Search results for: multichannel monitoring systems
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11342

Search results for: multichannel monitoring systems

11192 The Diffusion of Telehealth: System-Level Conditions for Successful Adoption

Authors: Danika Tynes

Abstract:

Telehealth is a promising advancement in health care, though there are certain conditions under which telehealth has a greater chance of success. This research sought to further the understanding of what conditions compel the success of telehealth adoption at the systems level applying Diffusion of Innovations (DoI) theory (Rogers, 1962). System-level indicators were selected to represent four components of DoI theory (relative advantage, compatibility, complexity, and observability) and regressed on 5 types of telehealth (teleradiology, teledermatology, telepathology, telepsychology, and remote monitoring) using multiple logistic regression. The analyses supported relative advantage and compatibility as the strongest influencers of telehealth adoption, remote monitoring in particular. These findings help to quantitatively clarify the factors influencing the adoption of innovation and advance the ability to make recommendations on the viability of state telehealth adoption. In addition, results indicate when DoI theory is most applicable to the understanding of telehealth diffusion. Ultimately, this research may contribute to more focused allocation of scarce health care resources through consideration of existing state conditions available foster innovation.

Keywords: adoption, diffusion of innovation theory, remote monitoring, system-level indicators

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11191 Deep Learning-Based Object Detection on Low Quality Images: A Case Study of Real-Time Traffic Monitoring

Authors: Jean-Francois Rajotte, Martin Sotir, Frank Gouineau

Abstract:

The installation and management of traffic monitoring devices can be costly from both a financial and resource point of view. It is therefore important to take advantage of in-place infrastructures to extract the most information. Here we show how low-quality urban road traffic images from cameras already available in many cities (such as Montreal, Vancouver, and Toronto) can be used to estimate traffic flow. To this end, we use a pre-trained neural network, developed for object detection, to count vehicles within images. We then compare the results with human annotations gathered through crowdsourcing campaigns. We use this comparison to assess performance and calibrate the neural network annotations. As a use case, we consider six months of continuous monitoring over hundreds of cameras installed in the city of Montreal. We compare the results with city-provided manual traffic counting performed in similar conditions at the same location. The good performance of our system allows us to consider applications which can monitor the traffic conditions in near real-time, making the counting usable for traffic-related services. Furthermore, the resulting annotations pave the way for building a historical vehicle counting dataset to be used for analysing the impact of road traffic on many city-related issues, such as urban planning, security, and pollution.

Keywords: traffic monitoring, deep learning, image annotation, vehicles, roads, artificial intelligence, real-time systems

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11190 Using Multiple Strategies to Improve the Nursing Staff Edwards Lifesciences Hemodynamic Monitoring Correctness of Operation

Authors: Hsin-Yi Lo, Huang-Ju Jiun, Yu-Chiao Chu

Abstract:

Hemodynamic monitoring is an important in the intensive care unit. Advances in medical technology in recent years, more diversification of intensive care equipment, there are many kinds of instruments available for monitoring of hemodynamics, Edwards Lifesciences Hemodynamic Monitoring (FloTrac) is one of them. The recent medical safety incidents in parameters were changed, nurses have not to notify doctor in time, therefore, it is hoped to analyze the current problems and find effective improvement strategies. In August 2021, the survey found that only 74.0% of FloTrac correctness of operation, reasons include lack of education, the operation manual is difficulty read, lack of audit mechanism, nurse doesn't know those numerical changes need to notify doctor, work busy omission, unfamiliar with operation and have many nursing records then omissions. Improvement methods include planning professional nurse education, formulate the secret arts of FloTrac, enacting an audit mechanism, establish FloTrac action learning, make「follow the sun」care map, hold simulated training and establish monitoring data automatically upload nursing records. After improvement, FloTrac correctness of operation increased to 98.8%. The results are good, implement to the ICU of the hospital.

Keywords: hemodynamic monitoring, edwards lifesciences hemodynamic monitoring, multiple strategies, intensive care

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11189 A Car Parking Monitoring System Using a Line-Topology Wireless Sensor Network

Authors: Dae Il Kim, Jungho Moon, Tae Yun Chung

Abstract:

This paper presents a car parking monitoring system using a wireless sensor network. The presented sensor network has a line-shaped topology and adopts a TDMA-based protocol for allowing multi-hop communications. Sensor nodes are deployed in the ground of an outdoor parking lot in such a way that a sensor node monitors a parking space. Each sensor node detects the availability of the associated parking space and transmits the detection result to a sink node via intermediate sensor nodes existing between the source sensor node and the sink node. We evaluate the feasibility of the presented sensor network and the TDMA-based communication protocol through experiments using 11 sensor nodes deployed in a real parking lot. The result shows that the presented car parking monitoring system is robust to changes in the communication environments and efficient for monitoring parking spaces of outdoor parking lots.

Keywords: multi-hop communication, parking monitoring system, TDMA, wireless sensor network

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11188 Experimental Monitoring of the Parameters of the Ionosphere in the Local Area Using the Results of Multifrequency GNSS-Measurements

Authors: Andrey Kupriyanov

Abstract:

In recent years, much attention has been paid to the problems of ionospheric disturbances and their influence on the signals of global navigation satellite systems (GNSS) around the world. This is due to the increase in solar activity, the expansion of the scope of GNSS, the emergence of new satellite systems, the introduction of new frequencies and many others. The influence of the Earth's ionosphere on the propagation of radio signals is an important factor in many applied fields of science and technology. The paper considers the application of the method of transionospheric sounding using measurements from signals from Global Navigation Satellite Systems to determine the TEC distribution and scintillations of the ionospheric layers. To calculate these parameters, the International Reference Ionosphere (IRI) model of the ionosphere, refined in the local area, is used. The organization of operational monitoring of ionospheric parameters is analyzed using several NovAtel GPStation6 base stations. It allows performing primary processing of GNSS measurement data, calculating TEC and fixing scintillation moments, modeling the ionosphere using the obtained data, storing data and performing ionospheric correction in measurements. As a result of the study, it was proved that the use of the transionospheric sounding method for reconstructing the altitude distribution of electron concentration in different altitude range and would provide operational information about the ionosphere, which is necessary for solving a number of practical problems in the field of many applications. Also, the use of multi-frequency multisystem GNSS equipment and special software will allow achieving the specified accuracy and volume of measurements.

Keywords: global navigation satellite systems (GNSS), GPstation6, international reference ionosphere (IRI), ionosphere, scintillations, total electron content (TEC)

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11187 Integrated Gas Turbine Performance Diagnostics and Condition Monitoring Using Adaptive GPA

Authors: Yi-Guang Li, Suresh Sampath

Abstract:

Gas turbine performance degrades over time, and the degradation is greatly affected by environmental, ambient, and operating conditions. The engines may degrade slowly under favorable conditions and result in a waste of engine life if a scheduled maintenance scheme is followed. They may also degrade fast and fail before a scheduled overhaul if the conditions are unfavorable, resulting in serious secondary damage, loss of engine availability, and increased maintenance costs. To overcome these problems, gas turbine owners are gradually moving from scheduled maintenance to condition-based maintenance, where condition monitoring is one of the key supporting technologies. This paper presents an integrated adaptive GPA diagnostics and performance monitoring system developed at Cranfield University for gas turbine gas path condition monitoring. It has the capability to predict the performance degradation of major gas path components of gas turbine engines, such as compressors, combustors, and turbines, using gas path measurement data. It is also able to predict engine key performance parameters for condition monitoring, such as turbine entry temperature that cannot be directly measured. The developed technology has been implemented into digital twin computer Software, Pythia, to support the condition monitoring of gas turbine engines. The capabilities of the integrated GPA condition monitoring system are demonstrated in three test cases using a model gas turbine engine similar to the GE aero-derivative LM2500 engine widely used in power generation and marine propulsion. It shows that when the compressor of the model engine degrades, the Adaptive GPA is able to predict the degradation and the changing engine performance accurately using gas path measurements. Such a presented technology and software are generic, can be applied to different types of gas turbine engines, and provide crucial engine health and performance parameters to support condition monitoring and condition-based maintenance.

Keywords: gas turbine, adaptive GPA, performance, diagnostics, condition monitoring

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11186 A Building Structure Health Monitoring DeviceBased on Cost Effective 1-Axis Accelerometers

Authors: Chih Hsing Lin, Wen-Ching Chen, Ssu-Ying Chen, Chih-Chyau Yang, Chien-Ming Wu, Chun-Ming Huang

Abstract:

Critical structures such as buildings, bridges and dams require periodic inspections to ensure safe operation. The reliable inspection of structures can be achieved by combing temperature sensor and accelerometers. In this work, we propose a building structure health monitoring device (BSHMD) with using three 1-axis accelerometers, gateway, analog to digital converter (ADC), and data logger to monitoring the building structure. The proposed BSHMD achieves the features of low cost by using three 1-axis accelerometers with the data synchronization problem being solved, and easily installation and removal. Furthermore, we develop a packet acquisition program to receive the sensed data and then classify it based on time and date. Compared with 3-axis accelerometer, our proposed 1-axis accelerometers based device achieves 64.3% cost saving. Compared with previous structural monitoring device, the BSHMD achieves 89% area saving. Therefore, with using the proposed device, the realtime diagnosis system for building damage monitoring can be conducted effectively.

Keywords: building structure health monitoring, cost effective, 1-axis accelerometers, real-time diagnosis

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11185 Ensuring Safe Operation by Providing an End-To-End Field Monitoring and Incident Management Approach for Autonomous Vehicle Based on ML/Dl SW Stack

Authors: Lucas Bublitz, Michael Herdrich

Abstract:

By achieving the first commercialization approval in San Francisco the Autonomous Driving (AD) industry proves the technology maturity of the SAE L4 AD systems and the corresponding software and hardware stack. This milestone reflects the upcoming phase in the industry, where the focus is now about scaling and supervising larger autonomous vehicle (AV) fleets in different operation areas. This requires an operation framework, which organizes and assigns responsibilities to the relevant AV technology and operation stakeholders from the AV system provider, the Remote Intervention Operator, the MaaS provider and regulatory & approval authority. This holistic operation framework consists of technological, processual, and organizational activities to ensure safe operation for fully automated vehicles. Regarding the supervision of large autonomous vehicle fleets, a major focus is on the continuous field monitoring. The field monitoring approach must reflect the safety and security criticality of incidents in the field during driving operation. This includes an automatic containment approach, with the overall goal to avoid safety critical incidents and reduce downtime by a malfunction of the AD software stack. An End-to-end (E2E) field monitoring approach detects critical faults in the field, uses a knowledge-based approach for evaluating the safety criticality and supports the automatic containment of these E/E faults. Applying such an approach will ensure the scalability of AV fleets, which is determined by the handling of incidents in the field and the continuous regulatory compliance of the technology after enhancing the Operational Design Domain (ODD) or the function scope by Functions on Demand (FoD) over the entire digital product lifecycle.

Keywords: field monitoring, incident management, multicompliance management for AI in AD, root cause analysis, database approach

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11184 An Application of a Machine Monitoring by Using the Internet of Things to Improve a Preventive Maintenance: Case Study of an Automated Plastic Granule-Packing Machine

Authors: Anek Apipatkul, Paphakorn Pitayachaval

Abstract:

Preventive maintenance is a standardized procedure to control and prevent risky problems affecting production in order to increase work efficiency. Machine monitoring also routinely works to collect data for a scheduling maintenance period. This paper is to present the application of machine monitoring by using the internet of things (IOTs) and a lean technique in order to manage with complex maintenance tasks of an automated plastic granule packing machine. To organize the preventive maintenance, there are several processes that the machine monitoring was applied, starting with defining a clear scope of the machine, establishing standards in maintenance work, applying a just-in-time (JIT) technique for timely delivery in the maintenance work, solving problems on the floor, and also improving the inspection process. The result has shown that wasted time was reduced, and machines have been operated as scheduled. Furthermore, the efficiency of the scheduled maintenance period was increased by 95%.

Keywords: internet of things, preventive maintenance, machine monitoring, lean technique

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11183 Bridge Health Monitoring: A Review

Authors: Mohammad Bakhshandeh

Abstract:

Structural Health Monitoring (SHM) is a crucial and necessary practice that plays a vital role in ensuring the safety and integrity of critical structures, and in particular, bridges. The continuous monitoring of bridges for signs of damage or degradation through Bridge Health Monitoring (BHM) enables early detection of potential problems, allowing for prompt corrective action to be taken before significant damage occurs. Although all monitoring techniques aim to provide accurate and decisive information regarding the remaining useful life, safety, integrity, and serviceability of bridges, understanding the development and propagation of damage is vital for maintaining uninterrupted bridge operation. Over the years, extensive research has been conducted on BHM methods, and experts in the field have increasingly adopted new methodologies. In this article, we provide a comprehensive exploration of the various BHM approaches, including sensor-based, non-destructive testing (NDT), model-based, and artificial intelligence (AI)-based methods. We also discuss the challenges associated with BHM, including sensor placement and data acquisition, data analysis and interpretation, cost and complexity, and environmental effects, through an extensive review of relevant literature and research studies. Additionally, we examine potential solutions to these challenges and propose future research ideas to address critical gaps in BHM.

Keywords: structural health monitoring (SHM), bridge health monitoring (BHM), sensor-based methods, machine-learning algorithms, and model-based techniques, sensor placement, data acquisition, data analysis

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11182 Soil Bioremediation Monitoring Systems Powered by Microbial Fuel Cells

Authors: András Fülöp, Lejla Heilmann, Zsolt Szabó, Ákos Koós

Abstract:

Microbial fuel cells (MFCs) present a sustainable biotechnological solution to future energy demands. The aim of this study was to construct soil based, single cell, membrane-less MFC systems, operated without treatment to continuously power on-site monitoring and control systems during the soil bioremediation processes. Our Pseudomonas aeruginosa 541 isolate is an ideal choice for MFCs, because it is able to produce pyocyanin which behaves as electron-shuttle molecule, furthermore, it also has a significant antimicrobial effect. We tested several materials and structural configurations to obtain long term high power output. Comparing different configurations, a proton exchange membrane-less, 0.6 m long with 0.05 m diameter MFC tubes offered the best long-term performances. The long-term electricity production were tested from starch, yeast extract (YE), carboxymethyl cellulose (CMC) with humic acid (HA) as a mediator. In all cases, 3 kΩ external load have been used. The two best-operated systems were the Pseudomonas aeruginosa 541 containing MFCs with 1 % carboxymethyl cellulose and the MFCs with 1% yeast extract in the anode area and 35% hydrogel in the cathode chamber. The first had 3.3 ± 0.033 mW/m2 and the second had 4.1 ± 0.065 mW/m2 power density values. These systems have operated for 230 days without any treatment. The addition of 0.2 % HA and 1 % YE referred to the volume of the anode area resulted in 1.4 ± 0.035 mW/m2 power densities. The mixture of 1% starch with 0.2 % HA gave 1.82 ± 0.031 mW/m2. Using CMC as retard carbon source takes effect in the long-term bacterial survivor, thus enable the expression of the long term power output. The application of hydrogels in the cathode chamber significantly increased the performance of the MFC units due to their good water retention capacity.

Keywords: microbial fuel cell, bioremediation, Pseudomonas aeruginosa, biotechnological solution

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11181 Smart Side View Mirror Camera for Real Time System

Authors: Nunziata Ivana Guarneri, Arcangelo Bruna, Giuseppe Spampinato, Antonio Buemi

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In the last decade, automotive companies have invested a lot in terms of innovation about many aspects regarding the automatic driver assistance systems. One innovation regards the usage of a smart camera placed on the car’s side mirror for monitoring the back and lateral road situation. A common road scenario is the overtaking of the preceding car and, in this case, a brief distraction or a loss of concentration can lead the driver to undertake this action, even if there is an already overtaking vehicle, leading to serious accidents. A valid support for a secure drive can be a smart camera system, which is able to automatically analyze the road scenario and consequentially to warn the driver when another vehicle is overtaking. This paper describes a method for monitoring the side view of a vehicle by using camera optical flow motion vectors. The proposed solution detects the presence of incoming vehicles, assesses their distance from the host car, and warns the driver through different levels of alert according to the estimated distance. Due to the low complexity and computational cost, the proposed system ensures real time performances.

Keywords: camera calibration, ego-motion, Kalman filters, object tracking, real time systems

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11180 Factor Study Affecting Visual Awareness on Dynamic Object Monitoring

Authors: Terry Liang Khin Teo, Sun Woh Lye, Kai Lun Brendon Goh

Abstract:

As applied to dynamic monitoring situations, the prevailing approach to situation awareness (SA) assumes that the relevant areas of interest (AOI) be perceived before that information can be processed further to affect decision-making and, thereafter, action. It is not entirely clear whether this is the case. This study seeks to investigate the monitoring of dynamic objects through matching eye fixations with the relevant AOIs in boundary-crossing scenarios. By this definition, a match is where a fixation is registered on the AOI. While many factors may affect monitoring characteristics, traffic simulations were designed in this study to explore two factors, namely: the number of inbounds/outbound traffic transfers and the number of entry and/or exit points in a radar monitoring sector. These two factors were graded into five levels of difficulty ranging from low to high traffic flow numbers. Combined permutation in terms of levels of difficulty of these two factors yielded a total of thirty scenarios. Through this, results showed that changes in the traffic flow numbers on transfer resulted in greater variations having match limits ranging from 29%-100%, as compared to the number of sector entry/exit points of range limit from 80%-100%. The subsequent analysis is able to determine the type and combination of traffic scenarios where imperfect matching is likely to occur.

Keywords: air traffic simulation, eye-tracking, visual monitoring, focus attention

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11179 Preference Heterogeneity as a Positive Rather Than Negative Factor towards Acceptable Monitoring Schemes: Co-Management of Artisanal Fishing Communities in Vietnam

Authors: Chi Nguyen Thi Quynh, Steven Schilizzi, Atakelty Hailu, Sayed Iftekhar

Abstract:

Territorial Use Rights for Fisheries (TURFs) have been emerged as a promising tool for fisheries conservation and management. However, illegal fishing has undermined the effectiveness of TURFs, profoundly degrading global fish stocks and marine ecosystems. Conservation and management of fisheries, therefore, largely depends on effectiveness of enforcing fishing regulations, which needs co-enforcement by fishers. However, fishers tend to resist monitoring participation, as their views towards monitoring scheme design has not been received adequate attention. Fishers’ acceptability of a monitoring scheme is likely to be achieved if there is a mechanism allowing fishers to engage in the early planning and design stages. This study carried out a choice experiment with 396 fishers in Vietnam to elicit fishers’ preferences for monitoring scheme and to estimate the relative importance that fishers place on the key design elements. Preference heterogeneity was investigated using a Scale-Adjusted Latent Class Model that accounts for both preference and scale variance. Welfare changes associated with the proposed monitoring schemes were also examined. It is found that there are five distinct preference classes, suggesting that there is no one-size-fits-all scheme well-suited to all fishers. Although fishers prefer to be compensated more for their participation, compensation is not a driving element affecting fishers’ choice. Most fishers place higher value on other elements, such as institutional arrangements and monitoring capacity. Fishers’ preferences are driven by their socio-demographic and psychological characteristics. Understanding of how changes in design elements’ levels affect the participation of fishers could provide policy makers with insights useful for monitoring scheme designs tailored to the needs of different fisher classes.

Keywords: Design of monitoring scheme, Enforcement, Heterogeneity, Illegal Fishing, Territorial Use Rights for Fisheries

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11178 Kalman Filter Design in Structural Identification with Unknown Excitation

Authors: Z. Masoumi, B. Moaveni

Abstract:

This article is about first step of structural health monitoring by identifying structural system in the presence of unknown input. In the structural system identification, identification of structural parameters such as stiffness and damping are considered. In this study, the Kalman filter (KF) design for structural systems with unknown excitation is expressed. External excitations, such as earthquakes, wind or any other forces are not measured or not available. The purpose of this filter is its strengths to estimate the state variables of the system in the presence of unknown input. Also least squares estimation (LSE) method with unknown input is studied. Estimates of parameters have been adopted. Finally, using two examples advantages and drawbacks of both methods are studied.

Keywords: Kalman filter (KF), least square estimation (LSE), structural health monitoring (SHM), structural system identification

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11177 Bayesian Inference of Physicochemical Quality Elements of Tropical Lagoon Nokoué (Benin)

Authors: Hounyèmè Romuald, Maxime Logez, Mama Daouda, Argillier Christine

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In view of the very strong degradation of aquatic ecosystems, it is urgent to set up monitoring systems that are best able to report on the effects of the stresses they undergo. This is particularly true in developing countries, where specific and relevant quality standards and funding for monitoring programs are lacking. The objective of this study was to make a relevant and objective choice of physicochemical parameters informative of the main stressors occurring on African lakes and to identify their alteration thresholds. Based on statistical analyses of the relationship between several driving forces and the physicochemical parameters of the Nokoué lagoon, relevant Physico-chemical parameters were selected for its monitoring. An innovative method based on Bayesian statistical modeling was used. Eleven Physico-chemical parameters were selected for their response to at least one stressor and their threshold quality standards were also established: Total Phosphorus (<4.5mg/L), Orthophosphates (<0.2mg/L), Nitrates (<0.5 mg/L), TKN (<1.85 mg/L), Dry Organic Matter (<5 mg/L), Dissolved Oxygen (>4 mg/L), BOD (<11.6 mg/L), Salinity (7.6 .), Water Temperature (<28.7 °C), pH (>6.2), and Transparency (>0.9 m). According to the System for the Evaluation of Coastal Water Quality, these thresholds correspond to” good to medium” suitability classes, except for total phosphorus. One of the original features of this study is the use of the bounds of the credibility interval of the fixed-effect coefficients as local weathering standards for the characterization of the Physico-chemical status of this anthropized African ecosystem.

Keywords: driving forces, alteration thresholds, acadjas, monitoring, modeling, human activities

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11176 Real-Time Nonintrusive Heart Rate Measurement: Comparative Case Study of LED Sensorics' Accuracy and Benefits in Heart Monitoring

Authors: Goran Begović

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In recent years, many researchers are focusing on non-intrusive measuring methods when it comes to human biosignals. These methods provide solutions for everyday use, whether it’s health monitoring or finessing the workout routine. One of the biggest issues with these solutions is that the sensors’ accuracy is highly variable due to many factors, such as ambiental light, skin color diversity, etc. That is why we wanted to explore different outcomes under those kinds of circumstances in order to find the most optimal algorithm(s) for extracting heart rate (HR) information. The optimization of such algorithms can benefit the wider, cheaper, and safer application of home health monitoring, without having to visit medical professionals as often when it comes to observing heart irregularities. In this study, we explored the accuracy of infrared (IR), red, and green LED sensorics in a controlled environment and compared the results with a medically accurate ECG monitoring device.

Keywords: data science, ECG, heart rate, holter monitor, LED sensors

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11175 Hypergraph for System of Systems modeling

Authors: Haffaf Hafid

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Hypergraphs, after being used to model the structural organization of System of Sytems (SoS) at macroscopic level, has recent trends towards generalizing this powerful representation at different stages of complex system modelling. In this paper, we first describe different applications of hypergraph theory, and step by step, introduce multilevel modeling of SoS by means of integrating Constraint Programming Langages (CSP) dealing with engineering system reconfiguration strategy. As an application, we give an A.C.T Terminal controlled by a set of Intelligent Automated Vehicle.

Keywords: hypergraph model, structural analysis, bipartite graph, monitoring, system of systems, reconfiguration analysis, hypernetwork

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11174 Disaster Management Supported by Unmanned Aerial Systems

Authors: Agoston Restas

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Introduction: This paper describes many initiatives and shows also practical examples which happened recently using Unmanned Aerial Systems (UAS) to support disaster management. Since the operation of manned aircraft at disasters is usually not only expensive but often impossible to use as well, in many cases managers fail to use the aerial activity. UAS can be an alternative moreover cost-effective solution for supporting disaster management. Methods: This article uses thematic division of UAS applications; it is based on two key elements, one of them is the time flow of managing disasters, other is its tactical requirements. Logically UAS can be used like pre-disaster activity, activity immediately after the occurrence of a disaster and the activity after the primary disaster elimination. Paper faces different disasters, like dangerous material releases, floods, earthquakes, forest fires and human-induced disasters. Research used function analysis, practical experiments, mathematical formulas, economic analysis and also expert estimation. Author gathered international examples and used own experiences in this field as well. Results and discussion: An earthquake is a rapid escalating disaster, where, many times, there is no other way for a rapid damage assessment than aerial reconnaissance. For special rescue teams, the UAS application can help much in a rapid location selection, where enough place remained to survive for victims. Floods are typical for a slow onset disaster. In contrast, managing floods is a very complex and difficult task. It requires continuous monitoring of dykes, flooded and threatened areas. UAS can help managers largely keeping an area under observation. Forest fires are disasters, where the tactical application of UAS is already well developed. It can be used for fire detection, intervention monitoring and also for post-fire monitoring. In case of nuclear accident or hazardous material leakage, UAS is also a very effective or can be the only one tool for supporting disaster management. Paper shows some efforts using UAS to avoid human-induced disasters in low-income countries as part of health cooperation.

Keywords: disaster management, floods, forest fires, Unmanned Aerial Systems

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11173 Impact of Digitized Monitoring & Evaluation System in Technical Vocational Education and Training

Authors: Abdul Ghani Rajput

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Although monitoring and evaluation concept adopted by Technical Vocational Education and Training (TVET) organization to track the progress over the continuous interval of time based on planned interventions and subsequently, evaluating it for the impact, quality assurance and sustainability. In digital world, TVET providers are giving preference to have real time information to do monitoring of training activities. Identifying the benefits and challenges of digitized monitoring & evaluation real time information system has not been sufficiently tackled in this date. This research paper looks at the impact of digitized M&E in TVET sector by analyzing two case studies and describe the benefits and challenges of using digitized M&E system. Finally, digitized M&E have been identified as carriers for high potential of TVET sector.

Keywords: digitized M&E, innovation, quality assurance, TVET

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11172 Science and Monitoring Underpinning River Restoration: A Case Study

Authors: Geoffrey Gilfillan, Peter Barham, Lisa Smallwood, David Harper

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The ‘Welland for People and Wildlife’ project aimed to improve the River Welland’s ecology and water quality, and to make it more accessible to the community of Market Harborough. A joint monitoring project by the Welland Rivers Trust & University of Leicester was incorporated into the design. The techniques that have been used to measure its success are hydrological, geomorphological, and water quality monitoring, species and habitat surveys, and community engagement. Early results show improvements to flow and habitat diversity, water quality and biodiversity of the river environment. Barrier removal has increased stickleback mating activity, and decreased parasitically infected fish in sample catches. The habitats provided by the berms now boast over 25 native plant species, and the river is clearer, cleaner and with better-oxygenated water.

Keywords: community engagement, ecological monitoring, river restoration, water quality

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11171 Application of a Model-Free Artificial Neural Networks Approach for Structural Health Monitoring of the Old Lidingö Bridge

Authors: Ana Neves, John Leander, Ignacio Gonzalez, Raid Karoumi

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Systematic monitoring and inspection are needed to assess the present state of a structure and predict its future condition. If an irregularity is noticed, repair actions may take place and the adequate intervention will most probably reduce the future costs with maintenance, minimize downtime and increase safety by avoiding the failure of the structure as a whole or of one of its structural parts. For this to be possible decisions must be made at the right time, which implies using systems that can detect abnormalities in their early stage. In this sense, Structural Health Monitoring (SHM) is seen as an effective tool for improving the safety and reliability of infrastructures. This paper explores the decision-making problem in SHM regarding the maintenance of civil engineering structures. The aim is to assess the present condition of a bridge based exclusively on measurements using the suggested method in this paper, such that action is taken coherently with the information made available by the monitoring system. Artificial Neural Networks are trained and their ability to predict structural behavior is evaluated in the light of a case study where acceleration measurements are acquired from a bridge located in Stockholm, Sweden. This relatively old bridge is presently still in operation despite experiencing obvious problems already reported in previous inspections. The prediction errors provide a measure of the accuracy of the algorithm and are subjected to further investigation, which comprises concepts like clustering analysis and statistical hypothesis testing. These enable to interpret the obtained prediction errors, draw conclusions about the state of the structure and thus support decision making regarding its maintenance.

Keywords: artificial neural networks, clustering analysis, model-free damage detection, statistical hypothesis testing, structural health monitoring

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11170 Feasibility Study of Wireless Communication for the Control and Monitoring of Rotating Electrical Machine

Authors: S. Ben Brahim, T. H. Vuong, J. David, R. Bouallegue, M. Pietrzak-David

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Electrical machine monitoring is important to protect motor from unexpected problems. Today, using wireless communication for electrical machines is interesting for both real time monitoring and diagnostic purposes. In this paper, we propose a system based on wireless communication IEEE 802.11 to control electrical machine. IEEE 802.11 standard is recommended for this type of applications because it provides a faster connection, better range from the base station, and better security. Therefore, our contribution is to study a new technique to control and monitor the rotating electrical machines (motors, generators) using wireless communication. The reliability of radio channel inside rotating electrical machine is also discussed. Then, the communication protocol, software and hardware design used for the proposed system are presented in detail and the experimental results of our system are illustrated.

Keywords: control, DFIM machine, electromagnetic field, EMC, IEEE 802.11, monitoring, rotating electrical machines, wireless communication

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11169 Model of Monitoring and Evaluation of Student’s Learning Achievement: Application of Value-Added Assessment

Authors: Jatuphum Ketchatturat

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Value-added assessment has been used for developing the model of monitoring and evaluation of student's learning achievement. The steps of model development consist of 1) study and analyisis of the school and the district report system of student achievement and progress, 2) collecting the data of student achievement to develop the value added indicator, 3) developing the system of value-added assessment by participatory action research approach, 4) putting the system of value-added assessment into the educational district of secondary school, 5) determining the quality of the developed system of value-added assessment. The components of the developed model consist of 1) the database of value-added assessment of student's learning achievement, 2) the process of monitoring and evaluation the student's learning achievement, and 3) the reporting system of value-added assessment of student's learning achievement.

Keywords: learning achievement, monitoring and evaluation, value-added assessment

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11168 Participatory Air Quality Monitoring in African Cities: Empowering Communities, Enhancing Accountability, and Ensuring Sustainable Environments

Authors: Wabinyai Fidel Raja, Gideon Lubisa

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Air pollution is becoming a growing concern in Africa due to rapid industrialization and urbanization, leading to implications for public health and the environment. Establishing a comprehensive air quality monitoring network is crucial to combat this issue. However, conventional methods of monitoring are insufficient in African cities due to the high cost of setup and maintenance. To address this, low-cost sensors (LCS) can be deployed in various urban areas through the use of participatory air quality network siting (PAQNS). PAQNS involves stakeholders from the community, local government, and private sector working together to determine the most appropriate locations for air quality monitoring stations. This approach improves the accuracy and representativeness of air quality monitoring data, engages and empowers community members, and reflects the actual exposure of the population. Implementing PAQNS in African cities can build trust, promote accountability, and increase transparency in the air quality management process. However, challenges to implementing this approach must be addressed. Nonetheless, improving air quality is essential for protecting public health and promoting a sustainable environment. Implementing participatory and data-informed air quality monitoring can take a significant step toward achieving these important goals in African cities and beyond.

Keywords: low-cost sensors, participatory air quality network siting, air pollution, air quality management

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11167 Application of Combined Cluster and Discriminant Analysis to Make the Operation of Monitoring Networks More Economical

Authors: Norbert Magyar, Jozsef Kovacs, Peter Tanos, Balazs Trasy, Tamas Garamhegyi, Istvan Gabor Hatvani

Abstract:

Water is one of the most important common resources, and as a result of urbanization, agriculture, and industry it is becoming more and more exposed to potential pollutants. The prevention of the deterioration of water quality is a crucial role for environmental scientist. To achieve this aim, the operation of monitoring networks is necessary. In general, these networks have to meet many important requirements, such as representativeness and cost efficiency. However, existing monitoring networks often include sampling sites which are unnecessary. With the elimination of these sites the monitoring network can be optimized, and it can operate more economically. The aim of this study is to illustrate the applicability of the CCDA (Combined Cluster and Discriminant Analysis) to the field of water quality monitoring and optimize the monitoring networks of a river (the Danube), a wetland-lake system (Kis-Balaton & Lake Balaton), and two surface-subsurface water systems on the watershed of Lake Neusiedl/Lake Fertő and on the Szigetköz area over a period of approximately two decades. CCDA combines two multivariate data analysis methods: hierarchical cluster analysis and linear discriminant analysis. Its goal is to determine homogeneous groups of observations, in our case sampling sites, by comparing the goodness of preconceived classifications obtained from hierarchical cluster analysis with random classifications. The main idea behind CCDA is that if the ratio of correctly classified cases for a grouping is higher than at least 95% of the ratios for the random classifications, then at the level of significance (α=0.05) the given sampling sites don’t form a homogeneous group. Due to the fact that the sampling on the Lake Neusiedl/Lake Fertő was conducted at the same time at all sampling sites, it was possible to visualize the differences between the sampling sites belonging to the same or different groups on scatterplots. Based on the results, the monitoring network of the Danube yields redundant information over certain sections, so that of 12 sampling sites, 3 could be eliminated without loss of information. In the case of the wetland (Kis-Balaton) one pair of sampling sites out of 12, and in the case of Lake Balaton, 5 out of 10 could be discarded. For the groundwater system of the catchment area of Lake Neusiedl/Lake Fertő all 50 monitoring wells are necessary, there is no redundant information in the system. The number of the sampling sites on the Lake Neusiedl/Lake Fertő can decrease to approximately the half of the original number of the sites. Furthermore, neighbouring sampling sites were compared pairwise using CCDA and the results were plotted on diagrams or isoline maps showing the location of the greatest differences. These results can help researchers decide where to place new sampling sites. The application of CCDA proved to be a useful tool in the optimization of the monitoring networks regarding different types of water bodies. Based on the results obtained, the monitoring networks can be operated more economically.

Keywords: combined cluster and discriminant analysis, cost efficiency, monitoring network optimization, water quality

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11166 Application of Remote Sensing Technique on the Monitoring of Mine Eco-Environment

Authors: Haidong Li, Weishou Shen, Guoping Lv, Tao Wang

Abstract:

Aiming to overcome the limitation of the application of traditional remote sensing (RS) technique in the mine eco-environmental monitoring, in this paper, we first classified the eco-environmental damages caused by mining activities and then introduced the principle, classification and characteristics of the Light Detection and Ranging (LiDAR) technique. The potentiality of LiDAR technique in the mine eco-environmental monitoring was analyzed, particularly in extracting vertical structure parameters of vegetation, through comparing the feasibility and applicability of traditional RS method and LiDAR technique in monitoring different types of indicators. The application situation of LiDAR technique in extracting typical mine indicators, such as land destruction in mining areas, damage of ecological integrity and natural soil erosion. The result showed that the LiDAR technique has the ability to monitor most of the mine eco-environmental indicators, and exhibited higher accuracy comparing with traditional RS technique, specifically speaking, the applicability of LiDAR technique on each indicator depends on the accuracy requirement of mine eco-environmental monitoring. In the item of large mine, LiDAR three-dimensional point cloud data not only could be used as the complementary data source of optical RS, Airborne/Satellite LiDAR could also fulfill the demand of extracting vertical structure parameters of vegetation in large areas.

Keywords: LiDAR, mine, ecological damage, monitoring, traditional remote sensing technique

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11165 Examination of Corrosion Durability Related to Installed Environments of Steel Bridges

Authors: Jin-Hee Ahn, Seok-Hyeon Jeon, Young-Bin Lee, Min-Gyun Ha, Yu-Chan Hong

Abstract:

Corrosion durability of steel bridges can be generally affected by atmospheric environments of bridge installation, since corrosion problem is related to environmental factors such as humidity, temperature, airborne salt, chemical components as SO₂, chlorides, etc. Thus, atmospheric environment condition should be measured to estimate corrosion condition of steel bridges as well as measurement of actual corrosion damage of structural members of steel bridge. Even in the same atmospheric environment, the corrosion environment may be different depending on the installation direction of structural members. In this study, therefore, atmospheric corrosion monitoring was conducted using atmospheric corrosion monitoring sensor, hygrometer, thermometer and airborne salt collection device to examine the corrosion durability of steel bridges. As a target steel bridge for corrosion durability monitoring, a cable-stayed bridge with truss steel members was selected. This cable-stayed bridge was located on the coast to connect the islands with the islands. Especially, atmospheric corrosion monitoring was carried out depending on structural direction of a cable-stayed bridge with truss type girders since it consists of structural members with various directions. For atmospheric corrosion monitoring, daily average electricity (corrosion current) was measured at each monitoring members to evaluate corrosion environments and corrosion level depending on structural members with various direction which have different corrosion environment in the same installed area. To compare corrosion durability connected with monitoring data depending on corrosion monitoring members, monitoring steel plate was additionally installed in same monitoring members. Monitoring steel plates of carbon steel was fabricated with dimension of 60mm width and 3mm thickness. And its surface was cleaned for removing rust on the surface by blasting, and its weight was measured before its installation on each structural members. After a 3 month exposure period on real atmospheric corrosion environment at bridge, surface condition of atmospheric corrosion monitoring sensors and monitoring steel plates were observed for corrosion damage. When severe deterioration of atmospheric corrosion monitoring sensors or corrosion damage of monitoring steel plates were found, they were replaced or collected. From 3month exposure tests in the actual steel bridge with various structural member with various direction, the rust on the surface of monitoring steel plate was found, and the difference in the corrosion rate was found depending on the direction of structural member from their visual inspection. And daily average electricity (corrosion current) was changed depending on the direction of structural member. However, it is difficult to identify the relative differences in corrosion durability of steel structural members using short-term monitoring results. After long exposure tests in this corrosion environments, it can be clearly evaluated the difference in corrosion durability depending on installed conditions of steel bridges. Acknowledgements: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1B03028755).

Keywords: corrosion, atmospheric environments, steel bridge, monitoring

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11164 GSM Based Smart Patient Monitoring System

Authors: Ayman M. Mansour

Abstract:

In this paper, we propose an intelligent system that is used for monitoring the health conditions of Patients. Monitoring the health condition of Patients is a complex problem that involves different medical units and requires continuous monitoring especially in rural areas because of inadequate number of available specialized physicians. The proposed system will Improve patient care and drive costs down comparing to the existing system in Jordan. The proposed system will be the start point to Faster and improve the communication between different units in the health system in Jordan. Connecting patients and their physicians beyond hospital doors regarding their geographical area is an important issue in developing the health system in Jordan. The propose system will provide an intelligent system that will generate initial diagnosing to the patient case. This will assist and advice clinicians at the point of care. The decision is based on demographic data and laboratory test results of patient data. Using such system with the ability of making medical decisions, the quality of medical care in Jordan and specifically in Tafial is expected to be improved. This will provide more accurate, effective, and reliable diagnoses and treatments especially if the physicians have insufficient knowledge.

Keywords: GSM, SMS, patient, monitoring system, fuzzy logic, multi-agent system

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11163 An Effective and Efficient Web Platform for Monitoring, Control, and Management of Drones Supported by a Microservices Approach

Authors: Jorge R. Santos, Pedro Sebastiao

Abstract:

In recent years there has been a great growth in the use of drones, being used in several areas such as security, agriculture, or research. The existence of some systems that allow the remote control of drones is a reality; however, these systems are quite simple and directed to specific functionality. This paper proposes the development of a web platform made in Vue.js and Node.js to control, manage, and monitor drones in real time. Using a microservice architecture, the proposed project will be able to integrate algorithms that allow the optimization of processes. Communication with remote devices is suggested via HTTP through 3G, 4G, and 5G networks and can be done in real time or by scheduling routes. This paper addresses the case of forest fires as one of the services that could be included in a system similar to the one presented. The results obtained with the elaboration of this project were a success. The communication between the web platform and drones allowed its remote control and monitoring. The incorporation of the fire detection algorithm in the platform proved possible a real time analysis of the images captured by the drone without human intervention. The proposed system has proved to be an asset to the use of drones in fire detection. The architecture of the application developed allows other algorithms to be implemented, obtaining a more complex application with clear expansion.

Keywords: drone control, microservices, node.js, unmanned aerial vehicles, vue.js

Procedia PDF Downloads 99