relation: https://frw.studenttheses.ub.rug.nl/4763/
title: Privacy-aware agent-based simulation for modeling indoor movement patterns in university campuses
creator: Niemi, Elmeri
description: This master thesis explores the development of a privacy-conscious methodology for modeling indoor movement  patterns in campus environments using Agent-Based Simulation (ABS). The primary research question addresses  how movement can be accurately modeled while ensuring the privacy of individuals. The study utilizes WiFi-based  occupancy data and an adapted PageRank algorithm to predict movement behaviors within university buildings  without individual tracking. The ABS model incorporates various factors, including agent ontologies, room attractiveness, and spatial relationships, to simulate realistic indoor movement patterns. The model is validated using  real-world data from the University of Groningen, demonstrating strong correlation between simulated and observed  building occupancy. The findings highlight the effectiveness of the methodology in replicating movement patterns  across different areas of the building, though some areas required further refinement. The use of aggregate data  ensures privacy preservation, successfully balancing the need for data-driven insights with ethical data practices.  This research contributes a novel approach to the field of indoor spatial analysis, with practical applications for  space management, energy efficiency, and campus planning. The flexible framework developed can be adapted to  various indoor environments, offering significant potential for future research and implementation.
date: 2024
type: Thesis
type: NonPeerReviewed
format: text
language: en
identifier: https://frw.studenttheses.ub.rug.nl/4763/1/niemis3783723mscthesisfinal.pdf
identifier:   Niemi, Elmeri  (2024) Privacy-aware agent-based simulation for modeling indoor movement patterns in university campuses.  Master thesis.