Architecture of Compressor Equipment Monitoring and Control Cyber-Physical System Based on Influxdata Platform
Architecture of the compressor equipment monitoring and control cyber-physical system (CPS) based on the InfluxData IoT platform is proposed. CPS consists of three subsystems: a subsystem of a physical object, a digital twin and an interface. As a technical implementation of the IoT controller, a measuring and control module based on a data acquisition, data transfer and control device - VIDA350, connected to the Telegraf data collection agent of the platform using the MQTT protocol, is proposed. The basic methods of processing raw data from energy meters and sensors of technological parameters, implemented in blocks of on-line and off-line calculations are given. The organization of the digital twin of the compressor using the database of time series InfluxDB and the relational database MSSQL, storing information about changes in the technological parameters of equipment over time, energy efficiency indicators, statistics on accidents and operating time, equipment models, etc., is proposed. Grafana system and FreeCAD is used for visualization of equipment in 3D. The use of CPS can increase the efficiency of operation of compressors due to the timely detection of air leaks, minimizing idling, minimizing peak consumption, optimizing process parameters and settings both of the compressors and consumers.
This paper discusses data interchange formats in the context of heterogeneous networks for the Internet of Things (IoT). The wide dissemination of IoT technologies into various industries, such as agriculture and mining, reveals data transfer issues in geographically remote locations due to absence of any network infrastructure. Several technologies like LoraWAN and NB-IOT offer extended communication ranges, however they still cannot fully solve the problem. In many cases satellite networks are the only available option for transmitting IoT data to a central collection point. Our research of satellite networks showed that as of today the Iridium Short Burst Data (SBD) network is one of the best technologies suited for IoT applications. However, the SBD imposes a significant limit on the size of transmitted messages, which turns data format selection into a vitally important task. We developed a simulation model as well as a heterogeneous Iridium-LoRAWAN prototype to compare different data exchange formats. Our experiments showed more than 4 times increase in the amount of data transferred with Protocol Buffers, compared to the widely used JSON format.
This proceeding includes the papers of the following topics:
Bioinformatics, e-Health and Wellbeing Internet of Things and enabling technologies Smart Spaces, Linked Data and Semantic Web Big Data and Data Mining, Data Storage and Management Knowledge and Data Managements Systems Location Based Services: Navigation, Logistics, e-Tourism Context Awareness and Proactive Services Sensor Design, Ad-hoc and Sensor Networking Natural Language Processing, Speech Technologies Artificial Intelligence, Robotics and Automation Systems Open Source Mobile OS: Architectures and Applications Software Design, Innovative Applications Smart Systems and Embedded Networks Security and Privacy: Applications and Coding Theory Next Generation Networks, Emerging Wireless Technologies, 5G Computer Vision, Image and Video Processing Crowdsourcing and Collective Intelligence IoT based methods for Smart Water Distribution and Management in Agriculture Innovative Drone Enhanced Applications Semantic Audio and the Internet of Things Intelligence, Social Media and Web
The reports were present at the 24th Conference of Open Innovations Association FRUCT held on April 8-12, 2019 in Moscow, Russia.
Within the framework of the digital economy development in Russia, one of important areas is «digital logistics/ supply chain». In the market of freight and passenger traffic the use of digital technologies gives a competitive advantage, therefore their implementation is becoming inevitable for the entire logistics industry. This article considers trends, advantages, prospects and barriers to the implementation of digital technologies in the Russian Federation; the main types of these technologies and their influence on logistics business processes efficiency. A scheme for digital technologies (Big Data, IoT (Internet of Things), Blockchain, Cloud Services, 3D Printing) using in the supply chain are also presented. This paper provides the analysis of digital technologies use impact and a methodology for assessing the relationship with the components of the model of total logistics costs (TLC) in supply chains. It should be noted that proposed TLC model does not only include logistics operations costs, but also the costs associated with complete customer satisfaction.The use of digital technologies in logistics makes it possible to increase efficiency,precision and speed of logistics operations, however it requires significant financial investments, personnel training, accounting long-term physical movement over long distances, problems of customs clearance and terminal handling of goods.
The paper discusses opportunities and challenges in development of the current ecosystem of digital services. Special attention is paid to analysis of the role of Location Based Services (LBS) platforms for service ecosystems in the Internet of Things (IoT) era. We study architectures of LBS-enabled smart systems and analyze factors that could enable faster adoption of new service paradigms by the industry. The paper discusses potential roles of the IoT infrastructure for addressing this problem. One of the supporting questions is the role of mobile operational systems in development of a future ecosystem of the services, which we study by reviewing two approaches implemented in two open source mobile operational systems: Sailfish OS and Tizen OS. One of the starting observations was that the “cold start” problem is one of the top factors that block services from successful development. The problem refers to the case when a new service lacks relevant content. We propose to address this problem by providing developers with a toolkit for accessing relevant content available in various open databases. Development of a method for efficient data importing from open databases and content management is one of the practical results of this study. We implemented the proposed method as an extension to the open source LBS platform Geo2Tag. Now, it is available for free use and illustrates really good performance. Results of our study were tested on the most typical use cases of services for tourists and hospitality industry. The practical results of projects are available for use by business and helped us formulate priorities for further research.
The dg.o conference is the flagship conference of the Digital Government Society (DGS), and has positioned itself to be a top-ranking conference in this interdisciplinary academic field. It brings high quality research contributions and plays a major role in the advancement of knowledge in the field of digital government. The continue growing number of scholars and the growing number of members will continue to reinforce the position of DGS as a research and practice platform where researchers and practitioners can meet, exchange ideas, and build new relationships.
Subject: smart house maintenance requires taking into account a number of factors - resource conservation, mitigating working expenditures, safety enhancement, ensuring comfort of leisure and operation. Automation of such engineering systems networks as illumination, climate control, security and communication, may be achieved through utilization of contemporary technologies (e.g. IoT – Internet of Things). However, storing and processing the overwhelmingly massive corpora of data produced by the aforementioned systems poses a significant challenge. It is necessary to rationally manage the available big data during the stage of information modelling, due to the fact, that a building’s lifespan outlives most iterations of safety, comfort, and maintenance standards substantially.
Materials and methods: since smart houses may be classified as human-machine systems, the cybernetic approach will be considered as the base method of information system design and discovery. Instrumental methods are represented by set-theoretical modelling, automata theory and architectural principles of information management systems’ organization.
Results: an agile architecture of information system for smart house hardware management has been synthesized. The architecture encompasses several levels: client level, application level and data level; as well as three layers: presentation level, actuating devices layer and analytics layer. As proposed, the problem of growing volumes of information process by realtime message controller is attended by employment of sensors with configurable thresholds and actuating mechanisms, which implement control logic based on discrete automaton (namely, logical algorithm schemes). Multicircuit control system is suggested to be additionally enhanced with datamining module, DBMS, datamarts, and OLAP cube, which are jointly capable of processing large amount of data produced by hardware subsystems.
Conclusions: an information system for smart house hardware management, once built according to the proposed architecture, will enhance the quality of decision-making process, decrease operational costs of the smart house, due to the datamining-enabled control circuit. Suggested solution is recommended to be employed for the management of buildings and constructions, that utilize means of automation and IoT.
This book constitutes the joint refereed proceedings of the 20th International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and Systems, NEW2AN 2020, and the 13th Conference on Internet of Things and Smart Spaces, ruSMART 2020. The conference was held virtually due to the COVID-19 pandemic.
The 79 revised full papers presented were carefully reviewed and selected from 225 submissions. The papers of NEW2AN address various aspects of next-generation data networks, with special attention to advanced wireless networking and applications. In particular, they deal with novel and innovative approaches to performance and efficiency analysis of 5G and beyond systems, employed game-theoretical formulations, advanced queuing theory, and stochastic geometry, while also covering the Internet of Things, cyber security, optics, signal processing, as well as business aspects. ruSMART 2020, provides a forum for academic and industrial researchers to discuss new ideas and trends in the emerging areas.
The Internet undergoes a fundamental transformation as billions of connected “things” surround us and embed themselves into the fabric of our everyday lives. However, this is only the beginning of true convergence between the realm of humans and that of machines, which materializes with the advent of connected machines worn by humans, or wearables. The resulting shift from the Internet of Things to the Internet of Wearable Things (IoWT) brings along a truly personalized user experience by capitalizing on the rich contextual information, which wearables produce more than any other today's technology. The abundance of personally identifiable information handled by wearables creates an unprecedented risk of its unauthorized exposure by the IoWT devices, which fuels novel privacy challenges. In this paper, after reviewing the relevant contemporary background, we propose efficient means for the delegation of use applicable to a wide variety of constrained wearable devices, so that to guarantee privacy and integrity of their data. Our efficient solutions facilitate contexts when one would like to offer their personal device for temporary use (delegate it) to another person in a secure and reliable manner. In connection to the proposed protocol suite for the delegation of use, we also review the possible attack surfaces related to advanced wearables.