Multi-Source Information Monitoring Test of Fractured Rock Mass Destruction Characteristics and Sensitivity Analysis of Precursor Phenomena

The accuracy of the monitoring information is particularly important for exploring fractured rock mass deformation and failure mechanisms and precursor characteristics. Appropriate monitoring methods can not only timely and effectively reflect the failure laws of fractured rock masses but also play an early warning role. To explore more reasonable monitoring methods, uniaxial compression experiments and real-time non-destructive monitoring on prefabricated fractured rock specimens through DIC, AE, and IRT were conducted; the strain field, temperature field, ringing frequency, standard deviation, etc. were analyzed; and correlation between the three methods in the information of audience was explored. The results show the following. (1) The failure evolution process of fractured rock mass can be divided into four stages. DIC can detect the initiation and propagation of cracks near the fractures of the specimen at the earliest stages. (2) The order of occurrence of precursor phenomena in multi-source monitoring information is different, which is vertical strain field > shear strain field > horizontal strain field > temperature field > ringing times. (3) The dispersion degree of standard deviation of each field is obviously different; the infrared temperature field is greater, but the strain field and temperature field show the same trend. (4) There are obvious precursors before the specimen is on the verge of instability; acoustic emission detected two consecutive increases in the cumulative number of ringing before destruction, which means the most obvious precursors. The research results can provide a theoretical basis for the precursory information capture and damage early warning of the fractured rock mass destruction process.

Features of modeling and construction of the information system of remote monitoring of the technical condition of vehicles

The article presents the features of construction and modeling of the system of operational remote monitoring of the technical condition of the truck in operation, and ensuring the interaction of monitoring data of the technical condition of the vehicle, trailer, mode of operation and rest of the driver and physical condition of the driver. The peculiarity of the vehicle monitoring information system equipped with the means of registration, mode of work and rest of the driver and physical condition of the driver is that it considers the features of remote inspection of the mode of work and rest of the driver and physical condition of the driver in the modern information and communication complex. means. The on-board intelligent diagnostic complex allows to measure in the conditions of operation a large number of parameters of the vehicle with the internal combustion engine and to carry out their registration on the remote computer with use of possibilities of the claimed method. As a result of forming a model of information system for monitoring the technical condition of the vehicle, it is possible to simultaneously monitor the parameters of the vehicle, provide remote inspection of driver's work and rest, physical condition of the driver, environmental performance of the vehicle, speeding. The process of formation and analysis of information structures of information-analytical system of operative control of technical condition of vehicle in operating conditions (Systems of Operative Control of a Technical Condition of the Vehicle in Operating Conditions) is considered. The effectiveness of the remote monitoring information system is enhanced by the possibility of prompt adjustment of the level of negative impact of motor vehicles on the environment and road infrastructure.

The development of models of an analytical data processing system for monitoring information security of an informatization object using cloud infrastructure

The article is devoted to the problem of developing an analytical data processing system for monitoring information security within the information security management system of modern companies conducting their main activities in cyberspace and using cloud infrastructure. Based on the analysis of modern information technologies related to ensuring information security of cloud infrastructure and the most popular products for ensuring information security of cloud infrastructures, as well as existing scientific approaches, a formalized approach to the synthesis of an analytical data processing system for monitoring the information security of an informatization object using cloud infrastructure is proposed. This approach takes into account the usefulness of the used information technologies from the viewpoint of information security. A general model of the structure of information support of an analytical data processing system for monitoring information security, as well as a model of the dependence of the usefulness of information technology on time and the ratio of the skill level of an information security specialist and an attacker are presented. The quality of the information security monitoring system is used as a criterion in the first optimization model. The following limitations are suggested: limitation on the time of making a decision on an incident; limitation on the degree of quality of analysis of information security events by the analytical data processing system and limitation on the compatibility of data analysis functions with data types about information security events. The cited results of the study of the second model show a logically consistent dependence of the usefulness of information technology on time and the ratio of the skill level of an information security specialist to the skill level of an attacker. The particular models of the structure of the information support of ASOD are presented. They make it possible to determine the rational structure information support of ASOD according to particular criteria. The following particular criteria are used: the maximin criterion of the usefulness of the information support of ASOD for monitoring the information security of an informatization object in the cloud infrastructure; the criterion for the maximum relevance of information support distributed over the nodes of the cloud infrastructure for systems with a low degree of centralization of management.

Seepage behavior assessment of earth-rock dams based on Bayesian network

Seepage behavior assessment is an important part of the safety operation assessment of earth-rock dams, because of insufficient intelligent analysis of monitoring information, abnormal phenomena or measured values are often ignored or improperly processed. To improve the intelligent performance of the monitoring system, this article has established an assessment framework covering project quality, maintenance status, monitoring data analysis, and on-site inspection based on the relevant norms of seepage safety assessment of earth-rock dams and the expert survey scoring method, and the Leaky Noisy-OR Gate extended model were used to determine the probability of events, and the dynamic and static Bayesian networks used to assess the possibility of seepage failure of earth-rock dams and diagnose the most likely cause of failure. The function of static and dynamic Bayesian networks to assess the seepage behavior of earth-rock dams, abnormal measured values, and causes of anomalies can make up for the limitations of reservoir management personnel and monitoring system in seepage failure experience and seepage knowledge of earth-rock dams and enable better handling of abnormal phenomena and monitoring information, making the monitoring system more intelligent.

Multilabel Acoustic Event Classification Using Real-World Urban Data and Physical Redundancy of Sensors

Many people living in urban environments nowadays are overexposed to noise, which results in adverse effects on their health. Thus, urban sound monitoring has emerged as a powerful tool that might enable public administrations to automatically identify and quantify noise pollution. Therefore, identifying multiple and simultaneous acoustic sources in these environments in a reliable and cost-effective way has emerged as a hot research topic. The purpose of this paper is to propose a two-stage classifier able to identify, in real time, a set of up to 21 urban acoustic events that may occur simultaneously (i.e., multilabel), taking advantage of physical redundancy in acoustic sensors from a wireless acoustic sensors network. The first stage of the proposed system consists of a multilabel deep neural network that makes a classification for each 4-s window. The second stage intelligently aggregates the classification results from the first stage of four neighboring nodes to determine the final classification result. Conducted experiments with real-world data and up to three different computing devices show that the system is able to provide classification results in less than 1 s and that it has good performance when classifying the most common events from the dataset. The results of this research may help civic organisations to obtain actionable noise monitoring information from automatic systems.

MiCADO-Edge: Towards an Application-level Orchestrator for the Cloud-to-Edge Computing Continuum

Automated deployment and run-time management of microservices-based applications in cloud computing environments is relatively well studied with several mature solutions. However, managing such applications and tasks in the cloud-to-edge continuum is far from trivial, with no robust, production-level solutions currently available. This paper presents our first attempt to extend an application-level cloud orchestration framework called MiCADO to utilise edge and fog worker nodes. The paper illustrates how MiCADO-Edge can automatically deploy complex sets of interconnected microservices in such multi-layered cloud-to-edge environments. Additionally, it shows how monitoring information can be collected from such services and how complex, user- defined run-time management policies can be enforced on application components running at any layer of the architecture. The implemented solution is demonstrated and evaluated using two realistic case studies from the areas of video processing and secure healthcare data analysis.

Evaluasi Kesuksesan Sistem Informasi Pelaporan dan Monitoring Kota Layak Anak dengan Model Design-Reality Gap

The Child-Friendly City web-based reporting and monitoring information system was implemented at the end of 2018 in Depok City. Through the web address, http://kla.depok.id Child-Friendly City cadres could report activities of child-friendly city forums based on five clusters and 29 indicators. The public could find information on Depok City as well as a child-friendly city. After three years of implementation, evaluation was necessary to ensure that the information system operates according to the initial design. This study aimed to evaluate the success of the monitoring and reporting information system for the Child-Friendly City of Depok. The evaluation was done by looking at the gap between the initial design of the system and the reality of the system's current state. The evaluation method was a gap analysis using a design-reality gap model consisting of 7 dimensions of Information, Technology, Process, Goals and Values, Staff placement and skills, management systems and structures, and other resources (ITPOSMO). The evaluation results showed that the information system failed partially. A recommendation for improvement was proposed so that Child-Friendly Cities' reporting and monitoring information system does not fail miserably. This recommendation aimed to make the reporting and monitoring process for the child-friendly city of Depok more effective.

Smart Traffic Light System

Wise city management, good road management is one of the most important things. Traffic congestion can be effectively controlled, provided that the number of vehicles passing through a traffic junction can be determined in advance. The proposed approach introduces a framework, which has the potential to continuously transmit traffic and generate alarms in the event of a major traffic congestion at the Sangli control station or in similar Indian cities. The number of vehicles passing through the area well before the required road junction can be estimated using the help of image processing techniques. In addition, monitoring information can be shared with a remote control centre near the city via the Internet. The tests performed show the effectiveness of this Internet-based technology (IoT) technology. Keywords: Traffic Volume Estimation, Genetic Algorithm, Wireless sensor network, Vehicle detection, Intelligent Traffic Signal Controller.