Modelling population density using artificial neural networks from open data

Adam Nadolny
Uniwersytet Przyrodniczy we Wrocławiu

Streszczenie

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.

Słowa kluczowe:

population density, artificial neural networks, detection models, image information extraction

Pełny tekst:

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