The technologies of a smart home and artificial intelligence (AI) are now inextricably linked. The perception and consideration of these technologies as a single system will make it possible to significantly simplify the approach to their study, design and implementation. The introduction of AI in managing the infrastructure of a smart home is a process of irreversible close future at the level with personal assistants and autopilots. It is extremely important to standardize, create and follow the typical models of information gathering and device management in a smart home, which should lead in the future to create a data analysis model and decision making through the software implementation of a specialized AI. AI techniques such as multi-agent systems, neural networks, fuzzy logic will form the basis for the functioning of a smart home in the future. The problems of diversity of data and models and the absence of centralized popular team decisions in this area significantly slow down further development. A big problem is a low percentage of open source data and code in the smart home and the AI when the research results are mostly unpublished and difficult to reproduce and implement independently. The proposed ways of finding solutions to models and standards can significantly accelerate the development of specialized AIs to manage a smart home and create an environment for the emergence of native innovative solutions based on analysis of data from sensors collected by monitoring systems of smart home. Particular attention should be paid to the search for resource savings and the profit from surpluses that will push for the development of these technologies and the transition from a level of prospect to technology exchange and the acquisition of benefits.
Abstract. The cleansing of the Ukrainian banking system, performed in 2014—2016, showed the purpose of the National Bank to break the old models of banking and ensure sustainable development of the banking system and Ukraine as a whole. At the same time, the cleansing of the banking system was revolutionary, affecting not only the owners but also the broad sectors of society and the business entities, who suffered losses. Due to high relevance and social impact, discussions about the root causes, methods, and consequences arose. This article aims to establish the compliance of cleansing the banking system of Ukraine with the goals of sustainable development. In this study, we considered the provisions of economic theory and the theory of banking systems, taking into account the spirit, ideals and principles of sustainable development. This study has the structure as follows. Firstly, we performed a theoretical analysis of the evolutionary and revolutionary types of banking reforms. Then we conducted a historical-economic analysis of the events that preceded the beginning of the cleansing of the banking system. In the central part, we analyzed the generalized causes and specific problems that led to the withdrawal of banks from the market in the primary wave of cleansing. Finally, we singled out three groups of NBU’s comments on the liquidation of specific banks. We established their close connection with the implementation of task 8.3 of the eighth Sustainable Development Goal. We pointed out some discrepancies between the reasons for the liquidation of individual banks and the comments of the NBU. Therefore, we have suggested combining comments into groups which more clearly reflect liquidation reason. Such groups include non-compliance with stakeholders, lack of bank recovery strategy and resources, and misbehaviour by shareholders, insiders, and related parties. Finally, we reaffirmed the revolutionary nature of the reform. We proved that, despite the losses, its absence, in the longrun, could have made it impossible to meet Task 8.3 of the Eighth Sustainable Development Goal. Promising are as of further research are comparing the procedure and results of cleansing the banking system in Ukraine and foreign countries. Keywords: banking system, cleansing, liquidation, banking reform, sustainable development. JEL Classification Q01, G21 Formulas: 0; fig.: 0, tabl.: 0, bibl.: 28.
The field of health improvement and life prolonging develops poorly, despite all the advances in medicine, chemistry and genetic engineering. Among the main problems is the difficulty of using new scientific achievements in other industries due to the rapid development of specialized knowledge, the problem of returning costs for the creation of really effective and the problem of aging population in developed countries. There are problems with data for this methods usage with privacy and security on different levels with regional peculiarities. Effective timing of work on health at the personal level can result as a result of increased time and productivity. But it's difficult for people to allocate their intellectual resources for that, so you have to connect artificial intelligence and machine learning. Big Data model with methods and analysis techniques on different levels for health improvement was suggested. The importance of the level of social networks and its regional aspects for the analysis of health improvement data was identified. Big data processing results implementation and levels of interaction with human with request for changes model was proposed. It consists from two levels of interaction with humans by level of quick reaction and discussion with smart personal assistance. Regional aspects from possible AI implementation in undeveloped countries were analyzed on example of personal level big data for health usage.
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