents a design in healthcare monitoring systems for a proactive reliable data transmission mechanism with resilience requirements in a many-to-one stream model. This Network Coding-based Fault-tolerant Mechanism (NCFM) first proposes a greedy grouping algorithm to divide the topology into small logical units; it then constructs a spanning tree based on random linear network coding to generate linearly independent coding combinations. Numerical results indicate that this transmission scheme works better than traditional methods in reducing the probability of packet loss, the resource redundant rate, and average delay, and can increase the effective throughput rate.

Specialist Cohort Event Monitoring studies: a new study method for risk management in pharmacovigilance.

The evolving regulatory landscape has heightened the need for innovative, proactive, efficient and more meaningful solutions for ‘real-world’ post-authorization safety studies (PASS) that not only align with risk management objectives to gather additional safety monitoring information or assess a pattern of drug utilization, but also satisfy key regulatory requirements for marketing authorization holder risk management planning and execution needs. There is a need for data capture across the primary care and secondary care interface, or for exploring use of new medicines in secondary care to support conducting PASS. To fulfil this need, event monitoring has evolved. The Specialist Cohort Event Monitoring (SCEM) study is a new application that enables a cohort of patients prescribed a medicine in the hospital and secondary care settings to be monitored. The method also permits the inclusion of a comparator cohort of patients receiving standard care, or another counterfactual comparator group, to be monitored concurrently, depending on the study question. The approach has been developed in parallel with the new legislative requirement for pharmaceutical companies to undertake a risk management plan as part of post-authorization safety monitoring. SCEM studies recognize that the study population comprises those patients who may have treatment initiated under the care of specialist health care professionals and who are more complex in terms of underlying disease, co-morbidities and concomitant medications than the general disease population treated in primary care. The aims of this paper are to discuss the SCEM new-user study design, rationale and features that aim to address possible bias (such as selection bias) and current applications.

5T Information Fusion System Based on Train Technology Scheme Design

On the train parts of 5T system at present all kinds of fault real-time monitoring the relevance of the weak, poor information sharing, centralized monitoring problem not in time, the system can achieve 5T effective integration of information system, information real-time delivery, 5T information fusion and 5T information fusion integrated query and statistical analysis and other functions through the acquisition of 5T system data, to train vehicle as the object of management, in order to train car number as the only connection identifier, fusion 5T information resources, to establish a global view of train vehicle safety monitoring information model. To improve the level of security early warning and fault analysis ability is of great significance.

Improving bridge collapse detection and on-site emergency alarms: A case study in Taiwan

During the past decades in Taiwan, numerous scour problems have led to the collapse of bridges. Such accidents have caused severe economic losses and killed many people. Although Taiwanese government agencies have mitigated this relationship between natural hazards and bridge collapse, two problems still exist at bridge sites: the lack of convenient mechanisms for bridge collapse detection and the lack of active mechanisms for on-site emergency alarms. Therefore, based on an approach consisting of mixed collapse detectors (i.e., bi-axial tilt sensors, electronic circuits) and compounded wireless networks (i.e., low-rate wireless personal area network, wireless local area network, worldwide interoperability for microwave access), this study proposes a bridge safety monitoring information system. While the mixed collapse detectors identify the status of various bridge elements, the compounded wireless networks streamline the information transmission between on-site bridges and off-site headquarters. This research is composed of two-year tests on six bridges. After 382 earthquakes and 13 typhoons, this study confirmed that the stability of the bridge safety monitoring information system achieved the anticipated results. Thus, this study provides a sound reference for similar applications in bridge and disaster management.

Enhancing Collapse Detection and Alarms in Bridge Management

Taiwan has more than 28,000 bridges. In the past decades, because of scour problems, some bridges collapsed. Such accidents have caused severe economic losses and killed many people. Although Taiwanese government agencies have mitigated the relationship between natural hazards and bridge collapse, the lack of mechanisms for bridge collapse detection and on-site emergency alarms still exists at bridge sites. Therefore, this study proposes a bridge safety monitoring information system. With mixed collapse detectors, this information system could identify the status of various bridge elements in real time. After two-year tests at six bridge sites, this study confirmed that the performance of the bridge safety monitoring information system. Overall, this study helps for similar applications in bridge and disaster management.

Application of Fault Detection based on Hybrid Intelligent Methods

How to collect information optimally by scheduling a limited number of sensors is one of the key technologies of safety monitoring for large mechanical equipment systems. In this paper, an improved model of Pulse Coupled Neural Network is used for the discretization algorithm of continuous features. And based on classificatory error parameter and approximate dependence degree in Variable Precision Rough Sets theory, a VPRS data model is created by utilizing the measured signals from the multi-sensor Bridge Erecting Machine Safety Monitoring System. Then the corresponding relations between time-frequency characteristics and operating condition classifications are analyzed. Finally, while the determinability of decision making analysis is enhanced, the validity order of safety monitoring information of the multi-sensor sampling points is gained, which can direct optimal scheduling of position of sensors in large-scale mechanical equipment systems. DOI: http://dx.doi.org/10.11591/telkomnika.v10i8.1634 Full Text: PDF

Patient safety monitoring indicators based on medical complaints

Objective To build the indicators system to collect patient safety monitoring information, focusing on medical complaints. Methods With such methods as literature review and expert advice, building the system for medical complaints collection and monitoring. Such indicators are modified and improved in pilot operations. Results The framework of the medical complaint monitoring indicators system is built in five dimensions, comprising 8 grade-1 indicators including patient complaint causes and hospital cause analysis, and 20 grade-2 indicators. Conclusion These indicators are scientific and operable to detect adverse patient safety events. Key words: Patient safety; Medical complaints; Monitoring indicators; System building