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Main Authors: Murcio, Roberto, Soundararaj, Balamurugan
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2501.06316
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author Murcio, Roberto
Soundararaj, Balamurugan
author_facet Murcio, Roberto
Soundararaj, Balamurugan
contents The accurate estimation of human activity in cities is one of the first steps towards understanding the structure of the urban environment. Human activities are highly granular and dynamic in spatial and temporal dimensions. Estimating confidence is crucial for decision-making in numerous applications such as urban management, retail, transport planning and emergency management. Detecting general trends in the flow of people between spatial locations is neither obvious nor easy due to the high cost of capturing these movements without compromising the privacy of those involved. This research intends to address this problem by examining the movement of people in a SmartStreetSensors network at a fine spatial and temporal resolution using a Transfer Entropy approach.
format Preprint
id arxiv_https___arxiv_org_abs_2501_06316
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Trends in urban flows: A transfer entropy approach
Murcio, Roberto
Soundararaj, Balamurugan
Information Theory
Methodology
The accurate estimation of human activity in cities is one of the first steps towards understanding the structure of the urban environment. Human activities are highly granular and dynamic in spatial and temporal dimensions. Estimating confidence is crucial for decision-making in numerous applications such as urban management, retail, transport planning and emergency management. Detecting general trends in the flow of people between spatial locations is neither obvious nor easy due to the high cost of capturing these movements without compromising the privacy of those involved. This research intends to address this problem by examining the movement of people in a SmartStreetSensors network at a fine spatial and temporal resolution using a Transfer Entropy approach.
title Trends in urban flows: A transfer entropy approach
topic Information Theory
Methodology
url https://arxiv.org/abs/2501.06316