Інноваційні підходи до управління підприємствами морської індустрії на основі впровадження інформаційно-комунікаційних технологій

Subject/topic. The article discusses the possibilities and prospects of ensuring the dynamic stability of the economic development of industrial enterprises through the use of end-to-end technologies of the digital economy. The purpose and objectives of the study is to consider the potential and state of the use of digital technologies in the context of ensuring the dynamic sustainability of the development of industrial enterprises and to identify promising areas for improvement. Methodology. The study used: the general scientific dialectical method of knowledge, as well as some special research methods: comparative, survey method, statistical, generalization method and others. Results. An approach to understanding dynamic stability as a key characteristic of economic development has been substantiated. The importance of end-to-end digital technologies as a source of dynamism and sustainability of the development process of industrial enterprises is noted. Insufficient effectiveness of digitalization of Russian industrial enterprises is stated, factors that inhibit and stimulate industrial digitalization are highlighted. Some promising areas of digital assistance to ensure the economic development of Russian industrial enterprises are presented. Conclusions/Relevance. It has been confirmed that complex digital technologies of the so-called "end-to-end" nature can be fairly considered as the most modern toolkit for ensuring the dynamic sustainability of the development of economic entities in industry. Their use is truly synergistic in nature, since it pushes high-tech development of related industries, provides a deeper penetration of digitalization into the public sector, and also contributes to an integral increase in the global competitiveness of domestic industry, thereby making an invaluable contribution to achieving the desired parameters of national economic security. The promising directions of digitalization as a tool for ensuring the dynamic stability of the economic development of Russian industrial enterprises are given, such as the introduction of wireless communication technologies and the industrial Internet along the entire territorial chain of added value creation; activation of the use of robotics and sensorics components through the support of digital control and monitoring tools; orientation of the consumer product portfolio to the "Internet of Things"; further digitalization of general administrative and management processes (upstream-level of management of industrial enterprises) based on the introduction of tools and technologies for integrated digital planning and digital controlling.

The role of information and communication technologies (ICTs) in freight transport as key enabler is well recognised. However the uptake of recent ICT advances for multimodal freight transport provisions in the UK and Europe has been slow. The aim of our paper is to explore the potential reasons for such a slow adoption and assess how recent technological advances such as cloud computing and Internet of Things might have changed the landscape and thus help to overcome these barriers. Via an extensive review of 33 EU framework programme projects, we are able to consolidate and present current major efforts in ICT developments in the freight multimodal transport setting at European level. We further discuss barriers inhibiting quick take-up of ICT applications in multimodal transport. Resolutions were then explored by reviewing four key ICT development trends recently emerging and evaluating their potential impact in reducing such barriers for deployment. Our contribution is two-fold: it advances current knowledge by presenting an up-to-date overview of existing and emerging ICT applications in the field of multimodal transport and barriers to e-enabled multimodal transport. It also captures some of the best practices in industry and aims to provoke a debate among practitioners and academics via the analysis of how innovative use of recent technological developments could potentially lower the barriers to multimodal ICT adoption and lead to a more integrated freight transport network. Therefore it lays the foundation for further research.

OMICS: A Journal of Integrative BiologyVol. 24, No. 5 EditorialsCOVID-19 (Coronavirus Disease 2019): Opportunities and Challenges for Digital Health and the Internet of Medical Things in ChinaBiaoyang Lin and ShengJun WuBiaoyang LinAddress correspondence to: Biaoyang Lin, PhD, Department of Urology, University of Washington School of Medicine, Seattle, WA 98195, USA E-mail Address: biaoylin@gmail.comZhejiang-California International Nanosystems Institute (ZCNI) Proprium Research Center, Zhejiang University, Hangzhou, China.Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.Department of Urology, University of Washington School of Medicine, Seattle, Washington, USA.Search for more papers by this author and ShengJun WuDepartment of Clinical Laboratories, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China.Search for more papers by this authorPublished Online:7 May 2020https://doi.org/10.1089/omi.2020.0047AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"COVID-19 (Coronavirus Disease 2019): Opportunities and Challenges for Digital Health and the Internet of Medical Things in China." OMICS: A Journal of Integrative Biology, 24(5), pp. 231–232FiguresReferencesRelatedDetailsCited byEmerging technologies for COVID (ET-CoV) detection and diagnosis: Recent advancements, applications, challenges, and future perspectivesBiomedical Signal Processing and Control, Vol. 83Integration of cloud computing with the Internet of things for the treatment and management of the COVID-19 pandemic15 November 2022 | Information Systems and e-Business Management, Vol. 26A novel e-healthcare diagnosing system for COVID-19 via whale optimization algorithm24 September 2022 | Journal of Experimental & Theoretical Artificial Intelligence, Vol. 6Call for Papers: COVID-19 Systems Biology, Multi-Omics Integration, and Digital Technologies in Ecology, Health, and Society Vural Özdemir7 September 2022 | OMICS: A Journal of Integrative Biology, Vol. 26, No. 9From Personalized Medicine to Population Health: A Survey of mHealth Sensing TechniquesIEEE Internet of Things Journal, Vol. 9, No. 17The role of contemporary digital tools and technologies in COVID‐19 crisis: An exploratory analysis6 October 2021 | Expert Systems, Vol. 39, No. 6Coronavirus Disease (COVID-19): Challenges and Opportunities10 September 2020 | Disaster Medicine and Public Health Preparedness, Vol. 16, No. 2Anthropomorphic Robotic Eyes: Structural Design and Non-Verbal Communication Effectiveness15 April 2022 | Sensors, Vol. 22, No. 8Digital Transformation in Personalized Medicine with Artificial Intelligence and the Internet of Medical Things Biaoyang Lin and Shengjun Wu7 February 2022 | OMICS: A Journal of Integrative Biology, Vol. 26, No. 2A Review About the Main Technologies to Fight COVID-1915 April 2022Identifying and addressing digital health risks associated with emergency pandemic response: Problem identification, scoping review, and directions toward evidence-based evaluationInternational Journal of Medical Informatics, Vol. 157Unlocking the Public Perception of COVID-19 Vaccination Process on Social MediaToward Combatting COVID-19: A Risk Assessment SystemIEEE Internet of Things Journal, Vol. 8, No. 21An online COVID-19 self-assessment framework supported by IoMT technology6 August 2021 | Journal of Intelligent Systems, Vol. 30, No. 1A Security Management Framework for Big Data in Smart HealthcareBig Data Research, Vol. 25Connected Medical Kiosks to Counter COVID-19: Needs, Architecture & Design GuidelinesThe perspectives of biomarker-based electrochemical immunosensors, artificial intelligence and the Internet of Medical Things toward COVID-19 diagnosis and managementMaterials Today Chemistry, Vol. 20Internet of Things (IoT) Enabled Architecture for Social Distancing During Pandemic15 April 2021 | Frontiers in Communications and Networks, Vol. 2A Comprehensive Review of Applications of Internet of Things for Covid-19 PandemicIOP Conference Series: Materials Science and Engineering, Vol. 1055, No. 1Robotics and Drone-Based Solution for the Impact of COVID-19 Worldwide Using AI and IoT16 February 2021Digital Transformation and Emerging Technologies for COVID-19 Pandemic: Social, Global, and Industry Perspectives20 February 2021Telemedicine maybe an effective solution for management of chronic disease during the COVID-19 epidemic29 September 2021 | Primary Health Care Research & Development, Vol. 22Uma análise sobre o desenvolvimento de tecnologias digitais em saúde para o enfrentamento da COVID-19 no Brasil e no mundo1 January 2021 | Cadernos de Saúde Pública, Vol. 37, No. 3Enabled IoT Applications for Covid-191 May 2021Swarm Intelligence based Hierarchical Routing Protocols Study in WSNsCOVID-19 Digital Health Innovation Policy: A Portal to Alternative Futures in the Making Mustafa Bayram, Simon Springer, Colin K. Garvey, and Vural Özdemir3 August 2020 | OMICS: A Journal of Integrative Biology, Vol. 24, No. 8Digital Technologies-Enabled Smart Manufacturing and Industry 4.0 in the Post-COVID-19 Era: Lessons Learnt from a Pandemic3 July 2020 | International Journal of Environmental Research and Public Health, Vol. 17, No. 13Adoption of Digital Technologies in Health Care During the COVID-19 Pandemic: Systematic Review of Early Scientific Literature6 November 2020 | Journal of Medical Internet Research, Vol. 22, No. 11 Volume 24Issue 5May 2020 InformationCopyright 2020, Mary Ann Liebert, Inc., publishersTo cite this article:Biaoyang Lin and ShengJun Wu.COVID-19 (Coronavirus Disease 2019): Opportunities and Challenges for Digital Health and the Internet of Medical Things in China.OMICS: A Journal of Integrative Biology.May 2020.231-232.http://doi.org/10.1089/omi.2020.0047Published in Volume: 24 Issue 5: May 7, 2020Online Ahead of Print:April 20, 2020PDF download

The fusion of Internet of Intelligent Things (IoIT) in remote diagnosis of obstructive Sleep Apnea: A survey and a new model

The Internet of Things (IoT) has ushered in a new era of innovative agriculture research. Because IoT is still in its early stages, it must be widely tested before it can be widely deployed in many agricultural applications. In this paper, I look at different prospective IoT applications, as well as the unique concerns and constraints connected with IoT deployment for better farming. The gadgets and wireless communication technologies linked with IoT in agricultural and farming applications are thoroughly researched to focus on the unique requirements. Sensor-enabled IoT systems that deliver intelligent and smart services for smart agriculture are being investigated.
 Several case studies are offered to investigate the existing IoT-based solutions implemented by various organizations, individuals, and groups depending on their deployment criteria. The difficulties in these solutions are addressed, as are the factors for improvement and the future roadmap of work with IoT. Smart farming is a trend that emphasizes the use of information and communications technology (ICT) in machinery, equipment, and sensors in network-based hi-tech farm supervision cycles. Innovative technologies such as the Internet of Things (IoT) and cloud computing are expected to spur growth and kickstart the usage of robotics and artificial intelligence in agriculture. Such radical departures are upsetting established agricultural practices while also posing several obstacles. This study explores the techniques and equipment utilized in wireless sensor applications in IoT agriculture, as well as the predicted problems encountered when integrating technology with traditional farming practices. Furthermore, this technical knowledge is useful to growers during crop times ranging from planting to harvest, and applications in packing and transportation are being researched.

Usually, IoT devices are designed to perform specific tasks, while robots have to adapt to unpredictable situations. Artificial intelligence and machine learning help these robots cope with the emerging unexpected conditions. The Internet of Robotic Things is an evolving concept that brings together all-encompassing sensors and devices with robotic and autonomous systems. Both IoT devices and robots rely on sensors to understand the surrounding environment, to process data quickly, and to decide how to respond. Nevertheless, while most IoT systems can handle only well-defined tasks, robots can handle expected situations as well. The Internet of Robotic Things is a better Internet of Things (IoT) solution due to its ability to bridge the gap between IT and real operations. The IoRT may face several challenges in power consumption and network bandwidth limitation due to the growth in the information dissemination over the Robotic network. The main objective of this paper is to introduce an overview of the concepts and challenges in the Internet of Robotic Things based on Fog Computing technique. Further, a framework of Fog based IoRT is introduced.

The Internet of Things (IoT) gives a strong structure for connecting things to the internet to facilitate Machine to Machine (M2M) communication and data transmission through basic network protocols such as TCP/IP. IoT is growing at a fast pace, and billions of devices are now associated, with the amount expected to reach trillions in the coming years. Many fields, including the army, farming, manufacturing, healthcare, robotics, and biotechnology, are adopting IoT for advanced solutions as technology advances. This paper offers a detailed view of the current IoT paradigm, specifically proposed for robots, namely the Internet of Robotic Things (IoRT). IoRT is a collection of various developments such as Cloud Computing, Artificial Intelligence (AI), Machine Learning, and the (IoT). This paper also goes over architecture, which would be essential in the design of Multi-Role Robotic Systems for IoRT. Furthermore, includes systems underlying IoRT, as well as IoRT implementations. The paper provides the foundation for researchers to imagine the idea of IoRT and to look beyond the frame while designing and implementing IoRT-based robotic systems in real-world implementations.

Success of IoT in Smart Cities of India: An empirical analysis

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

Digital transformation is reshaping industries worldwide, including the maritime sector, by integrating advanced technologies to improve efficiency, safety, and sustainability. In the context of Indonesia, a country with a vast archipelago and significant maritime activities, digital transformation offers substantial opportunities but also presents distinct challenges. This paper explores the multifaceted impacts of digital transformation on Indonesia's maritime industry, examining both the opportunities and challenges that arise from this technological shift. Opportunities in the maritime sector include enhanced operational efficiency, improved safety, and better environmental management. Technologies such as the Internet of Things (IoT), big data analytics, artificial intelligence (AI), and blockchain are pivotal in optimizing logistics, predictive maintenance, and real-time monitoring of vessels and cargo. These advancements can lead to reduced operational costs, minimized human errors, and lower environmental footprints. For Indonesia, leveraging these technologies could significantly boost its competitiveness in global shipping, enhance port operations, and support the sustainable management of its extensive marine resources. However, the journey towards digital transformation in Indonesia’s maritime industry is fraught with challenges. Key issues include inadequate digital infrastructure, limited technological expertise, and regulatory hurdles. The uneven distribution of digital infrastructure across Indonesia's archipelago hampers the consistent application of advanced technologies. Additionally, the maritime workforce requires upskilling to handle new digital tools effectively, necessitating substantial investment in education and training. Regulatory frameworks also need to evolve to address data security, privacy concerns, and the integration of international standards, ensuring a seamless transition to digital operations.

Since the Internet of Things (IoT) will be entwined with everything we use in our daily life, the consequence of security flaws escalates. Smart objects will govern most of the home appliances and car engines yielding potential disaster scenarios. In this context, successful attacks could lead to chaos and scary scenarios (www.darkreading.com). Unprotected personal information may expose sensitive and embarrassing data to the public and attacks may threaten not only our computers and smart devices, but our intimacy and perhaps our lives too. Because persons and objects will be bonded with each other, user consent becomes critical. Therefore, thing, object, and user Identity will be the focus of future IoT security solutions, yielding a Trust, Security, and Privacy (TSP) paradigm, which may constitute the Achilles' heel of IoT. While security issues are quite straightforward, mainly from background knowledge, privacy issues are far more complex. Privacy constitutes a rather challenging task, even for the m...

In current years, Internet of Things (IoT) has come a long way and is well emerged within many organizations and fields covering the sector of healthcare. Continuously, encompassing of the Internet of Medical Things (IoMT) in the field of the medical sector helps in the rise of medical data and analysis of that. Smart healthcare plays important role in human life and various research projects are running on it. It consists of diverse ingredients like wireless communication technology, cloud computing, edge computing, medical sensors, artificial intelligence (AI), IoMT, and IoT. The chapter introduces IoMT with respect to the multiple challenges like privacy, security and low-power operation faced while incorporating IoT with healthcare sector. For emergency treatment, a cloud-based healthcare framework provides a platform to support patients over internet communication by medical experts. Privacy and security to the medical records are on higher priority due to the very sensitive nature of the content. Moreover, a comprehensive survey on IoMT-based cloud and edge-intelligent healthcare system is also described. The current advancement in the field of IoT, IoMT, cloud computing, and AI related to privacy and security, some pathways for forthcoming work in collaboration of healthcare sector and IoT based on a collection of challenges and open issues are also addressed.

Relevance. The growing integration of Internet of Things (IoT) technologies into all areas of human life – from intelligent households to smart city infrastructure – is accompanied by an exponential increase in the volume of data being collected, transmitted, and processed in real time. When combined with artificial intelligence technologies, this data becomes the foundation for making autonomous decisions, predicting user behavior, and adapting environments to the needs of specific individuals. However, it is precisely in this context that the critically important issue of personal data protection arises. Many IoT devices operate in uncontrolled environments, have limited resources for cryptographic protection, and are vulnerable to cyberattacks and unauthorized data collection. Meanwhile, artificial intelligence algorithms used to analyze this data often exhibit the “black box” problem, where it is impossible to fully explain how and why a particular decision was made based on personalized data. The lack of transparency, combined with broad access to sensitive information, threatens fundamental human rights to privacy. The relevance of this topic is driven by the need to find balanced technical solutions that enable both effective analysis of large-scale data in IoT environments and a high level of data security. In this regard, the study of modern methods for processing, analyzing, and protecting data in IoT systems, adapted to the requirements of ethical artificial intelligence and digital privacy standards, represents one of the key challenges of contemporary digital science. The object of research: the processes of data collection, processing, analysis, and protection in IoT systems, particularly those components related to the use of users' personal information and its processing through artificial intelligence methods. Purpose of the article: research of modern methods for data processing and analysis in IoT systems. The objective of the work is to identify the most effective approaches to secure data handling, characterize existing privacy threats, and assess the potential for integrating protected analytical algorithms that meet both the technical and ethical requirements of the digital environment. Research results. A comprehensive analysis of modern approaches to data collection, processing, analysis, and protection in IoT systems has been conducted, particularly in the context of the growing role of artificial intelligence. The technological foundations of IoT functionality were examined, key architectural components identified, and their role in creating digital ecosystems for monitoring, management, and decision-making across various sectors – from household systems to critical infrastructure – was investigated. Special attention was paid to data preprocessing methods, which help reduce information load, improve the quality of analysis, and adapt data flows to the requirements of intelligent algorithms. It was demonstrated that the use of edge processing and local-level aggregation enhances both system performance and security. The main types of databases for IoT – especially those optimized for time series – were analyzed, along with tools for handling large volumes of data in cloud and hybrid environments. Conclusions. Data collection methods in IoT are multilayered and closely linked to the requirements for energy efficiency, security, latency, and system scalability. The quality and reliability of the collected information form the foundation for subsequent processing, analysis, and decision-making; therefore, the selection of sensors, communication protocols, and architectural models is of strategic importance for any IoT system. Preprocessing and efficient data storage in IoT are critical stages that ensure the quality, security, and usability of information for further analysis. They determine not only the accuracy of analytics but also the stability, scalability, and compliance with regulatory standards. This creates a demand for the development of adaptive, intelligent data processing and storage systems capable of dynamically responding to changes in device operation context and user requirements. The successful implementation of secure IoT solutions requires an integrated approach that combines technical expertise, legal knowledge, and ethical responsibility.

Methods. The generalization and analysis made it possible to prove that the most important condition for the economic development of the country in modern turbulent conditions is to ensure the stability of the development of industrial enterprises in the real sector of the economy. In the course of the globalization of the economy, accompanied by the active development of the economic space, the acceleration of the exchange of information, technology, knowledge and experience, contribute to the transformation of industrial enterprises and increase their dynamism, which puts forward new requirements for doing business. The issues of the constancy of functioning and development of industrial enterprises are becoming increasingly important due to the increasing impact on business entities of negative trends caused by exogenous and endogenous factors (financial crises, pandemics, military events, etc.). Accordingly, qualitative changes are needed in the management mechanisms at the level of industrial enterprises to ensure their sustainable functioning and development. In unstable economic conditions, the management of industrial enterprises must be based on the principles of adaptation to ensure economically sustainable functioning and development in the long term. However, at present, one can state the low quality of management, which negatively affects the efficiency of industrial enterprises. Consequently, the modern market economy requires absolutely innovative approaches to management, which are based on the principles of selffinancing, self-sufficiency, self-government. Results. The author in the article analyzed the dynamics of the volume of sales (goods, services) of enterprises in 2010–2021 (according to the institutional and functional approach). The results of the analysis indicate that the volume of sold products (goods, services) of the industry in the total number of products sold for 2010–2021. 68% to 33.78%. Therefore, we can state the fact that the general industry provides from 30 to 40% of the total volume of sales, which confirms the priority of this industry in the development of the country's economy. The article analyzes the problems of industrial enterprises, identifies the components and their indicators necessary for a permanent assessment of the resource potential as the basis for the formation of a management system for the innovative development of industrial enterprises. Novelty. An algorithm is proposed for assessing the components of the resource potential of industrial enterprises in order to develop a management solution for the formation of a foresightinnovative enterprise management mechanism, which consists in successfully overcoming problems at domestic industrial enterprises, needs an integrated approach, including business support, technology modernization, stable energy supply, social responsibility and favorable conditions in the investment and regulatory environment. Only in such conditions it is possible to create certain positive conditions for the development of industry and ensure the sustainable growth of the country's economy. Practical value. It was determined that the solution of problems at domestic industrial enterprises of Ukraine requires comprehensive measures, including support from the state, involvement of the private sector, modernization of technologies and management, innovation, education and international cooperation. Only in such conditions it is possible to create favorable conditions for the stable development of domestic industrial enterprises.

BlockIoTIntelligence: A Blockchain-enabled Intelligent IoT Architecture with Artificial Intelligence