ABSTRACT
The Interoperability, continuous data and technology flow are core requirements of a proper smart city. Smart cities take on the characteristics of innovative, competitive and attractive megalopolises, which is strategically important for residents and investors. The aim of the article was to identify the current state and current issues of the Smart City concept implementation in Ukraine in the context of the experience of developed countries. The main methodological tools included the observation, statistical and comparative analysis. The study found that the effective development of digital transformation of territorial units in Ukraine requires focusing on certain factors during the implementation of the Smart City concept. Such factors conditionally include: technology-based infrastructure;environmental comments;constructive level of public transport;progressive city plans;opportunities for citizens to use appropriate resources. It was found reasonable to introduce infrastructural development of smart cities in Ukraine as a foundation of digital transformation of territorial units. Smart Cities were substantiated as an important tool for effective prevention and control of the pandemic without the introduction of restriction policies. A comparative analysis of the practice of Ukraine and developed countries in the implementation of infrastructural development of Smart Cities is a promising area of further research.
ABSTRACT
BACKGROUND AND OBJECTIVES: The new wave of the Covid-19 pandemic has complicated the working conditions of higher education institutions in Ukraine. In this regard, saving energy resources of the university offers an opportunity to get out of the crisis. The purpose of the study is to develop a management system for energy complexes with non-conventional renewable energy sources in the context of preventing a new outbreak of Covid-19 pandemic. METHODS: The method of Deutsche Gesellschaft fur Nachhaltiges Bauen was used to conduct energy audits, construct energy profiles of university offices. The cluster analysis was used to perform energy certification of university offices according to the indicators of integral energy efficiency potential and the level of annual specific energy consumption. Fuzzy methods made it possible to classify all the buildings into 3 categories (A, B, C) to prioritize their use in the light of Covid-19 pandemic. The system for monitoring the attained level of energy efficiency is based on the use of discriminant analysis. FINDINGS: Implementation of the weighted strategy has proved that the classes will be given online, 23% of all offices. Category A (administrative, technical, service buildings;laboratories with unique equipment with 24-hour service) will be used in a pessimistic scenario (continuation of Covid-19 pandemic). In the optimistic scenario (end of Covid-19 pandemic), by means of the suggested energy efficiency monitoring system, the probability of using category A offices makes 100%, B offices- 50% and C offices - 13%. CONCLUSION: Implementation of the developed energy efficiency action plan will offer the opportunity for the University to use reasonably the common connection point of knowledge management of energy complexes with non-conventional renewable energy sources in the context of preventing a new outbreak of the Covid-19 pandemic. The profitability of implementing a weighted energy efficiency strategy is 15%, with a payback period of 6.7 years for the purchase and installation of non-conventional renewable energy equipment. In the future, it would be advisable to convert gradually all of the remaining 14 university buildings to the autonomous use of non-conventional renewable energy sources, using a common connection point for the knowledge management of the energy complexes.
ABSTRACT
BACKGROUND AND OBJECTIVES: A new wave of Covid-19 pandemic has worsened the epidemiological situation in Ukraine. This caused the need to tighten quarantine measures that have been introduced since 31.08.2020. The conducted analysis showed that there are 3 groups of technologies for digital contact tracing: from maximum (25%) to minimum (20%). Objective of the study is to develop an exchange platform to track the spread of COVID-19 in rural areas. METHODS: Factor analysis identified key factors of COVID-19 virus spread. Cluster analysis identified clusters of COVID-19 spread. Taxonomy method established the limits of using contact tracing methods. Discriminatory method makes it possible to change the applied contact tracing method. FINDINGS: The results showed that the identified factors (medico-demographic special features of Covid-19 virus spread;rural infrastructure to counteract the infection) describe in total 83.24% of the data processed. Specified 4 clusters differ in the level of susceptibility of the population to COVID-19 and infrastructure development: from minimum (33% of the united territorial communities) to maximum - 13% of the united territorial communities. The value of the integral indicator calculated provides means for establishing the maximum (8.5) and the minimum (2) limit of changes in the method of digital contact tracing. CONCLUSION: The developed methodology was implemented on the basis of the united territorial communities of Sumy region. Monitoring of changes in the epidemiological situation made it possible to justify the need to change the contact tracing model, which will reduce the epidemiological level in the region as a whole by 30%. ©2021 GJESM. All rights reserved