The Use of Artificial Intelligence as a Tool Supporting Sustainable Development Local Policy

Maria Mrówczyńska, Małgorzata Sztubecka, Marta Skiba, Anna Bazan-Krzywoszańska and Przemysław Bejga
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Maria Mrówczyńska: Institute of Civil Engineering, Faculty of Civil Engineering, Architecture and Environmental Engineering, University of Zielona Góra, u1 Prof. Z. Szafrana 1, 65-516 Zielona Góra, Poland
Małgorzata Sztubecka: Faculty of Civil and Environmental Engineering and Architecture, UTP University of Science and Technology in Bydgoszcz, Al. Prof. S. Kaliskiego 7, 85-796 Bydgoszcz, Poland
Marta Skiba: Institute of Civil Engineering, Faculty of Civil Engineering, Architecture and Environmental Engineering, University of Zielona Góra, u1 Prof. Z. Szafrana 1, 65-516 Zielona Góra, Poland
Anna Bazan-Krzywoszańska: Institute of Civil Engineering, Faculty of Civil Engineering, Architecture and Environmental Engineering, University of Zielona Góra, u1 Prof. Z. Szafrana 1, 65-516 Zielona Góra, Poland
Przemysław Bejga: Department of Pharmakology and Toxicology, Faculty of Medicine and Health Sciences, University of Zielona Góra, ul. Zyty 28, 65-046 Zielona Góra, Poland

Sustainability, 2019, vol. 11, issue 15, 1-17

Abstract: This paper addresses the problem of noise in spa protection areas. Its aim is to determine the delimitation of the areas that exceed a permissible noise level around the sanatorium on the example of a health resort in Inowroc?aw. The determination of the exceedance of permissible noise levels allows us to develop directly effective local policy tools to be included in planning documents. In order to reduce noise infiltration, it is important to define environmental priorities. Taking into account their impact on the health of users in the protection area, environmental priorities enable us to introduce additional elements to street architecture. In order to properly manage space, in accordance with the idea of sustainable development, zones of environmental sensitivity—and their socio-environmental vulnerability—have been designated for assessing damage (exceeding permissible noise in health facilities) and defining methods of building resilience (proper management). This has provided the basis for a natural balance optimized for the people living in these areas. To achieve the goal above, non-linear support vector machine (SVM) networks were used. This technique allows us to classify the linearly inseparable data and to determine the optimal separation margin. The boundaries of the areas which exceeded permissible noise levels (separation margin) were estimated on the basis of noise pollution maps, created by means of the SVM technique. Thus, the study results in establishing buffer zones where it is possible to use varied land utilization in terms of form and function, as described in the planning documents. Such an activity would limit the spread of noise.

Keywords: noise; acoustic space; socio-environmental vulnerability; Support Vector Machines; spatial policy; preventive healthcare; healthcare facilities (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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