Modelling population density using artificial neural networks from open data

• Autorzy: Nadolny Adam

Warianty tytułu

PL

Modelowanie gęstości ludności z wykorzystaniem sztucznych sieci neuronowych na podstawie otwartych danych

• Języki publikacji: EN

Abstrakty

EN

This paper introduces the concept of creating a model for population density prediction and presents the work done so far. The unit of reference in the study is more the population density of a location rather than tracking human movements and habits. Heterogeneous open data, which can be obtained from the World Wide Web, was adopted for the analysis. Commercial telephony data or social networking applications were intentionally omitted. Both for data collection and later for modeling the potential of artificial neural networks was used. The potential of detection models such as YOLO or ResNet was explored. It was decided to focus on a method of acquiring additional data using information extraction from images and extracting information from web pages. The BDOT database and statistical data from the Central Statistical Office (polish: GUS) were adopted for the base model. It was shown that the use of street surveillance cameras in combination with deep learning methods gives an exam.

PL

W niniejszej pracy przedstawiono koncepcję stworzenia modelu do predykcji gęstości ludności oraz przedstawiono wykonane dotychczas prace. Jednostką odniesienia w badaniach jest bardziej gęstość ludności w danym miejscu niż śledzenie ruchów i nawyków człowieka. Do analizy przyjęto heterogeniczne otwarte dane, które można pozyskać z sieci WWW. Celowo pominięto komercyjne dane telefonii czy aplikacji społecznościowych. Zarówno do gromadzenia danych jak i później do modelowania wykorzystano potencjał sztucznych sieci neuronowych. Zbadano potencjał modeli detekcyjnych takich jak YOLO czy ResNet. Postanowiono skupić się na metodzie pozyskiwania dodatkowych danych z wykorzystaniem ekstrakcji informacji z obrazu oraz pozyskiwania informacji ze stron WWW. Do modelu bazowego przyjęto bazę danych BDOT oraz dane statystyczne z GUS. Wykazano, że wykorzystanie kamer monitoringu ulic w połączeniu z metodami głębokiego uczenia daje egzamin.

Słowa kluczowe

EN

population density; artificial neural network; detection model; information extraction; image

PL

gęstość zaludnienia; sztuczna sieć neuronowa; model detekcyjny; ekstrakcja informacji; obraz

• Wydawca: Polskie Towarzystwo Informacji Przestrzennej
• Czasopismo: Roczniki Geomatyki
• Rocznik: 2021
• Tom: T. 19, z. 2(93)
• Strony: 31--43
• Opis fizyczny: Bibliogr. 27 poz., rys., tab.

Twórcy

autor

Nadolny Adam

• Wroclaw University of Environment and Life Sciences, Institute of Geodesy and Geoinformatics Wroclaw Institute of Spatial Information and Artificial Intelligence

• https://orcid.org/0000-0002-8886-182X

Bibliografia

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