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Полковникова, Н. А., Е. В. Тузинкевич, and А. Н. Попов. "Application of convolutional neural networks for monitoring of marine objects." MORSKIE INTELLEKTUAL`NYE TEHNOLOGII), no. 4(50) (December 17, 2020): 53–61. http://dx.doi.org/10.37220/mit.2020.50.4.097.
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В статье рассмотрены технологии компьютерного зрения на основе глубоких свёрточных нейронных сетей. Применение нейронных сетей особенно эффективно для решения трудно формализуемых задач. Разработана архитектура свёрточной нейронной сети применительно к задаче распознавания и классификации морских объектов на изображениях. В ходе исследования выполнен ретроспективный анализ технологий компьютерного зрения и выявлен ряд проблем, связанных с применением нейронных сетей: «исчезающий» градиент, переобучение и вычислительная сложность. При разработке архитектуры нейросети предложено использовать функцию активации RELU, обучение некоторых случайно выбранных нейронов и нормализацию с целью упрощения архитектуры нейросети. Сравнение используемых в нейросети функций активации ReLU, LeakyReLU, Exponential ReLU и SOFTMAX выполнено в среде Matlab R2020a. На основе свёрточной нейронной сети разработана программа на языке программирования Visual C# в среде MS Visual Studio для распознавания морских объектов. Программапредназначена для автоматизированной идентификации морских объектов, производит детектирование (нахождение объектов на изображении) и распознавание объектов с высокой вероятностью обнаружения. The article considers computer vision technologies based on deep convolutional neural networks. Application of neural networks is particularly effective for solving difficult formalized problems. As a result convolutional neural network architecture to the problem of recognition and classification of marine objects on images is implemented. In the research process a retrospective analysis of computer vision technologies was performed and a number of problems associated with the use of neural networks were identified: vanishing gradient, overfitting and computational complexity. To solve these problems in neural network architecture development, it was proposed to use RELU activation function, training some randomly selected neurons and normalization for simplification of neural network architecture. Comparison of ReLU, LeakyReLU, Exponential ReLU, and SOFTMAX activation functions used in the neural network implemented in Matlab R2020a.The computer program based on convolutional neural network for marine objects recognition implemented in Visual C# programming language in MS Visual Studio integrated development environment. The program is designed for automated identification of marine objects, produces detection (i.e., presence of objects on image), and objects recognition with high probability of detection.
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Zhang, Fan, Shui Yuan Cheng, Ping Zhong, Rui Wu, Ming Juan Ma, and Wei Wei Gong. "Study of China’s Highway Environmental Monitoring Network Planning." Applied Mechanics and Materials 675-677 (October 2014): 318–24. http://dx.doi.org/10.4028/www.scientific.net/amm.675-677.318.
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Environmental monitoring of national highway is an important content of China’s environmental monitoring network in the transport field, a part of national environmental monitoring system, and also a significant basis for environmental protection supervision and management of the transport industry. Using the methods of spatial analysis, grid analysis, and optimization through ArcGIS, monitoring objects of Chinese national highway environmental monitoring network had been screened out. Among which, the environmental quality monitoring objects are composed of the national highway sensitive sections nearby or passing through 277 natural reserves, 32 national scenic areas, 7 of the world’s natural and cultural heritage sites, 8 important wetlands, 398 important reservoirs, and 193 state-level sensitive aquatic germ plasm resources conservation areas; and the pollutant emission monitoring objects include 316 long and extra-long tunnels, 539 service areas and 601 toll stations with large traffic volume. Environmental quality monitoring objects and pollutant emission monitoring objects form China’s National Highway Environmental Monitoring Network, which has filled the blank of highway environmental monitoring in the national environmental monitoring network. It will play a positive role in promoting the green development of China's transport industry.
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Bao, Ke, and Yourong Ding. "Multiobjects Association and Abnormal Behavior Detection for Massive Data Analysis in Multisensor Monitoring Network." Mathematical Problems in Engineering 2020 (November 3, 2020): 1–9. http://dx.doi.org/10.1155/2020/8858416.
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With the rapid increase in the number of large-scale distributed cameras and the rapid increase in the monitoring range of the camera network, how to accurately recognize and analyze abnormal behavior is still a challenging problem. In addition, the appearance of moving objects between different cameras without overlapping fields of view undergoes significant changes, making it difficult to obtain accurate association Therefore, multiobjects association and abnormal behavior detection for massive data analysis in multisensor monitoring network are proposed in this paper, which firstly uses belief propagation to associate multiple objects, extracts the object’s behavior trajectory characteristics, and then builds a long short-term memory classification network to realize automatic classification of abnormal behaviors. Multiobject association fully considers the timing correlation and object detection probability, as well as the statistical dependence of the measurement on the association matrix. The experimental results show that our proposed method can achieve a high classification accuracy and sensitivity, which meets the requirements of automatic classification of abnormal behavior in complex monitoring network. This further shows that this research has practical application value.
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Loktev, Daniil, and Olga Lokteva. "Image processing of transport objects using neural networks." E3S Web of Conferences 164 (2020): 03036. http://dx.doi.org/10.1051/e3sconf/202016403036.
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The paper is devoted to the development of an automated system model for monitoring and control of transport objects, based on the processing of images obtained using photo or video detectors, which can be installed on a fixed base near the transport highway for monitoring traffic flows and individual vehicles, and on rolling stock for monitoring transport infrastructure facilities. Image processing occurs by determining the function of blurring the image of an object, algorithms for extracting an image of an object using cascading classifiers and characteristic points, depending on the behavior of the object itself, as well as using a convolutional neural network. Machine learning of the convolutional neural network occurs when using the back propagation method of error. A neural network allows detecting objects of certain classes in the image, determining the parameters of their state and behavior. The proposed model with a movable hardware, which is responsible for obtaining the primary image, was tested on a section of the railway track to identify deviations of the state of the superstructure from the content standards, and a system with stationary photodetectors was tested to determine the parameters of moving vehicles. The obtained results of processing experimental data allowed drawing qualitative conclusions about the possibility of using the proposed algorithms and schemes for monitoring and control of various transport objects.
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Rodimtsev, Sergey, Alexander Psaryov, and Andrey Chuykin. "Monitoring of moving objects in the absence of a GSM signal." MATEC Web of Conferences 341 (2021): 00029. http://dx.doi.org/10.1051/matecconf/202134100029.
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Many modern transport processes require constant on-line monitoring and management. However, the main difficulty lies in the lack of a stable GSM connection. One of the possible solutions to this issue is the use of MESH networks. These represent the possibility of wireless communication between multiple entities, which are nodes on a distributed network. The article presents the results of the development of original local radio modules and a base station to ensure uninterrupted transmission of digital data from the monitoring object, in conditions of insufficient GSM coverage. The complex provides the following operating modes: simple interaction via a GSM channel, data transmission via a self-organizing network, as well as sensory interaction between objects. In the absence of GSM communication, the repeater provides on-line data transmission from the monitoring object, at a distance of up to 860 m, at a distance from the base station - at least 500 m. The use of the new complex makes it possible to promptly respond to changes in operating factors and prevent emergency situations during the operation of vehicles.
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Novokreschenova, Regina, and Olga Nikolaeva. "RELEVANCE OF ENVIRONMENTAL MONITORING OF MUNICIPAL WATER OBJECTS." Interexpo GEO-Siberia 4, no. 2 (2019): 112–17. http://dx.doi.org/10.33764/2618-981x-2019-4-2-112-117.
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The article substantiates the relevance of detailing the existing network of state monitoring of water objects by forming an additional observation network for water objects being in municipal ownership. A brief description of the existing observation network of surface water monitoring carried out by Roshydromet is given. The main documents regulating the order of surface water monitoring are listed. The insufficient coverage of water bodies in municipal ownership by the observation program was noted. The layout of surface water monitoring stations in the Novosibirsk Region, confirming this fact, is given. The main types of water bodies that are the municipal ownership are listed. The list of the water objects that are the municipal property of Novosibirsk is resulted. The fact of active economic and recreational use of these objects that contradicts the municipal legislation and safety requirements is noted. A list of the possible use of these facilities for the benefit of the municipality is stated. Conclusions about the need for the formulation of water bodies in municipal ownership, cadastral registration for their effecient use in the economy are drawn. The main types of work planned to solve this problem are listed.
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Nikoletseas, Sotiris, and Paul Spirakis. "Efficient sensor network design for continuous monitoring of moving objects." Theoretical Computer Science 402, no. 1 (July 2008): 56–66. http://dx.doi.org/10.1016/j.tcs.2008.03.005.
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Jasim Saud, Laith, and Zainab Kudair Abass. "A Comparison between Multi-Layer Perceptron and Radial Basis Function Networks in Detecting Humans Based on Object Shape." Ibn AL- Haitham Journal For Pure and Applied Science 31, no. 2 (September 12, 2018): 210. http://dx.doi.org/10.30526/31.2.1950.
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Human detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two types of neural networks are used to classify the extracted objects. Tests have been performed on a sequence of frames, and the simulation results by MATLAB showed that the RBF neural network gave a better performance compared with the MLP neural network where the RBF model gave a mean squared error (MSE) equals to 2.36811e-18 against MSE equals to 2.6937e-11 achieved by the MLP model. The more important thing observed is that the RBF approach required less time to classify the detected object as human compared to the MLP, where the RBF took approximately 86.2% lesser time to give the decision.
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Jagdale, Balaso, and Jagdish Bakal. "Privacy Aware Monitoring of Mobile Users in Sensor Networks Environment." International Journal of Interactive Mobile Technologies (iJIM) 13, no. 02 (February 22, 2019): 128. http://dx.doi.org/10.3991/ijim.v13i02.10023.
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<p><strong>Abstract—</strong>Due to complex monitoring systems in various business domains, secrecy and privacy has become critical issue for movable resources including human being. In a mobile object monitoring systems, balancing computing resources and quality of privacy is required. Objects can be mobile devices or users or any other moving entity. This work is presented in wireless sensor network environment. Earlier work does not consider presence of mobile objects in 3D space. We can observe that objects also carry Z axis in city area where high rise buildings are present. Earlier monitoring applications are mainly designed in two dimensional space to protect privacy. Our novelty is to suggest and design mechanism that reflect Z position (height) of mobile objects for protecting privacy. While calculating cloaking area and counting of objects, height is also considered as third dimension. This results in better location privacy as compared to the privacy delivered by the scheme that considers two dimensional space. We have presented performance, communications cost and privacy strength of modified 3D quality algorithm and 3D resource algorithm. Moreover, we present novel containment resolution algorithm that handles duplicate counting due to 3D presence of wireless system and mobile devices.</p>
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Ouldzira, Hicham, Ahmed Mouhsen, Hajar Lagraini, Mostafa Chhiba, Abdelmoumen Tabyaoui, and Said Amrane. "Remote monitoring of an object using a wireless sensor network based on NODEMCU ESP8266." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 3 (December 1, 2019): 1154. http://dx.doi.org/10.11591/ijeecs.v16.i3.pp1154-1162.
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<p>In recent years, wireless sensors networks (WSNs) have been imposed as an effective means of interconnection with simultaneous communication and information processing. They allow operating with sensors at low cost and low power consumption in various application areas such as ecosystem monitoring, detection and monitoring of objects and smart cities, etc.This paper describes the development of a system to detect the presence of an object and monitor it. This prototype is based on four NodeMcu modules (a static access point that provides the WIFI network, a server, a client and a mobile access point attached to the remote surveillance object) programmed under Arduino IDE and communicating between them via the HTTP protocol. The remote monitoring of the object for a linear disposition of the nodes used is based on the existence of the mobile access point in the HTTP client field.</p>
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Ren, Qiong, and Jun Tao. "The Research on Monitoring System Design and Implementation for the Network Security." Applied Mechanics and Materials 733 (February 2015): 821–24. http://dx.doi.org/10.4028/www.scientific.net/amm.733.821.
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Taking into account the safety of itself and high reliability and high availability features, we need to do to design more complete security monitoring system, which combines detection equipment, actuators and monitored objects together to form a whole, including the network directly to the monitored object inspection, monitoring and control process. This paper presents a systematic framework that through data collection, analysis, processing, rules, standards, violation, stop, and record all the process to achieve the protection and monitoring of local or remote computers all kinds of information, and then discuss the modules and systems different functions.
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Yang, Zebo, and Tatsuo Nakajima. "Connecting Smart Objects in IoT Architectures by Screen Remote Monitoring and Control." Computers 7, no. 4 (September 24, 2018): 47. http://dx.doi.org/10.3390/computers7040047.
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Electronic visual display enabled by touchscreen technologies evolves as one of the universal multimedia output methods and a popular input intermediate with touch–interaction. As a result, we can always gain access of an intelligent machine by obtaining control of its display contents. Since remote screen sharing systems are also increasingly prevalent, we propose a cross-platform middleware infrastructure which supports remote monitoring and control functionalities based on remote streaming for networked intelligent devices such as smart phone, computer and smart watch, etc. and home appliances such as smart refrigerator, smart air-conditioner and smart TV, etc. We aim to connect all these devices with display screens, so as to make possible remote monitoring and controlling a certain device by whichever one (usually the nearest one) of display screens among the network. The system is a distributed network consisting of multiple modular nodes of server and client, and is compatible to prevalent operating systems such as Windows, macOS, Unix-like/Linux and Android, etc.
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Toth, C., G. Jozkow, Z. Koppanyi, S. Young, and D. Grejner-Brzezinska. "MONITORING AIRCRAFT MOTION AT AIRPORTS BY LIDAR." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 2, 2016): 159–65. http://dx.doi.org/10.5194/isprsannals-iii-1-159-2016.
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Improving sensor performance, combined with better affordability, provides better object space observability, resulting in new applications. Remote sensing systems are primarily concerned with acquiring data of the static components of our environment, such as the topographic surface of the earth, transportation infrastructure, city models, etc. Observing the dynamic component of the object space is still rather rare in the geospatial application field; vehicle extraction and traffic flow monitoring are a few examples of using remote sensing to detect and model moving objects. Deploying a network of inexpensive LiDAR sensors along taxiways and runways can provide both geometrically and temporally rich geospatial data that aircraft body can be extracted from the point cloud, and then, based on consecutive point clouds motion parameters can be estimated. Acquiring accurate aircraft trajectory data is essential to improve aviation safety at airports. This paper reports about the initial experiences obtained by using a network of four Velodyne VLP- 16 sensors to acquire data along a runway segment.
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Toth, C., G. Jozkow, Z. Koppanyi, S. Young, and D. Grejner-Brzezinska. "MONITORING AIRCRAFT MOTION AT AIRPORTS BY LIDAR." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 2, 2016): 159–65. http://dx.doi.org/10.5194/isprs-annals-iii-1-159-2016.
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Improving sensor performance, combined with better affordability, provides better object space observability, resulting in new applications. Remote sensing systems are primarily concerned with acquiring data of the static components of our environment, such as the topographic surface of the earth, transportation infrastructure, city models, etc. Observing the dynamic component of the object space is still rather rare in the geospatial application field; vehicle extraction and traffic flow monitoring are a few examples of using remote sensing to detect and model moving objects. Deploying a network of inexpensive LiDAR sensors along taxiways and runways can provide both geometrically and temporally rich geospatial data that aircraft body can be extracted from the point cloud, and then, based on consecutive point clouds motion parameters can be estimated. Acquiring accurate aircraft trajectory data is essential to improve aviation safety at airports. This paper reports about the initial experiences obtained by using a network of four Velodyne VLP- 16 sensors to acquire data along a runway segment.
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Zeng, Xiao Hui, Man Hua Li, and Wen Lang Luo. "Research on a Remote Network Monitoring Model for Large-Scale Materials Manufacturing." Key Engineering Materials 474-476 (April 2011): 1999–2003. http://dx.doi.org/10.4028/www.scientific.net/kem.474-476.1999.
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A remote network monitoring model for large-scale materials manufacturing is proposed, including five modules: center control module, data collection and fault alarm module, graph drawing module and data storage module. The center control module not only interacts with users, but also controls the other four modules to work together in harmony. According to this monitoring model, a remote network monitoring platform is designed and realized. The user can interact with the control center module through an Internet browser, and the information about the monitored manufacturing machines and devices can be displayed by means of text, chart, graphic and sound, etc. Moreover, the details about the problems or faults from the monitored objects can be obtained in time. The experimental results indicate that the network monitoring platform can accurately get the information of the monitored objects, and users can conveniently get the online running state of those monitored objects.
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AKHMEDOV, Daulet, Meirbek MOLDABEKOV, Denis YERYOMIN, and Dinara ZHAXYGULOVA. "High Accuracy Positioning of Backbone Network Infrastructure and Mobile Objects." INCAS BULLETIN 11, no. 4 (December 8, 2019): 3–10. http://dx.doi.org/10.13111/2066-8201.2019.11.4.1.
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This article deals with the system of high accuracy positioning of backbone railway network infrastructure and mobile objects of the Republic of Kazakhstan. Using the developments of high accuracy satellite positioning systems and backbone geodetic networks for creating the system of high accuracy positioning in the railway field will allow determining coordinates of backbone network infrastructure and mobile objects and sites of defects revealed with high accuracy and, moreover, will possess the high degree of reliability of conducted measurements of railway infrastructure elements. High accuracy positioning can be provided by the implementation of reference GNSS stations along the backbone railways. The relevance of the study is that the project implementation will allow providing the high accuracy monitoring of defects and/or deviations of the rail track elements from design parameters, movement speed increase and railway transportation safety increase.
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Majcher, Andrzej. "Event Driven Networked Control System for Impact Load Monitoring." Solid State Phenomena 237 (August 2015): 169–74. http://dx.doi.org/10.4028/www.scientific.net/ssp.237.169.
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The article describes the application of the event-driven networked control system (NCS) for impact load monitoring. The main problem in this type of application is measurement synchronization, which should provide full information about the impact in terms of stochastic delays introduced by the network and stochastic characteristics of the actuator. Using the simulation model of the NCS system, the method of solving this particular problem was developed. The results of verification tests for the real object and a synchronized dynamic measurement of signals from resistance strain gauges are presented. The described system can find use in monitoring and fault detection, in tasks connected with dynamics of liquids and gases, acoustics, and the analysis of resistance properties of materials and technical objects. Key words: Networked control system (NCS), event maintenance, event synchronization, impact monitoring, measurement trigger, strain gauge.
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Grachev, V. V., A. V. Grishchenko, V. A. Kruchek, F. Yu Bazilevsky, M. A. Schwartz, and F. M. Schwartz. "Methodology for synthesis of neural network diagnostic models of complex technical objects." Automation on Transport 6, no. 4 (December 2020): 466–83. http://dx.doi.org/10.20295/2412-9186-2020-6-4-466-483.
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Despite the vast experience of using the neural networks for solving various machine learning problems, the numerous attempts to use them in technical diagnostics have not yet led to complete solutions so far (with rare exceptions). The reason is the specific nature of technical diagnostics that distinguishes such tasks from traditional machine learning problems. Having analyzed these specific features, the authors propose an approach to diagnosing complex technical objects that is focused on the use in built-in diagnostics systems and is based on the neural network reference diagnostic models of functionally isolated nodes and assemblies. The article describes the methodology for the synthesis of such models, their training on the data obtained by monitoring the object being tested using built-in diagnostic tools, determining the permissible response errors, and adapting to the current status of the object. The fuzzification of the diagnostic model results using the test sample proposed in the article makes it possible to standardize the approach to diagnosing complex technical objects designed for various purposes. The use of D. Trigg’s tracking control signal proposed by the authors to monitor regression residuals during the learning increases the training quality and generalization ability of models. The value of this signal determined by the model run on a test sample is an additional informative diagnostic parameter that increases the accuracy of classifying the status of the object under test. The proposed methodology applied at the complex technical object design stage allows optimizing the monitored parameters’ array and multiplying the efficiency of the diagnostic information recorded by the built-in diagnostic and monitoring tools.
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Bondarenko, M. A., A. V. Bondarenko, and M. Z. Benenson. "HARDWARE-SOFTWARE PLATFORM OF INDUSTRIAL MONITORING." Issues of radio electronics, no. 5 (June 8, 2019): 20–27. http://dx.doi.org/10.21778/2218-5453-2019-5-20-27.
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The paper describes basic requirements for a modern supervisory control and data acquisition system (SCADA), in particular for monitoring systems of complex industrial facilities. It is known that many robotic processes require non‑destructive testing with pattern recognition elements within a common monitoring system. On the widely used GENESIS64 SCADA example, it is considered a solution based on the hardware and software platform RT -XDC of RASTER TECHNOLOGY digital cameras, allowing to integrate into the system of this class any set of complex sensors such as digital cameras that support standard interfaces, built -in processing and data analysis. In addition, it is proposed the hierarchical model of complex objects monitoring and the universal way of its representation on the Moscow metro station network example, which includes four levels: the model map level, the model level, the model objects level and the level of their attributes. The considered data structure, which have to operate in solving the common monitoring task, make a choice in favor of object -oriented databases application like IPR, used in Delta Design CAD. The results were obtained during the development of experimental software that allows visualizing 3D models and displaying information about the selected object in the form of any predetermined structures.
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Zhang, Na, Xianghui Zhao, Tao Liu, Ming Lei, Cui Wang, and Yikun Wang. "Layout Planning of Highway Transportation Environment Monitoring Network: The Case of Xinjiang, China." Sustainability 12, no. 1 (December 30, 2019): 290. http://dx.doi.org/10.3390/su12010290.
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Environmental monitoring is an important tool for environmental protection supervision and management. Environmental monitoring can help us effectively understand and master the degree of environmental pollution, and provide data support for putting forward environmental protection measures. Scientific layout and reasonable level of environmental monitoring network design is an essential cornerstone for environmental monitoring, and a significant measure to promote the industry and green sustainable development. This paper systematically analyzed its requirements of monitoring stations in the highway traffic environment monitoring network. First of all, the paper analyzed the influencing factors of regional monitoring stations in the Xinjiang transportation environment monitoring network by referring to the idea of planning the distribution points of the national transportation environment monitoring network, and determines the weight of them by using the analytic hierarchy process (AHP), which lays a foundation for the subsequent selection and determination of environmental monitoring stations. Secondly, the advantage order of ecological monitoring objects’ importance degree was synthetically sorted by the fuzzy comprehensive evaluation method. Finally, the ranking results of the environmental monitoring objects were integrated to determine the number of traffic environmental monitoring stations that need to be built, and the layout of the highway traffic environment monitoring network in Xinjiang was proposed.
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Both, A., M. Duckham, P. Laube, T. Wark, and J. Yeoman. "Decentralized Monitoring of Moving Objects in a Transportation Network Augmented with Checkpoints." Computer Journal 56, no. 12 (September 5, 2012): 1432–49. http://dx.doi.org/10.1093/comjnl/bxs117.
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Xiong, Haitao, Jiaqing Wu, Qing Liu, and Yuanyuan Cai. "Research on abnormal object detection in specific region based on Mask R-CNN." International Journal of Advanced Robotic Systems 17, no. 3 (May 1, 2020): 172988142092528. http://dx.doi.org/10.1177/1729881420925287.
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As an information carrier with rich semantics, image plays an increasingly important role in real-time monitoring of logistics management. Abnormal objects are typically closely related to the specific region. Detecting abnormal objects in the specific region is conducive to improving the accuracy of detection and analysis, thereby improving the level of logistics management. Motivated by these observations, we design the method called abnormal object detection in a specific region based on Mask R-convolutional neural network: Abnormal Object Detection in Specific Region. In this method, the initial instance segmentation model is obtained by the traditional Mask R-convolutional neural network method, then the region overlap of the specific region is calculated and the overlapping ratio of each instance is determined, and these two parts of information are fused to predict the exceptional object. Finally, the abnormal object is restored and detected in the original image. Experimental results demonstrate that our proposed Abnormal Object Detection in Specific Region can effectively identify abnormal objects in a specific region and significantly outperforms the state-of-the-art methods.
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Barkova, N. Yu, D. D. Zherega, E. A. Popova, and V. P. Logacheva. "APPLICATION OF THE INTERNET OF THINGS IN PHARMACEUTICAL INDUSTRY SUPPLY CHAINS." Vestnik Universiteta, no. 9 (October 26, 2019): 68–74. http://dx.doi.org/10.26425/1816-4277-2019-9-68-74.
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Сurrent temperature monitoring, humidity, physical condition and real-time data transmission are extremely important in the pharmaceutical supply chains. The intelligent logistics system for monitoring the state of objects, implemented on the basis of the Internet of things, which can be used for the pharmaceutical industry, has been considered in this article. The two-level network architecture of the IOT platform has been reviewed. The first level is radio frequency object identification, and the second level is organization of wireless sensor network. By adapting the proposed system, the pharmaceutical company can easily monitor and control the quality of the goods during transportation.
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Babchuk, S. M. "CLASSIFICATION OF WIRELESS SPECIALIZED COMPUTER NETWORKS FOR THE OBJECTS LOCATION MONITORING." METHODS AND DEVICES OF QUALITY CONTROL, no. 1(42) (June 27, 2019): 70–76. http://dx.doi.org/10.31471/1993-9981-2019-1(42)-70-76.
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At present, it is possible to achieve the desired level of management of any enterprise only if there is complete and up-to-date source information about the current state of affairs in this enterprise. Growing size of an enterprise complicates the collection of necessary information and its processing. The speed and completeness of data collection is also influenced by many other factors associated with the specifics of specific enterprises. In particular, oil and gas companies have a large number of objects located at large distances from each other (including in remote and hard-toreach areas). In addition, these enterprises operate a variety of equipment and uses a large range of different matetechnical values. Quite often, for certain managerial needs, equipment and material and technical values can be moved within a single unit located in a large area or between units of one oil and gas undertaking. In connection with the aforementioned present, the enterprises of the oil and gas complex require the introduction of modern effective systems for collecting information on available material and technical values and their location at a certain point in time. In order to solve this problem, an analysis of modern wireless specialized digital networks was carried out and identified from them, which can be used at enterprises of the oil and gas complex for the monitoring of the location of the objects. Also, the basic characteristics of wireless specialized digital networks (which can be used for systems for monitoring the location of objects), by which they can be classified, are also established. A classification of wireless specialty digital networks (which can be used for objects monitoring systems) is created, which allows the specialists of control and measurement equipment and automation services to select the most appropriate wireless digital network for monitoring the location objects of oil and gas enterprises.
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Gnatyuk, Sergiy O., Vitaliy V. Kishchenko, Vitaliy V. Kotelianets, and Madina Bauyrzhan. "Network-Centric Monitoring for Cyber Incidents in Sectors of Critical State Infrastructure." Cybersecurity: Education, Science, Technique, no. 2 (2018): 80–89. http://dx.doi.org/10.28925/2663-4023.2018.2.8089.
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Information and communication technologies implementation in most areas of human life is aimed at improving the efficiency of business processes, but the emergence of new vulnerabilities and cyberthreats generates cybersecurity incidents. To localize and neutralize incidents effective management techniques are necessary. These processes are very actual for critical information infrastructure of the state, because destructive influences on objects of critical information infrastructure can cause big losses for the state (human life, material and status losses). Known methods for incidents management are not oriented on some special components and parameters of the cyberspace. It complicates implementation of these methods in real information and communication systems. From this viewpoint, in this paper the concept of network-centric incident management was developed. It allows to identify the most important (real) objects of critical information infrastructure protection and cybersecurity incidents to predict the categories that arise as a result of specific cyberattacks and their risk level. Further research study consists in instrumental tools based on mentioned concept. These tools can be useful for incidents prediction (character and level of losses) in information and communication systems of state critical infrastructure objects.
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Cho, Hyung-Ju, Seung-Kwon Choe, and Tae-Sun Chung. "A Distributed Approach to Continuous Monitoring of Constrained k-Nearest Neighbor Queries in Road Networks." Mobile Information Systems 8, no. 2 (2012): 107–26. http://dx.doi.org/10.1155/2012/303585.
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Given two positive parameters k and r, a constrained k-nearest neighbor (CkNN) query returns the k closest objects within a network distance r of the query location in road networks. In terms of the scalability of monitoring these CkNN queries, existing solutions based on central processing at a server suffer from a sudden and sharp rise in server load as well as messaging cost as the number of queries increases. In this paper, we propose a distributed and scalable scheme called DAEMON for the continuous monitoring of CkNN queries in road networks. Our query processing is distributed among clients (query objects) and server. Specifically, the server evaluates CkNN queries issued at intersections of road segments, retrieves the objects on the road segments between neighboring intersections, and sends responses to the query objects. Finally, each client makes its own query result using this server response. As a result, our distributed scheme achieves close-to-optimal communication costs and scales well to large numbers of monitoring queries. Exhaustive experimental results demonstrate that our scheme substantially outperforms its competitor in terms of query processing time and messaging cost.
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Lister, Tim A., S. Greenstreet, E. Gomez, E. Christensen, and S. Larson. "The LCOGT NEO Follow-up Network." Proceedings of the International Astronomical Union 10, S318 (August 2015): 321–23. http://dx.doi.org/10.1017/s1743921315006778.
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AbstractLas Cumbres Observatory Global Telescope Network (LCOGT) has deployed a homogeneous telescope network of nine 1-meter telescopes to four locations in the northern and southern hemispheres, with a planned network size of twelve 1-meter telescopes at 6 locations. This network is very versatile and is designed to respond rapidly to target of opportunity events and also to perform long term monitoring of slowly changing astronomical phenomena. The global coverage of the network and the apertures of telescope available make LCOGT ideal for follow-up and characterization of Solar System objects (e.g. asteroids, Kuiper Belt Objects, comets, Near-Earth Objects (NEOs)) and additionally for the discovery of new objects.We are using the LCOGT network to confirm newly detected NEO candidates produced by the major sky surveys such as Catalina Sky Survey (CSS) and PanSTARRS (PS1&2) and several hundred targets are now being followed per year. An increasing amount of time is being spent to obtain follow-up astrometry and photometry for radar-targeted objects and those on the Near-Earth Object Human Space Flight Accessible Targets Study (NHATS) or Asteroid Retrieval Mission (ARM) lists in order to improve the orbits, determine the light curves and rotation periods and improve the characterization. This will be extended to obtain more light curves of other NEOs which could be targets. Recent results have included the first period determinations for several of the Goldstone-targeted NEOs. We are in the process of building a NEO follow-up portal which will allow professionals, amateurs and Citizen Scientists to plan, schedule and analyze NEO imaging and spectroscopy observations and data using the LCOGT Network and to act as a co-ordination hub for the NEO follow-up efforts.
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Alkahtani, Hasan, Theyazn H. H. Aldhyani, and Mohammed Al-Yaari. "Adaptive Anomaly Detection Framework Model Objects in Cyberspace." Applied Bionics and Biomechanics 2020 (December 9, 2020): 1–14. http://dx.doi.org/10.1155/2020/6660489.
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Telecommunication has registered strong and rapid growth in the past decade. Accordingly, the monitoring of computers and networks is too complicated for network administrators. Hence, network security represents one of the biggest serious challenges that can be faced by network security communities. Taking into consideration the fact that e-banking, e-commerce, and business data will be shared on the computer network, these data may face a threat from intrusion. The purpose of this research is to propose a methodology that will lead to a high level and sustainable protection against cyberattacks. In particular, an adaptive anomaly detection framework model was developed using deep and machine learning algorithms to manage automatically-configured application-level firewalls. The standard network datasets were used to evaluate the proposed model which is designed for improving the cybersecurity system. The deep learning based on Long-Short Term Memory Recurrent Neural Network (LSTM-RNN) and machine learning algorithms namely Support Vector Machine (SVM), K-Nearest Neighbor (K-NN) algorithms were implemented to classify the Denial-of-Service attack (DoS) and Distributed Denial-of-Service (DDoS) attacks. The information gain method was applied to select the relevant features from the network dataset. These network features were significant to improve the classification algorithm. The system was used to classify DoS and DDoS attacks in four stand datasets namely KDD cup 199, NSL-KDD, ISCX, and ICI-ID2017. The empirical results indicate that the deep learning based on the LSTM-RNN algorithm has obtained the highest accuracy. The proposed system based on the LSTM-RNN algorithm produced the highest testing accuracy rate of 99.51% and 99.91% with respect to KDD Cup’99, NSL-KDD, ISCX, and ICI-Id2017 datasets, respectively. A comparative result analysis between the machine learning algorithms, namely SVM and KNN, and the deep learning algorithms based on the LSTM-RNN model is presented. Finally, it is concluded that the LSTM-RNN model is efficient and effective to improve the cybersecurity system for detecting anomaly-based cybersecurity.
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Максимовский, Александр Юрьевич, Григорий Александрович Остапенко, and Олег Николаевич Чопоров. "ABOUT PARAMETERS OF AUTOMATED MODELS FOR MONITORING INFORMATION SECURITY OF NETWORK OBJECTS, II." ИНФОРМАЦИЯ И БЕЗОПАСНОСТЬ, no. 3(-) (December 1, 2020): 327–36. http://dx.doi.org/10.36622/vstu.2020.23.3.001.
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В статье изучаются свойства сложных систем, представимых в виде сети автоматов, обладающих специальными свойствами. Данные свойства используются в интересах организации наблюдения за динамикой изменения (мониторинга) поведения состояния указанных систем в целях обеспечения надежного контроля функционирования. При этом в множество критериев контроля могут включаться результаты проверки соответствия троек входных последовательностей, последовательностей состояний и выходных последовательностей объектов контроля набору отношений, формируемых с использованием информации о свойствах рассматриваемых автоматных моделей сетевых объектов и, в частности, особенности функционирования указанных автоматных моделей. Предложены дальнейшие пути развития методов и средств выявления особенностей внешнего поведения автоматных моделей объектов контроля, способы построения и использования экспериментов с автоматами, а также отношений специального вида для автоматных моделей компонентов сложных систем и ассоциированных с ними комбинаторных объектов, определяемых на мультиграфах состояний соответствующих автоматов. Указаны общие подходы к применению автоматных моделей регистрового типа для мониторинга информационной безопасности сетевых объектов регистров сдвига или их обобщений, обладающие необходимыми свойствами. Получены новые результаты о возможностях и предложены новые подходы к выбору характеристик применения рассмотренных ранее автоматных моделей. Основное внимание уделено изучению групп автоматных моделей обобщенных недвоичных регистров сдвига и их обобщений, обладающих необходимыми свойствами. На основании этих результатов построены новые классы автоматных моделей параметров мониторинга информационной безопасности объектов сетевой инфраструктуры, которые включают не только основанные на контроле алгебраических и комбинаторных соотношений входных и выходных последовательностей указанных объектов, но и позволяют выявить потенциальные угрозы безопасности средствам контроля. The article studies the properties of complex systems that can be represented as a network of automata with special properties. These properties are used in the interests of organizing observation of the dynamics of changes (monitoring) the behavior of the state of these systems is in order to ensure reliable control over the functioning. In this case, the set of control criteria can include the results of checking the correspondence of triplets of input sequences, sequences of states and output sequences of control objects to a set of relations, generated using information about the properties of the considered automatic models of network objects and, in particular, the features of the functioning of these automatic models. Further ways of developing methods and means of identifying the features of the external behavior of automaton models of control objects, methods of constructing and using experiments with automata, as well as relations of a special kind for automata models of components of complex systems and associated combinatorial objects defined on the multigraphs of states of the corresponding automata. General approaches to the use of register-type automata models for monitoring information security of network objects of shift registers or their generalizations, which have the necessary properties, are indicated. New results on the possibilities are obtained and new approaches to the choice of characteristics of the application of the previously considered automatic models are proposed. The main attention is paid to the study of groups of automatic models of generalized non-binary shift registers of shift registers and their generalizations, which have the necessary properties. Based on these results, new classes of automata models of parameters for monitoring information security of network infrastructure objects were constructed, which include not only control-based algebraic and combinatorial relationships of the input and output sequences of the specified objects, but also allow identifying potential security threats to the controls themselves.
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Vinogradov, A. V., V. E. Bolshev, A. V. Vinogradova, A. A. Lansberg, M. O. Ward, and N. K. Miftakhova. "Method of accounting the dynamics of technological connections when forming a list of objects for the reconstruction and construction of electrical networks." E3S Web of Conferences 178 (2020): 01030. http://dx.doi.org/10.1051/e3sconf/202017801030.
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The paper gives a method of accounting the dynamics of technological connections when forming a list of objects for the reconstruction and construction of electrical networks. The specified method allows maintaining a database of technological connections taking into account the information received from the monitoring systems for electric network operating modes. It makes it possible to assess the dynamics of technological connections by settlements and regions. Based on this, it allows determining the availability of a power reserve for new technological connections and pre-compile a list of objects for reconstruction and construction of electrical network taking into account the dynamics of technological connections.
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Viatkin, R., and K. Viatkin. "THEORETICAL APPROACHES TO DETERMINING THE MONITORING OF LAND USE OF OBJECTS OF THE NATURE RESERVE FUND." Municipal economy of cities 4, no. 157 (September 25, 2020): 72–78. http://dx.doi.org/10.33042/2522-1809-2020-4-157-72-78.
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The purpose of the article is to study theoretical approaches to determining the monitoring of the use of ob-jects of the nature reserve Fund. The paper analyzes the existing theoretical approaches to determining the moni-toring of land objects of the nature reserve Fund, which showed their fragmentation and lack of common provi-sions. As a result of systematization of theoretical approaches to the justification of monitoring the use of land objects of the natural reserve Fund of the regions, the author proposed its definition, which is characterized by a set of legal, constructive, complex, organizational, functional and instrumental directions.At the present stage, there are a number of problematic aspects of determining the monitoring of objects of the nature reserve Fund, namely: - the need for a monitoring system should be linked to the regulatory framework for the use of nature re-serve facilities and with national institutions at different levels of management;- the need to strengthen the mech-anisms for financing the objects of the nature reserve Fund;- formation and improvement of existing systems for monitoring objects of the nature reserve FO-NDU;- the need to apply a comprehensive monitoring of objects of the nature reserve Fund by creating information support and methods for its assessment. The result of the proposed approach is the development of a system for monitoring land use of objects of the nature reserve Fund of Ukraine, which takes into account a set of information-analytical and spatial data on the state of objects of the nature reserve Fund using modern methods of data analysis and processing, visualization tools and automated systems for studying the state and dynamics of changes in the eco-network. It should be noted that the existing scientific developments in the system of monitoring the use of land objects of the natural reserve Fund of the regions do not take into account the instrumental aspects of its development and implementation. They are based on a comprehensive application of modern tools, in particular, geodesic, geoinformation systems, space survey results, and modern specialized software. Keywords: monitoring of land use, objects of the nature reserve Fund, systematization of theoretical ap-proaches, spatial data, information and analytical support, eco-network.
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Liu, B., S. Du, and X. Zhang. "LAND COVER CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK WITH REMOTE SENSING DATA AND DIGITAL SURFACE MODEL." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2020 (August 3, 2020): 39–43. http://dx.doi.org/10.5194/isprs-annals-v-3-2020-39-2020.
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Abstract. Land cover map is widely used in urban planning, environmental monitoring and monitoring of the changing world. This paper proposes a framework with convolutional neural network (CNN), object-based voting and conditional random field (CRF) for land cover classification. Both very-high-resolution (VHR) remote sensing images and digital surface model (DSM) are inputs of this CNN model. To solve the “salt and pepper” effect caused by pixel-based classification, an object-based voting classification is performed. And to capture accurate boundary of ground objects, a CRF optimization using spectral information, DSM and deep features extracted through CNN is applied. Area one of Vaihingen datasets is used for experiment. The experimental results show that method proposed in this paper achieve an overall accuracy of 95.57%, which demonstrate the effectiveness of proposed method.
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Ren, Sheng, Jianqi Li, Tianyi Tu, Yibo Peng, and Jian Jiang. "Towards Efficient Video Detection Object Super-Resolution with Deep Fusion Network for Public Safety." Security and Communication Networks 2021 (May 22, 2021): 1–14. http://dx.doi.org/10.1155/2021/9999398.
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Video surveillance plays an increasingly important role in public security and is a technical foundation for constructing safe and smart cities. The traditional video surveillance systems can only provide real-time monitoring or manually analyze cases by reviewing the surveillance video. So, it is difficult to use the data sampled from the surveillance video effectively. In this paper, we proposed an efficient video detection object super-resolution with a deep fusion network for public security. Firstly, we designed a super-resolution framework for video detection objects. By fusing object detection algorithms, video keyframe selection algorithms, and super-resolution reconstruction algorithms, we proposed a deep learning-based intelligent video detection object super-resolution (SR) method. Secondly, we designed a regression-based object detection algorithm and a key video frame selection algorithm. The object detection algorithm is used to assist police and security personnel to track suspicious objects in real time. The keyframe selection algorithm can select key information from a large amount of redundant information, which helps to improve the efficiency of video content analysis and reduce labor costs. Finally, we designed an asymmetric depth recursive back-projection network for super-resolution reconstruction. By combining the advantages of the pixel-based super-resolution algorithm and the feature space-based super-resolution algorithm, we improved the resolution and the visual perception clarity of the key objects. Extensive experimental evaluations show the efficiency and effectiveness of our method.
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Zhang, Huan, Ming Liu, and Ding Jun Hu. "Integrated Civil Monitoring System Based on POSA." Advanced Materials Research 919-921 (April 2014): 1599–602. http://dx.doi.org/10.4028/www.scientific.net/amr.919-921.1599.
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As the rapid development of network communication and multimedia technology,demand of integrated civil monitoring system is increasing. In this paper, an integrated civil monitoring system based on POSA(Pluggable Objects and Services Architecture) is presented. The proposed integrated civil monitoring system can be run on multiple hardware, platforms and operating systems to support distributed computing, to provide cross-network interaction. It also supports standard protocols and quickly access various device interface.What is more, our system can provide transparency applicable or service interaction in different hardware, platforms and operating system.
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Kashiyama, Takehiro, Hideaki Sobue, and Yoshihide Sekimoto. "Sky Monitoring System for Flying Object Detection Using 4K Resolution Camera." Sensors 20, no. 24 (December 10, 2020): 7071. http://dx.doi.org/10.3390/s20247071.
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The use of drones and other unmanned aerial vehicles has expanded rapidly in recent years. These devices are expected to enter practical use in various fields, such as taking measurements through aerial photography and transporting small and lightweight objects. Simultaneously, concerns over these devices being misused for terrorism or other criminal activities have increased. In response, several sensor systems have been developed to monitor drone flights. In particular, with the recent progress of deep neural network technology, the monitoring of systems using image processing has been proposed. This study developed a monitoring system for flying objects using a 4K camera and a state-of-the-art convolutional neural network model to achieve real-time processing. We installed a monitoring system in a high-rise building in an urban area during this study and evaluated the precision with which it could detect flying objects at different distances under different weather conditions. The results obtained provide important information for determining the accuracy of monitoring systems with image processing in practice.
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Payandeh, Shahram, and Jim Park. "Passive Observer of Activities for Aging in Place Using a Network of RGB-D Sensors." International Journal of Telemedicine and Applications 2020 (October 23, 2020): 1–15. http://dx.doi.org/10.1155/2020/8867926.
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Aging in place is a notion which supports the independent living of older adults at their own place of residence for as long as possible. To support this alternative living which can be in contrast to various other types of assisted living options, modes of monitoring technology need to be explored and studied in order to determine a balance between the preservation of privacy and adequacy of sensed information for better estimation and visualization of movements and activities. In this paper, we explore such monitoring paradigm on how a network of RGB-D sensors can be utilized for this purpose. This type of sensor offers both visual and depth sensing modalities from the scene where the information can be fused and coded for better protection of privacy. For this purpose, we introduce the novel notion of passive observer. This observer is only triggered by detecting the absence of movements of older adults in the scene. This is accomplished by classifying and localizing objects in the monitoring scene from both before and after the detection of movements. A deep learning tool is utilized for visual classification of known objects in the physical scene followed by virtual reality reconstructing of the scene where the shape and location of objects are recreated. Such reconstruction can be used as a visual summary in order to identify objects which were handled by an older adult in-between observation. The simplified virtual scene can be used, for example, by caregivers or monitoring personnel in order to assist in detecting any anomalies. This virtual visualization can offer a high level of privacy protection without having any direct visual access to the monitoring scene. In addition, using the scene graph representation, an automatic decision-making tool is proposed where spatial relationships between the objects can be used to estimate the expected activities. The results of this paper are demonstrated through two case studies.
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Dychko, Alina, and Igor Yeremeev. "Environmental monitoring of groundwater in urban ecosystems." USEFUL online journal 1, no. 2 (December 28, 2017): 01–10. http://dx.doi.org/10.32557/useful-1-2-2017-0001.
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Monitoring system, that ensures a steady control of water urboecosystem in area of man-caused factors influence, which allows evaluating measures to reduce the impact of hazardous sources on environment, which predicts possible consequences of intensive exploitation of ecosystem objects, is practically absent. Methods for determining structure of measuring network, arising from theory of fractals, are presented. The developed methodology for improving reliability of data for environmental monitoring is based on determining structure of measuring network, area limits and density of pollution on basis of measuring network data and appropriate interpolation and smoothing algorithms, and also determining dynamics of pollution area. Measurement network for monitoring of groundwater in urboecosystem should be formed as a matrix structure. The developed system of environmental monitoring allows carrying out constant monitoring of the environment, evaluating measures to reduce the technogenic impact and predicting its consequences.
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Solairaju, A., and S. Vivek Saravanan. "Security Service for Wireless Sensor Network." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 11, no. 6 (November 5, 2013): 2715–24. http://dx.doi.org/10.24297/ijct.v11i6.3047.
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Wireless Sensor Networks (WSNs) are gradually adopted in the industrial world due to their advantages over wired networks. In addition to saving cabling costs, WSNs widen the realm of environments feasible for monitoring. They thus add sensing and acting capabilities to objects in the physical world and allow for communication among these objects or with services in the future Internet. However, the acceptance of WSNs by theindustrial automation community is impeded by open issues, such as security guarantees. To examine both of these perspectives, we select and survey relevant WSN technologies dedicated to industrial automation. We determine to carry out a threat analysis, which act as basis of our evaluation of the current state-of-the-art. According to the results of this evaluation, we identify and discuss some research issues.
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Molotov, I., M. Zakhvatkin, L. Elenin, L. Canals Ros, F. Graziani, P. Teofilatto, T. Schildknecht, et al. "ISON NETWORK TRACKING OF SPACE DEBRIS: CURRENT STATUS AND ACHIEVEMENTS." Revista Mexicana de Astronomía y Astrofísica Serie de Conferencias 51 (April 13, 2019): 144–49. http://dx.doi.org/10.22201/ia.14052059p.2019.51.25.
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Interagency International Scientific Optical Network (ISON) represents one of largest systems specializing in observation of space objects. ISON provides permanent monitoring of the whole GEO region, regular surveying of Molniya type orbits, and tracking of objects at GEO, GTO, HEO and LEO. Currently ISON cooperates with 43 observation facilities of various affiliations with 100 telescopes in 17 countries. Six telescope subsets have been completed to the date, ISON encompasses five groups of telescopes and three scheduling centers. Obtained measurements are processed at the KIAM ballistic center to be used for scientific and applied goals, including collision risks analysis and space situation analysis. 20 millions measurements in 2.58 millions of tracklets for more 6740 objects have been collected by KIAM in 2016.
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Gura, Dmitry, Alina Pavlyukova, and Georgy Akopyan. "Security of infrastructural linear objects by using three-dimensional laser scanning technology." E3S Web of Conferences 157 (2020): 06007. http://dx.doi.org/10.1051/e3sconf/202015706007.
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For the functioning of any social infrastructure object, power supply is necessary. Therefore, such linear real estate objects as power lines are important elements in the urban engineering infrastructure. Linear objects are characterized by a considerable length, which makes it difficult to perform certain types of work, including monitoring. This paper discusses the structural elements of the overhead power lines (OHPL) and their inherent types of deformations. Current methods for monitoring and the instruments used are indicated. The disadvantages of the existing technology are described, which include bias data, a low degree of immediacy of its receipt, complexity, risk to the health of the performer. Alternative contact methods (using various sensors) and remote monitoring methods (video recording) with an indication of their shortcomings are analyzed. A scanning complex was performed, the results of which examined the possibility of using this technology as a strain monitoring using the example of supports and wires of overhead power lines. To do this, in laboratory conditions, measurements of the support tilting, the height of the suspension, the sag of the span, the size of the wire, and the length of the span were made for compliance with regulatory data. A conceptual basis for creating an urban digital monitoring platform for a network of power lines is proposed.
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Ren, Ping. "LabVIEW over BACnet, a New Approach for Electromechanical Equipment Remote Monitoring System." Applied Mechanics and Materials 44-47 (December 2010): 3807–11. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.3807.
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BACnet is a standard data communication protocol designed specifically for building automation and control systems. In BACnet network, each device is modeled as a collection of network-accessible, data structure called “objects”. LabVIEW is a graphical development environment for creating flexible data acquisition, device control and industrial automation applications at minimal cost. In this study, a remote monitoring system based on LabVIEW and BACnet was proposed, in which electromechanical equipment is described by a series of BACnet objects and LabVIEW provides a friendly unified human-computer interface for users. In order to evaluate the feasibility of this system, an experimental model was developed. Due to the characteristic of device-independent, not only can extend the scope of BACnet application, but also make different equipments monitored under the same platform becomes possible.
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Hoschke, Nigel, Don C. Price, D. Andrew Scott, and W. Lance Richards. "Structural Health Monitoring of Space Vehicle Thermal Protection Systems." Key Engineering Materials 558 (June 2013): 268–80. http://dx.doi.org/10.4028/www.scientific.net/kem.558.268.
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The thermal protection systems of spacecraft are vulnerable to damage from impacts by foreign objects moving at high velocities. This paper describes a proposed novel structural health monitoring system that will detect, locate and evaluate the damage resulting from such impacts. This system consists of a network of intelligent local agents, each of which controls a network of piezoelectric acoustic emission sensors to detect and locate an impact, and a network of optical fibre Bragg grating sensors to evaluate the effect of the impact damage by means of a thermographic technique. The paper concentrates on two issues that are critical to the successful implementation of the proposed SHM system: measurement of the elastic properties of the thermal protection material, knowledge of which is essential to the design and operation of the acoustic emission sensor network; and investigation of the practical feasibility of a switched network of optical fibre sensors.
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Marron, Pedro Jose, Daniel Minder, Andreas Lachenmann, Olga Saukh, and Kurt Rothermel. "Generic Model and Architecture for Cooperating Objects in Sensor Network Environments." African Journal of Information & Communication Technology 2, no. 1 (February 28, 2006): 1. http://dx.doi.org/10.5130/ajict.v2i1.9.
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The complexity and heterogeneity of cooperating object applications in ubiquitous environments or of applications in the sensor network domain require the use of generic models and architectures. These architectures should provide support for the following three key issues: flexible installation, management and reconfiguration of components in the system; optimization strategies whose implementation usually involves the proper management of cross-layer information; and proper adaptation techniques that allow for the self-configuration of nodes and components in the system with minimal human intervention. In this paper, we present one possible instance of such a generic model and architecture and show its applicability using Sustainable Bridges, a sensor network application that requires the analysis of complex sensor data to achieve its goal of effectively monitoring bridges for the detection of structural defects.
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Zhang, Yaqiang, Zhenhua Wang, Lin Meng, and Zhangbing Zhou. "Boundary Region Detection for Continuous Objects in Wireless Sensor Networks." Wireless Communications and Mobile Computing 2018 (2018): 1–13. http://dx.doi.org/10.1155/2018/5176569.
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Industrial Internet of Things has been widely used to facilitate disaster monitoring applications, such as liquid leakage and toxic gas detection. Since disasters are usually harmful to the environment, detecting accurate boundary regions for continuous objects in an energy-efficient and timely fashion is a long-standing research challenge. This article proposes a novel mechanism for continuous object boundary region detection in a fog computing environment, where sensing holes may exist in the deployed network region. Leveraging sensory data that have been gathered, interpolation algorithms have been applied to estimate sensory data at certain geographical locations, in order to estimate a more accurate boundary line. To examine whether estimated sensory data reflect that fact, mobile sensors are adopted to traverse these locations for gathering their sensory data, and the boundary region is calibrated accordingly. Experimental evaluation shows that this technique can generate a precise object boundary region with certain time constraints, and the network lifetime can be prolonged significantly.
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Wang, Ping, Yan Yan, Gui Yun Tian, Omar Bouzid, and Zhiguo Ding. "Investigation of Wireless Sensor Networks for Structural Health Monitoring." Journal of Sensors 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/156329.
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Wireless sensor networks (WSNs) are one of the most able technologies in the structural health monitoring (SHM) field. Through intelligent, self-organising means, the contents of this paper will test a variety of different objects and different working principles of sensor nodes connected into a network and integrated with data processing functions. In this paper the key issues of WSN applied in SHM are discussed, including the integration of different types of sensors with different operational modalities, sampling frequencies, issues of transmission bandwidth, real-time ability, and wireless transmitter frequency. Furthermore, the topology, data fusion, integration, energy saving, and self-powering nature of different systems will be investigated. In the FP7 project “Health Monitoring of Offshore Wind Farms,” the above issues are explored.
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Aulia, Reza. "Space Monitoring System Using the Background Subtraction Method with Whatsapp Notifications." Jurnal Jartel: Jurnal Jaringan Telekomunikasi 5, no. 2 (November 1, 2017): 15–20. http://dx.doi.org/10.33795/jartel.v5i2.199.
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This research was carried out by monitoring space using the background subtraction method with WhatsApp notifications, with features that make a system that can work and can help security and safety. The testing of this research is the effect of light intensity, the diversity of objects with different distances on motion detection and fire detection, WhatsApp notification delay testing and Quality of Service streaming networks on the website. From the results of the system testing carried out, the test results show that the light intensity used in the motion detection program must be more than 0 lux and objects that are too small are not defined as motion, fire detection can work at lux 8.33 and 25, delay in sending notifications is the same - equally good, when using a mobile network or FTTH, for delay in QOS (Quality of Service) testing it is in the very bad category, namely 0.99 Second, the resulting throughtput is 1048.53 Bytes / second on average and Packet loss is categorized as good in ITU -T with a value of 0%.
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Nikulins, Valerijs. "Modern seismological surveys in Latvia from 2008 to 2019 and prospects for their development." Российский сейсмологический журнал [Russian Journal of Seismology] 2, no. 1 (March 18, 2020): 27–39. http://dx.doi.org/10.35540/2686-7907.2020.1.03.
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In Latvia, seismological monitoring has been carried out at Slitere station since 2006. Slitere station is part of the GEOFON international network, with its center at GFZ Potsdam. The use of other stations of the GEOFON network and some stations of national networks of Finland and Estonia allows monitoring the entire East Baltic Region (VBR), including Estonia, Latvia, Lithuania, the Kaliningrad Region of Russia, and the adjacent part of the Baltic Sea (Lat=53.9°N - 59.7°N; Lon=19.4°E - 29.6°E). The impetus for the development of seismological monitoring was the Kaliningrad earthquakes of 2004 with Mw 5.0 and 5.2. The main object of research, in addition to tectonic earthquakes, is man-made seismicity, which prevails in Latvia and in EBR. Because of seismic monitoring for the period from 2008 to 2019, 8 tectonic earthquakes were localized, as well as more than 5640 man-made seismic events. The total number of seismic events localized by the BAVSEN network is 13328, including 1096 teleseismic events. The relevance of seismological monitoring is increasing due to unfavorable geodynamic conditions in the area where some large energy, transport facilities, and agglomerations are located, which requires a study of the seismic regime of the territories around these objects. The main problems of EBR seismic monitoring are associated with the identification of relatively weak seismic events, with a rare network of seismic stations, adverse seismic and geological conditions of the sedimentary cover, and low activity of EBR tectonic earthquakes. The lack of promising methods for recognizing the genesis of seismic events puts this problem in the first place. The prospects for seismological research in Latvia are related to the study of the seismic and geological properties of grounds, seismic micro zoning, monitoring of hydraulic structures, as well as the possibility of creating a National Data Center, within which seismological monitoring can become one of the main methods for radiation safety of EBR.
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Esina, Ekaterina N., and Vladislava V. Likhodeevskaya. "Development of methods for equalizing level networks." RUDN Journal of Engineering Researches 21, no. 1 (December 15, 2020): 58–65. http://dx.doi.org/10.22363/2312-8143-2020-21-1-58-65.
Full textAbstract:
The article is devoted to comparison of methods of calculating the approximate elevations of nodal points when adjusting leveling networks by strict and non-strict methods. Ensuring geomechanical monitoring of the mutual influence of constructed and operated objects is important in the intensive development of underground space of megacities, the construction of unique objects and structures. In the course of the research, mathematical models of level networks were developed and presented in the form of a closed loop and a set of open polygons. Analysis of modeling allows to determine the feasibility of applying the knot method by Professor V.V. Popov instead of the parametric method of adjustment. It is established that the quality of the results of strict equalization depends entirely on the quality of measurements, since deviations from the true values do not exceed the measurement error. The research has shown that it is possible to simplify the processing of monitoring data and evaluation of various configuration options for leveling networks, using algorithms for calculating approximate marks of nodal points. This makes it easier to process monitoring results and evaluate various network configuration options while ensuring the required level of measurement accuracy.
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Yim, Yongbin, Euisin Lee, and Seungmin Oh. "Large-Scale Object Monitoring in Internet-of-Things: Energy-Efficient Perspectives." Electronics 10, no. 4 (February 13, 2021): 461. http://dx.doi.org/10.3390/electronics10040461.
Full textAbstract:
Recently, the demand for monitoring a certain object covering large and dynamic scopes such as wildfires, glaciers, and radioactive contaminations, called large-scale fluid objects (LFOs), is coming to the fore due to disasters and catastrophes that lately happened. This article provides an analytic comparison of such LFOs and typical individual mobile objects (IMOs), namely animals, humans, vehicles, etc., to figure out inherent characteristics of LFOs. Since energy-efficient monitoring of IMOs has been intensively researched so far, but such inherent properties of LFOs hinder the direct adaptation of legacy technologies for IMOs, this article surveys technological evolution and advances of LFOs along with ones of IMOs. Based on the communication cost perspective correlated to energy efficiency, three technological phases, namely concentration, integration, and abbreviation, are defined in this article. By reviewing various methods and strategies employed by existing works with the three phases, this article concludes that LFO monitoring should achieve not only decoupling from node density and network structure but also trading off quantitative reduction against qualitative loss as architectural principles of energy-efficient communication to break through inherent properties of LFOs. Future research challenges related to this topic are also discussed.
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Chalasani Srinivas, Dr, Dr Srinivas Malladi, and . "A Light Protocol for Tracking Secure Stuff for the Internet of Things." International Journal of Engineering & Technology 7, no. 2.32 (May 31, 2018): 121. http://dx.doi.org/10.14419/ijet.v7i2.32.15384.
Full textAbstract:
The Internet of Things (IoT) is growing in the web of an age-old IPv6 address for Internet connections and messages that arise between these and other devices and systems that work with the Internet. It is equipped with the unique ID and data transfer capability through the network. Among other things, tracking and tracking online travel is a major issue. Although there are many tracking techniques for moving objects, many are at risk. So there is a need for tracking the safety of an object Safety protocols should provide visibility and tracking of street objects in support of the Internet (IoT). This protocol is based on the RFID Identity System for IoT Objects. Existing ones do not provide authentication of sites that lead to fakes. Great use of energy. The proposed protocol improves road safety tracking using the base protocol light and SPDL. The requested protocol is intended to ensure accuracy, accuracy, confidentiality and encryption. To ensure safe monitoring of objects, the requested protocols use cryptic primitives that use HMAC concepts that are used to authenticate an object. This protocol introduction relies on code authentication code (CMC), which is used to reduce power consumption at low cost. The testing of a test network evaluates protocol implementation and is found to be safer and requires less calculation than existing protocols.