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Dynamic Rescheduling for Optimal Transportation Incident Management in Inland Waterways

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2024年第10期25卷 14642-14653页

作者： Nadales, Juan M. de la Pena, David Munoz Limon, Daniel Alamo, Teodoro Univ Seville Dept Syst & Automat Engn Seville 41092 Andalusia Spain

This paper proposes a novel two-layer monitoring and rescheduling approach designed for vessels navigating natural inland waterways, addressing diverse scenarios such as arrival delays, speed reductions, and machinery failures. Firstly, a methodology for incident detection and classification is proposed, which compares the planned trajectory of the vessels with their actual position provided by an automatic identification system. Secondly, in case an incident is detected, the plan for each vessel is rescheduled. To achieve this, various rescheduling strategies are proposed, taking into account the particularities of each incident. The aim is not only to ensure the safety and efficiency of the operation but also to minimize the impact of rescheduling on the original plan, thus averting any negative repercussions on the port's reputation. Different simulations have been carried out taking the Guadalquivir River as an example, demonstrating the efficiency of the proposed methodology in preventing incidents and ensuring optimality.

关键词： Marine transportation intelligent transportation risk management optimal scheduling computerized monitoring classification tree analysis

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Automated monitoring of Construction Sites of Electric Power Substations Using Deep Learning

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IEEE ACCESS 2021年 9卷 19195-19207页

作者： Soares Oliveira, Bruno Alberto De Faria Neto, Abilio Pereira Arruda Fernandino, Roberto Marcio Carvalho, Rogerio Fernandes Fernandes, Amanda Lopes Guimaraes, Frederico Gadelha Univ Fed Minas Gerais Grad Program Elect Engn BR-31270901 Belo Horizonte MG Brazil SVA Tech BR-30130165 Belo Horizonte MG Brazil CPFL Energia Innovat Projects BR-13088900 Campinas Brazil

With each passing year, the consumption of electric energy in Brazil and the world increases, making it necessary to adopt measures such as the construction of new plants and the installation of power distribution structures. monitoring for construction management in companies is still done in person and manually, resulting in expenses that could be avoided. That said, there are opportunities to automate such processes using artificial intelligence and, therefore, the main objective of this work is the development of an automated constructions management system, whose goal is to increase the management and monitoring of substation constructions with the remote monitoring. The system incorporates resources of deep learning to classify the components in bays, comparing the data generated in this recognition with the engineering projects to verify the progress of the installation of these components and generating indicators of conformity and evolution of the construction. To achieve the main objective, a comparison was made among four convolutional neural network architectures: DenseNet, Inception, ResNet, and SqueezeNet, in the classification task. The models were trained with thousands of images extracted from photos of different bays captured in the field and, additionally, data augmentation techniques were applied. The models were trained using transfer learning and fine tuning starting from pre-trained weights in the ImageNet data set. All models obtained results close to 100% in the images of the test set, hence it is possible to conclude that, for the proposed problem, there was no significant difference between the assertiveness of the architectures. The chosen model was part of the final application that monitors the construction management of the bays in the electricity substations.

关键词： Substations monitoring Deep learning Computer architecture Convolutional neural networks Companies Visualization Computer vision computerized monitoring construction management image classification machine learning

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Preventing Pressure Ulcers by Image based Posture Detection 36

Preventing Pressure Ulcers by Image based Posture Detection

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36th IEEE International Symposium on Computer-Based Medical Systems (CBMS)

作者： Soleiunani, Ramin Pesch, Dirk Univ Coll Cork Sch Comp Sci & Informat Technol Cork Ireland

ISBN: (纸本)9798350312249

Pressure ulcers, also known as pressure sores or bedsores, are a disease affecting the skin and underlying tissue that mostly occurs over bony parts of the body because of long-term exposure to pressure. Pressure ulcers most commonly develop in patients who are often bed- or chair-bound for long periods of time. When an ulcer occurs, its treatment is often complex and expensive. Relieving the pressure imposed on the patient skin is the most effective approach for preventing bedsores. Common practice in hospitals and nursing homes is to periodically repositioning the patient. Manually relieving patient skin pressure places a financial and physical burden on caregivers. In this paper, we are proposing a detection approach that optimally detects patient posture and spots at-risk locations on the body by using data from a pressure sensor array in a bed. Our novel ulcer detection solution is based on posture detection using an SVM-based classifier, whose performance was considerably boosted by the pre-processing pipeline we designed. The approach periodically generates outputs that can be used to trigger actuators in air-enabled mattresses to inflate and deflate the air in the target locations. This technique can also be used in robot-equipped beds to turn patients if needed to prevent bedsores. The generated outputs can also be used in reporting the patient's condition.

关键词： Image Processing Bedsore Pressure Ulcers Prevention computerized monitoring Support Vector Machine

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Workforce Analytics in Teleworking

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IEEE ACCESS 2021年 9卷 156451-156464页

作者： Kifor, Claudiu Vasile Nicolaescu, Sergiu Stefan Florea, Adrian Savescu, Roxana Florenta Receu, Ilie Tirlea, Anca Victoria Danut, Raluca Elena Lucian Blaga Univ Sibiu Res Ctr Sustainable Prod & Proc Sibiu 550024 Romania Lucian Blaga Univ Sibiu Dept Comp Sci & Elect Engn Sibiu 550024 Romania

The recent COVID-19 pandemic has accelerated the interest in new software tools to monitor the computer-based activities of employees working remotely (teleworking), and the demand for better analytics functionalities to be offered, focusing on employees' performance and work-life balance. In this paper, we aim to analyze the habits of teleworking employees based on their interaction with the computer: how the employees are involved in different types of activities (actual work, recreation, documentation), and which are the most intensive periods. A conceptual framework for workforce analytics was developed for this purpose, together with tools and applications, that can provide useful information on different categories of activities where employees are involved. Knowledge generation is performed in four phases: collecting, processing, organizing, and analyzing the data to create valuable insights for the organization. Based on this framework, we developed a case study in an IT company, where two categories of employees, developers and software consultants, were monitored for 114 days, with 3.5 million events being generated and processed. The results showed different habits for consultants and developers, in terms of working activity structure, working schedule, inactivity time and interaction with the computer. Differences were also identified when we compared our results with previous research that monitored software developers working in-house: remote workers tend to organize their program for a longer period during the workday, and spend less time on meetings but longer time for programming. On the other hand, both categories of employees (in-house and teleworkers) show highly fragmented work, switching windows after very short periods of activity, with a potential negative impact on productivity, progress on tasks, and quality of output. The research results can be used in future employee productivity studies when searching answers to a fundamental question f

关键词： Teleworking monitoring Tools Companies Software Productivity Task analysis computerized monitoring workforce analytics employee performance data processing data engineering data analytics

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Stereovision Tracking System for monitoring Loader Crane Tip Position

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IEEE ACCESS 2020年 8卷 223346-223358页

作者： Grudzinski, Marek Marchewka, Lukasz Pajor, Miroslaw Zietek, Ryszard West Pomeranian Univ Technol Fac Mech Engn & Mechatron PL-70310 Szczecin Poland

This paper presents the idea and experimental tests of a non-stationary stereovision system used for supervision of a loading crane. The system based on two independent gimbals, equipped with cameras, allows simultaneously to measure and track a group of individual spatial points. The four steps calibration procedure is required for each gimbal axis, camera optics, gimbals positions, and loading crane position. Modern camera systems have been widely applied in several fields of the industry allowing for accurate measurements and real-time quality control. The systems based on stereo camera models and appropriate image analysis algorithms can measure a group of spatial points, complex surfaces, small displacements, or vibrations. There are also several vision systems such as laser tracker, camera mounted on fully controlled rotating head (called gimbal), or TOF camera, which can be used to follow and measure real-time object displacements. Unfortunately, they all have significant individual limitations explained in this paper. Accuracy tests of 3D measurements including active tracking of length pattern and crane tip have been performed within a selected working area. Based on reconstructed 3D data points, different types of geometric errors have been presented. The results revealed effects of accuracy degradation on the workspace boundaries and for higher observation angles, as well as 3D data bias suggesting mechanical issues. Several improvements in calibration and gimbal construction might result in far enough accuracy for normal operations of the crane.

关键词： Cameras Cranes Three-dimensional displays Image reconstruction Calibration Measurement by laser beam Position measurement Mechatronics cameras calibration machine vision stereo vision remote monitoring computerized monitoring

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TEEMoN: A continuous performance monitoring framework for TEEs 20

TEEMoN: A continuous performance monitoring framework for TE...

引用

21st International Middleware Conference (Middleware)

作者： Krahn, Robert Dragoti, Donald Gregor, Franz Le Quoc, Do Schiavoni, Valerio Felber, Pascal Souza, Clenimar Brito, Andrey Fetzer, Christof Tech Univ Dresden Dresden Germany Scontain UG Dresden Germany Univ Neuchatel Neuchatel Switzerland Univ Fed Campina Grande Campina Grande Paraiba Brazil

ISBN: (纸本)9781450381536

Trusted Execution Environments (TEEs), such as Intel Software Guard eXtensions (SGX), are considered as a promising approach to resolve security challenges in clouds. TEEs protect the confidentiality and integrity of application code and data even against privileged attackers with root and physical access by providing an isolated secure memory area, i.e., enclaves. The security guarantees are provided by the CPU, thus even if system software is compromised, the attacker can never access the enclave's content. While this approach ensures strong security guarantees for applications, it also introduces a considerable runtime overhead in part by the limited availability of protected memory (enclave page cache). Currently, only a limited number of performance measurement tools for TEE-based applications exist and none offer performance monitoring and analysis during runtime. This paper presents TEEMON, the first continuous performance monitoring and analysis tool for TEE-based applications. TEEMON provides not only fine-grained performance metrics during runtime, but also assists the analysis of identifying causes of performance bottlenecks, e.g., excessive system calls. Our approach smoothly integrates with existing open-source tools (e.g., Prometheus or Grafana) towards a holistic monitoring solution, particularly optimized for systems deployed through Docker containers or Kubernetes and offers several dedicated metrics and visualizations. Our evaluation shows that TEEMON's overhead ranges from 5% to 17%.

关键词： computerized monitoring Trusted Execution Environments Performance monitoring

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A Smart Camera Trap for Detection of Endotherms and Ectotherms

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SENSORS 2022年第11期22卷 4094-4094页

作者： Corva, Dean M. Semianiw, Nathan, I Eichholtzer, Anne C. Adams, Scott D. Mahmud, M. A. Parvez Gaur, Kendrika Pestell, Angela J. L. Driscoll, Don A. Kouzani, Abbas Z. Deakin Univ Sch Engn Geelong Vic 3216 Australia Deakin Univ Sch Life & Environm Sci Burwood Vic 3125 Australia

Current camera traps use passive infrared triggers;therefore, they only capture images when animals have a substantially different surface body temperature than the background. Endothermic animals, such as mammals and birds, provide adequate temperature contrast to trigger cameras, while ectothermic animals, such as amphibians, reptiles, and invertebrates, do not. Therefore, a camera trap that is capable of monitoring ectotherms can expand the capacity of ecological research on ectothermic animals. This study presents the design, development, and evaluation of a solar-powered and artificial-intelligence-assisted camera trap system with the ability to monitor both endothermic and ectothermic animals. The system is developed using a central processing unit, integrated graphics processing unit, camera, infrared light, flash drive, printed circuit board, solar panel, battery, microphone, GPS receiver, temperature/humidity sensor, light sensor, and other customized circuitry. It continuously monitors image frames using a motion detection algorithm and commences recording when a moving animal is detected during the day or night. Field trials demonstrate that this system successfully recorded a high number of animals. Lab testing using artificially generated motion demonstrated that the system successfully recorded within video frames at a high accuracy of 0.99, providing an optimized peak power consumption of 5.208 W. No water or dust entered the cases during field trials. A total of 27 cameras saved 85,870 video segments during field trials, of which 423 video segments successfully recorded ectothermic animals (reptiles, amphibians, and arthropods). This newly developed camera trap will benefit wildlife biologists, as it successfully monitors both endothermic and ectothermic animals.

关键词： animal behaviour computerized monitoring ectotherm endotherm environmental monitoring image capture image motion analysis smart cameras

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Indexing and Designing Deadbands for Industrial Alarm Signals

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2019年第10期66卷 8093-8103页

作者： Wang, Zhen Bai, Xingzhen Wang, Jiandong Yang, Zijiang Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao 266510 Shandong Peoples R China

Alarm systems play critically important roles for the safe and efficient operation of industrial plants, but they often suffer from too many nuisance alarms. Deadbands are widely used in industrial alarm systems to reduce the number of nuisance alarms. This paper formulates an index to determine whether deadbands are suitable for removing nuisance alarms of an analog signal, and proposes a method to design the deadband width. First, the deadband index is defined from two metrics, namely, normalized alarm durations and normalized alarm deviations. If the index is larger than 45 degrees, as indicated by a hypothesis test, then nuisance alarms are associated with large/small normalized alarm durations/deviations, so that deadbands are suitable. Second, a design method is proposed to find an optimal deadband width, so as to achieve the best weighted balance between the time duration of nuisance alarms and the delay in detecting abnormal conditions. The proposed method is applicable to nonindependent and identically distributed (IID) signals, whereas available design methods are confined to IID signals. Industrial examples are provided to validate the deadband index and the design method.

关键词： Alarm systems computerized monitoring fault detection industrial plants power generation safety management supervisory control and data acquisition (SCADA) systems supervisory control

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AirQ: A Smart IoT Platform for Air Quality monitoring

AirQ: A Smart IoT Platform for Air Quality Monitoring

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Vishal Choudhary Jun Hao Teh Victoria Beltran Hock Beng Lim Centre for Smart Systems Singapore University of Technology and Design

ISBN: (数字)9781728138930

ISBN: (纸本)9781728138947

Urban air pollution is a major problem in many cities globally. Prolonged exposure to particulate matter in the air is harmful to health. Government agencies and industries use expensive EPA-rated Air Quality monitoring Systems (AQMS) with specialized and expensive instruments. However, the air quality data provided by agencies is based on delayed averages and is region-based. The AirQ platform is a smart and cost-effective solution for air quality monitoring. The AirQ device is portable, low-cost and provides real-time and location-specific air quality data. It supports wireless data communication technologies including WiFi, 4G, Bluetooth, LoRa, etc. We have developed an ontology-based backend to support data management and the implementation of smart data analytics algorithms. The real-time air quality data and alerts are provided by the AirQ Dashboard and Smartphone App. The AirQ platform can be used to build large-scale and high-density air quality monitoring networks for Smart Cities, with devices deployed at many locations such as schools, childcare centers, hospitals, community centers, bus stops, parks, etc.

关键词： air pollution measurement computerised monitoring data analysis data communication environmental science computing Internet of Things mobile computing ontologies (artificial intelligence) radio networks smart cities smart phones Air pollution measurements air quality monitoring computerized monitoring Smartphone Internet of things Air quality data Radio networks data communication Smart cities Mobile Computing Data analysis Computing science

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Online Model-Based Thermal Prediction for Flexible Control of an Air-Cooled Hydrogenerator

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2019年第8期66卷 6311-6320页

作者： Oyvang, Thomas Noland, Jonas Kristiansen Hegglid, Gunne J. Lie, Bernt Univ South Eastern Norway Fac Technol Nat Sci & Maritime Sci N-3918 Porsgrunn Norway

The flexible generation of electrical energy is heavily dependent on hydropower. Advanced control systems may offer an enhanced operational security. During power system disturbances, a generator may need to operate beyond its limits to maintain a stable operation. This increased performance can be obtained if the total thermal capacity of the generator is exploited by applying optimal control theory in the automatic voltage regulator. A low-order model is required for online implementation and prediction of critical thermal stresses in the machine. Periodic extension of the generator capability diagram has been historically overlooked. In this paper, a thermal network for air-cooled hydrogenerators for use in real-time monitoring and optimal control is proposed and validated. The thermal model is extended with a heat exchanger model. The dynamic model is developed from an energy balance of the system and verified through finite-element method (FEM) simulations and temperature measurements in a case study. Transient simulation results of the online low-order model are in good agreement with measurements. Finally, a satisfactory simulator speed is obtained which confirms the feasibility of this approach in real-world applications.

关键词： Air-cooled hydrogenerator computerized monitoring energy balance fast simulator speed heat exchanger (HE) heat transfer thermal modeling voltage control

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