"Smart City": Electromagnetic Compatibility Problem

Introduction. The paper presents a description of the process of constructing a mathematical model for managing risks arising from the operation of complex technical unique systems for critical purposes under conditions of uncertainty of information about the parameters and phase state. The purpose of the study is to create an individual optimal strategy for managing risk events that occur during the operation of complex technical systems, which minimizes the cost of preventive work, as well as the amount of damage that may result from the occurrence of relevant events. The objectives of the study include the construction of a mathematical model for control risks arising from the operation of complex dynamic unique technical systems for critical purposes under conditions of interval uncertainty of information about the values of parameters and the phase state, since as well as an analysis of existing approaches to creating an individual forecast of changes in the state of the considered class of systems.
 Materials and Methods. The article gives a comparative description of the effectiveness of the application of the mathematical apparatus of the theory of outliers of random processes and the method of individual forecasting in solving the problem of managing risks arising from the operation of complex unique technical systems for critical purposes under conditions of uncertainty. Based on the statistical methods of interval data, a mathematical model of risk management was created, taking into account possible errors in measuring the values of the parameters of the considered class of complex systems at all control windows during the operation period.
 Results. The scientific novelty of the implemented approach lies in the use of interval data statistics, which allow the most correct consideration of possible errors associated with measuring the values of the characteristics of the studied technical systems at all stages of the control process.
 Discussion and Conclusions. The mathematical model of risk control developed in the course of the study, arising from the operation of complex technical systems for critical purposes, makes it possible to make the optimal choice of risk management strategy when using objects of this class. Along with the above, an algorithm has been developed for predicting changes in the state of a technical system during the entire period of its operation based on the mathematical apparatus of statistics of interval data, which makes it possible to take into account in the calculations the errors that occur when measuring the values of the main parameters of the system under consideration at all stages of the control process.

The article describes the power generating and other energy facilities as complex technical systems interacting with the material, financial, informational and legal environment. To ensure functioning and development of a technical system it is important to determine its place among other technical systems: technical systems and their elements must be classified. There have been presented the principles of formal theory of technical system classification. The classification objects have been given a definition. The concepts of classification, classification attribute and meaning of the classification attribute are formalized. The goal and tasks of the classification are formulated. The stages of forming and applying classifiers include developing the composition and structure of classifier kernel, marking interpretation elements and selecting an element corresponding to the user's request. The alphabet, inference rules, axioms and main theorems of the classification formal theory are presented. It is proved that a complete consistent independent classification theory is decidable. The taxonomy of the classifier types is considered: elementary (incomplete and complete), basic (discrete hierarchical, discrete matrix, continuous band), complex (combined and limiting). Examples of using classifiers of various types in the description of energy objects are given. The algorithms, labeling and selection problems are considered. The use of a grounded and structured classification theory allows better understanding and description of the relationship between technical and related systems and l increases the efficiency of functioning and development of technical systems.

The Aim of this paper is to develop the methods of analysis and simulation of the processes of occurrence and development of emergencies at complex railway infrastructure facilities. It cites analysis data on the threats, causes and consequences of sudden emergencies at complex railway infrastructure facilities. For the purpose of ensuring reliable operation of technical objects, as well as timely identification of faults, it is proposed to use the indicator-based approach that allows diagnosing and formally analyzing the processes of occurrence and propagation of malfunctions across the elements of complex technical systems. For the purpose of simulating the processes of propagation of the disturbances (hazards of emergencies) that occur as the result of malfunctions, it is proposed to use the theoretic graph approach that involves model and visual representation of the structure of a technical system under consideration in the form of a directed graph that shows the correlations between its elements. Each node and edge of a graph is assigned certain parameters or functionals that reflect the processes of correlated operation of the elements of the simulated system. The propagation of disturbances within a system is simulated with pulse processes initiated in one or several nodes. The paper refers to the developed formalized models of disturbance propagation in a technical system based on the construction of structural components and correlation matrices. The authors introduce the concept of critical element of a technical system that helps identify the event of its failure. Two basic criteria of technical system failure, i.e. the exclusive (a system is considered to have failed if the disturbance has reached any of the critical elements) and absolute criterion (failure occurs if the disturbance has reached the specified subset of critical elements) are defined. The paper provides an analytical example that illustrates the capabilities of the proposed model of disturbance propagation within the structure of a technical system. For the purpose more efficient diagnostics of the hazard of emergencies in railway infrastructure facilities the paper proposes a model of application of structurally integrated indicators that consists in the integration of indicators within the structure of a technical system that would immediately deliver the required and sufficient information in case of emergency. The main task would be to identify a set of indicators with the primary purpose of reducing the information-related stress and concentration of dispatchers’ or operators’ attention on the processes within a technical system that are most relevant in terms of accident-free and safe operation. Basic criteria are identified for the generation of the set of indicators within a complex technical system: maximum of reliability of the disturbance consequences estimate, maximum of accuracy of emergency causes identification, minimum of emergency identification time, minimum of nonrecurrent and current costs. A modified graph model of disturbance propagation in a complex technical system is provided that is the prerequisite for solving the multicriterion problems of optimal location of indicators within the structure of a technical system in terms of completeness, accuracy and timeliness of detection of failures of various types. Automation of the processes of generation of indicator sets using models of disturbance propagation in technical systems will allow using the proposed methods as part of further development of the URRAN methodology in terms of improvement of the decision support in railway infrastructure facilities management.

The paper considers the reliability – one of the characteristics of technical systems in manufacturing engineering. It is determined that the reliability weakness of technical systems causes the equipment breakdown. The authors enumerate the consequences of the equipment breakdown for the technical systems in the whole and note that various protection devices are provided to prevent serious consequences of the equipment breakdown. Technical system image has hierarchical structure changing over time. It is determined that the boundary condition of modeling of protection devices for technical systems is that the subsystems, the internal parameters of which are interrelated, are the functional protection system for technical systems. At the same time, the external links are strictly limited and defined. The authors considered the varieties of registered parameters and sub-varieties for technical systems and developed the mathematical model for quantitative assessment of protection devices. The model for all protection devices included in the considered object model is formed that makes possible to assess numerically the reliability of the technical system. The authors suggested the method of assessment of technical systems reliability on the base of analysis of possible breakdowns of the equipment and protection devices that allows preventing or minimizing the consequences of these breakdowns and developed the methodology, which on the base of protection devices model allows determining their necessary quantity and types at the system preset reliability in the whole. To describe formally the systems of protection devices, the set-theoretical concepts are used. The authors introduced the functional description of regulation, blocking and protection to characterize the technical systems protection devices and developed the model of the system (higher hierarchy level) for all protection devices included in the considered model of the object.

The article considers the importance of a technical system among other technical systems in order to ensure its functioning and development, to classify objects, subjects, processes of the technical and related systems. Previously, the author presented the basics of the formal classification theory. This article describes the basic classifiers and operations with them. Three types of basic classifications are identified: discrete hierarchical, discrete matrix and continuous band classifications. For them the concept, structure, dimension, basic operations (addition, multiplication, equality) are defined. In the hierarchy, the classification attributes can be sorted by subordination, when the classification attributes of the lower levels of the hierarchy detail the features of higher levels. The dimension of the hierarchical classification is the number of levels of classification features. Matrix classifications (including vector and super-matrix) are used when the classification attributes are equal and their values are discrete. Band classifications are similar in structure to matrix classifications, but the value of the classification attribute is the interval of numbers, for which the lower and upper boundaries are determined. The dimension of the matrix and band classifications is equal to the number of non-subordinate classification attributes. For all classifications, multiplication is equivalent to the introduction of new classification attributes, addition is the introduction of new values of already existing classification attributes. A unified approach to various types of classifications makes it possible to plan the structure of classifications of specific technical systems, taking into account the properties of characteristic parameters

Modern production is complex, integrated and is constantly being adapted to the market requirements by means of the reconfiguration of equipment structure and process alteration. The development of such production is performed based on evolutionary strategy by successively engaging (eliminating) stand-alone technological systems. Evolutionary developed technical systems and facilities presently make up a considerable share of technical systems. It is typical both for high-tech industries, namely: aviation, space exploration, military equipment, machine-building (Sujeet, 2005), and for applications based on large-scale interconnected production complexes (e.g. oiland gas-producing industry, oil and gas transportation, city economy engineering etc) (Gilard, 1999; Van Brussel et al., 1999; Jo, 1999; Ambartsumyan, Prangishvili, Poletykin, 2003; Ambartsumyan, Kazansky, 2008; Ambartsumyan, Potehin, 2003; Ambartsumyan, Branishtov, 2006). Evolutionary developed technical systems and facilities are featured by complex control system availability. The latter integrates into a single whole different, as to the purposes, automatic control loops (automatic control and regulation of physical process parameters, automatic shielding and blocking, logical configuration control) as well as the functions of supervisory control mainly aimed at coordination of different processes in a technical system. Supervisory control (SC) is intrinsically logical and is to provide the required operational sequence and exclude mutual blocking and deadlocks for stand-alone components (operating according to their internal rules time scale). SC is discrete and asynchronous by its nature and most commonly reveals itself as the change of flow as required by certain application (technical system functionality). It is important to consider two event aspects: first, everything happens as the result of a certain event; second, the change of states is regulated by events – there is no physical time though the system is dynamic. Though control systems are widely spread in the technical systems of such kind (Sujeet, 2005; Gilard, 1999; Van Brussel et al., 1999; Jo, 1999; Ambartsumyan, Prangishvili, Poletykin, 2003; Ambartsumyan, Kazansky, 2008; Ambartsumyan, Potehin, 2003; Ambartsumyan, Branishtov, 2006), presently there is no appropriate theoretical base to solve such supervisory control tasks as local control loops coordination, configuration of material flows structure and interaction with operations staff. Most spread concept of practical engineering of such systems is based on the model of interacting ′′black boxes′′: a ′′black box–control object′′ and symmetrically connected with it as to inputs and outputs a ′′black box–control system (device)′′. (Fig. 1). Source: Process Management, Book edited by: Maria Pomffyova, ISBN 978-953-307-085-8, pp. 338, April 2010, INTECH, Croatia, downloaded from SCIYO.COM

Networking information-centric system of systems is a network-centric, information-driven, system-supported complex giant system, which is the form of combat system under information warfare. The networking information-centric system involves multi-level and multi-type technical systems such as communication networks, combat applications and information services, and the technical systems are closely coupled with each other. In order to do a good job of designing the networking information-centric system, it is necessary to effectively verify each technical system, and through effective verification, iteratively optimize the design to enhance the capability of the networking information-centric system. This paper summarizes and analyzes the connotation of networking information-centric system and technical system, and describes the general framework of networking information-centric system technical system verification, including verification process, verification technology and optimization decision technology.

Smart Cities have become one of the most interesting research topics for governments, businesses and researchers in the last few years. Being a Smart City implies a competitive edge compared to other cities in terms of economic growth, sustainability, human resources and governance. Therefore, more and more governments pursue this future vision and hop onto the Smart City ‘Bandwagon’. However, the development of Smart City solutions is faced with challenges since there is no clear definition for Smart Cities yet. This paper provides a review on what challenges arise when designing Smart City solutions to provide a complete overview of identified challenges. This paper carries out a systematic literature review of publications between 2008 and 2016 which will be compared with a field study on Smart City initiatives conducted by the municipality of Enschede to develop a requirements framework for these projects. This research is relevant to governments and businesses aiming to create Smart Cities and for researchers, who aim to enhance the concept of Smart Cities. This paper found eight sub-domains within the topic of Smart Cities and these are: Technical Infrastructure, Application Domains, System Integration, Data Processing, Governance & Management, Society & Citizens, Business Domain and Environmental Sustainability. The eight sub-domains are respectively divided in two types: technological and non-technological domains. By firstly identifying the challenges and their solutions within these sub-domains, this paper proposes a requirements framework in combination with a checklist of questions to provide guidance for promoters to conduct future initiatives.

Big data and artificial intelligence based early risk warning system of fire hazard for smart cities

A smart city is a city that uses information and communication technologies (ICT), smart sensors, actuators and video cameras to better support and optimize the delivery of urban services and to address challenges within city communities. A smart city collects and analyzes data from smart IoT sensors (IoT devices/nodes) and video cameras. The data collected by the sensor nodes can be used to develop applications and systems that benefit the city and the community. Smart city industry is projected to be a $400 billion market by 2021, with 600 cities around the globe expected to generate 60% of the world's GDP by 2025, according to McKinsey research. Many cities have adopted at least one smart city project. However, the majority of cities around the globe are not yet smart cities. The key hurdle is securing the huge fund needed to start a smart city project, and ensuring that there are sufficient resources to sustain the project over time. Because implementing new smart city infrastructure is a large and complex financial undertaking that poses a financial hurdle, specifically, for most of the under-developed countries, a viable and cost-effective strategy is needed to tackle this problem and conquer the digital divide. Building upon and leveraging existing infrastructure is the key to address this problem. This minimizes the cost of technology upgrades and allows for an easier integration process. In addition, leveraging existing infrastructure can give cities a better and quicker return on investment. The main objective of this work is to devise an innovative research and development initiative, which builds upon and leverages ongoing global deployment of smart city and outdoor lighting infrastructures trend, to explore the potential and assess the feasibility of gradually transitioning existing Egypt’s cities infrastructure into truly IoT-enabled smart cities. Specifically, we propose and develop an innovative cost-effective, future-proof, scalable and modular end-to-end device-to-cloud connected outdoor Lighting network infrastructure solution that is based on P2P 4G LTE cellular technology to provide the direct connectivity between lighting poles (IoT devices) and the cloud. The proposed intelligent Lighting solution includes three key building blocks:1) light pole-mounted smart control nodes; 2) cloud-based smart city software solution (NetServ) to remotely monitor, manage, and control the entire lighting infrastructure; and 3) P2P 4G LTE cellular network. In the proposed architecture, smart streetlights serve as the framework for a high- bandwidth, low-latency wireless sensor network, capable of transporting large amounts of data in real-time, while concurrently supporting deployment of a wide range of smart city services.

The aim of this study is to structure the aspects of control and safety in technical systems using the concepts of entro-py, negentropy, and information, in order to identify additional factors for assessing controllability and loss of control in the process of decision-making or the loss of emergence. The article examines specific properties of ergatic systems that contribute to forming the informational basis for describing the structure, control, and safety levels of technical systems. A two-level ontological framework is proposed for evaluating the controllability of a technical system through the analysis of its informational characteristics. Negentropy is interpreted as an indicator of the system’s condition, reflecting the combined effect of internal properties and external influences on its functionality. The configuration and number of safety subsystems define the upper limits of controllability and safety within a technical system, including in scenarios involving emergence. The dualism of safety lies in capturing both the negentropy (describing the state of or-der in the system, as well as its actual — or worst-case — levels and structure of control and safety) and the infor-mation about the state of control and safety (expressed through the required number and configuration of safety sub-systems needed to achieve optimal performance). The article compares several concepts and regularities from infor-mation theory and thermodynamics for their applicability within the ontological framework of safety dualism. The analysis of safety dualism enables the comparison of structural and control architectures in technical system designs, the identification of factors contributing to successful or failed control, the definition of conditions under which emer-gence is lost, expert assessment of communication and control systems, and the development of optimal control and safety regimes—taking into account both resource depletion and the need for resource replenishment.

Biofilms are considered to be ubiquitous in industrial and drinking water distribution systems. Biofilms are a major source of contribution to biofouling in industrial water systems. The problem has wide ranging effects, causing damage to materials, production losses and affecting the quality of the product. The problem of biofouling is operationally defined as biofilm development that exceeds a given threshold of interference. It is for the plant operators to keep biofilm development below the threshold of interference for effective production and to work out values for threshold limits for each of the technical systems. Industrial biofilms are quite diverse and knowledge gained with a certain type of biofilm may not be applicable to others. In recognition of this, the old concept of a universal/effective biocide is a misnomer as physical, chemical and biological parameters of source water vary from site to site and so do the interactions of biocides with these parameters. Control methods have to be tailor-made for a given technical system and cannot be extrapolated. Because of the wide-ranging complexity in industrial technical systems, understanding the biofilm processes, detection, monitoring, control and management is imperative for efficient plant operation. A successful antifouling strategy involves prevention (disinfecting regularly, not allowing a biofilm to develop beyond a given threshold), killing of organisms and cleaning of surfaces. Killing of organisms does not essentially imply cleaning as most industrial systems deploy only biocides for killing, and the cleaning process is not achieved. Cleaning is essential as dead biomass on surfaces provide a suitable surface and nutrient source for subsequent attachment of organisms. A first step in a biofilm control programme is detection and assessment of various biofilm components, like thickness of slime layer, algal and bacterial species involved, extent of extracellular polymeric substances and inorganic components. Prior to adopting a biocidal dose and regime in an industrial system, laboratory testing of biocides using side-stream monitoring devices, under dynamic conditions, should be carried out to check their effectiveness. Online monitoring strategies should be adopted and biocidal dosing fine-tuned to keep biofilms under control. Literature on biofilm control strategies in technical systems is rich; however, the choice of the control method often depends on cost, time constraints and the cleanliness (threshold levels) required for a technical process. Currently, there is a trend to use strong oxidizing biocides like chlorine dioxide in cooling systems and ozone in water distribution systems as low levels of chlorine have been found to be ineffective against biofilms. A number of non-oxidizing biocides are available, which are effective but the long-term effects on the environment are still unclear. New techniques for biofilm control like ultrasound, electrical fields, hydrolysis of extracellular polymeric substances and methods altering biofilm adhesion and cohesion are still in their infancy at the laboratory level and are yet to be successfully demonstrated in large industrial systems.

The aim of the research is to analyze the emotional state of a person using stochastic methods and to study the dynamic characteristics of this state. The study uses statistical characteristics that are suitable for creating artificial intelligent systems, as well as for further development and design of organizational and technical systems. It is assumed that the emotional state of a person is determined by the amount of stress he experiences over a certain period of time. To account for the emotional responses of the cognitive system corresponding to the reactions of the human personality, the known results are used. In particular, to characterize the relative values of stress, the Holmes and Rahe scale was used, which contains 43 typical life situations with corresponding relative values of stress. It should be emphasized that all known results relate to time-independent stress models, and only the results of statistical processing of measurements of the impact of stress on the individual at certain time intervals are published.Materials and methods of research are the application of the Poisson model of stress occurrence in the process of system functioning. It is assumed that stresses are those impacts that are then processed, perceived, processed, and used by the individual and the organizational and technical system that models it. The occurrence of stresses over time is modeled by point Poisson processes, and the stress of each type according to Holmes and Rahe is described by a process with the corresponding individual function of the intensity of the occurrence of points (stresses). Dynamic responses of the system are described by well-known response functions in the theory of control systems. The key parameter of the response function is the time constant, which characterizes the typical response time of the system to individual stress.New results of the study are estimates of the average frequency of occurrence of various types of stress, which allowed us to determine the mentioned functions of the intensity of occurrence of stress in the Poisson model. This, in turn, made it possible to develop analytical relations for the relative amount of stress processed by the system for the current time. Thus, a model of the emotional state of the cognitive system (the development of the process of experiencing stress over time) is proposed in the form of a decreasing function of time with a certain time constant that characterizes the inertial properties of experiencing stress. Specific results and corresponding curves are obtained for the exponential response function of the system, which depends on the current time, times of stress occurrence, and relative stress values. In general, they correspond to the predictions of similar reactions for the individual obtained in published studies. In this regard, the model can be applied in the engineering design of organizational and technical systems that require accounting or modeling of emotional reactions.In conclusion, the directions of further development of the theory are indicated. In particular, the possibility of studying the reaction of the system to events, the occurrence of which is described by functions of the intensity of their occurrence, depending on time, which, of course, will bring the research results closer to real situations. Another important area may be the introduction of indicators and criteria for stress tolerance of systems to the consideration and study of behavior.

Design Rules, Volume 2: Chapter 6—The Value Structure of Technologies, Part 1: Mapping Functional Components

In this paper, we present the first generic framework for selecting comprehensive material/energetic sustainability performance indicators (SPIs) for technical systems: the S‐Cycle Performance Matrix (S‐CPMatrix). This novel matrix is comprised of 6 generic sustainability goals, 11 SPI archetypes, and 23 corresponding metrics identified from our previously developed model of technical system sustainability (the S‐Cycle), and is intended to support decision makers in meeting three identified criteria for comprehensive SPI sets: (C1) inclusion of indicators measuring performance at all relevant scales; (C2) inclusion of efficiency and effectiveness indicators; and (C3) coverage of all system sustainability goals. We evaluated the matrix by interpreting and classifying 324 indicators currently applied to assess technical system sustainability performance in the literature, with 94.1% found to be fully classifiable with respect to the proposed goals and SPI archetypes following several refinements. The matrix is applicable to different systems, and may be considered to facilitate the selection of a holistic set of SPIs from different sources and evaluation approaches. Thus, it addresses a need for consistent yet flexible guidance on how to comprehensively assess technical system sustainability performance, mirroring generic guidelines on organizational SPI selection widely available through several international initiatives. In addition to industrial evaluation of the S‐CPMatrix, four avenues for future research are proposed: (i) use of the matrix for systems comparison/benchmarking; (ii) further investigation of unsupported metrics; (iii) the nature and measurement of contaminants; and (iv) assessing the comprehensiveness of current SPI sets for technical systems.