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

Sustainability

Przemysław Bejga¹  Małgorzata Sztubecka²  Marta Skiba³  Anna Bazan-Krzywoszańska³  Maria Mrówczyńska³ 

[1] Department of Pharmakology and Toxicology, Faculty of Medicine and Health Sciences, University of Zielona Góra, ul. Zyty 28, 65-046 Zielona Góra, Poland;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;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;

关键词: noise;    acoustic space;    socio-environmental vulnerability;    Support Vector Machines;    spatial policy;    preventive healthcare;    healthcare facilities;   

DOI  :  10.3390/su11154199

来源: DOAJ

【 摘 要 】

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 Inowrocław. 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.

【 授权许可】

Unknown