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Title: Sistema de monitorización de flujo ciudadano mediante el uso de WiFi y LoRaWAN
Author: Delgado Bajo, Adrián
Director: Raul Parada Medina
Tutor: Carlos Monzo Sánchez
Keywords: WiFi
Big Data
Machine learning
Issue Date: Jan-2019
Publisher: Universitat Oberta de Catalunya (UOC)
Abstract: Over the last years there have been several projects that, using new technologies, have managed to create innovative and efficient solutions for daily problems. When it comes to public flow planning, managers plan based on either incomplete information (like public transport related information) or guesses (assuming that people will use a wider, pedestrian friendly street over the parallel, smaller streets). However, they rarely have real and trustworthy data, so the planning usually becomes hard and uncertain. In this work we develop a device that, monitoring radiofrequential systems, WiFi packages emitted from mobile devices specifically, monitors realiably the flow of pedestrians in a known location. Moreover, knowing also the time and location of each device we will create an application that will perform an analysis from wich we will generate statistics and visual reports that show the pedestrian flow between some locations in a city. To achieve this goal, we will use the LoRaWAN technology to send data due to it's high range in urban environment and it's low cost of both material and battery and we will apply graphic and Big Data analytics to enhance the final reports. The final result is a pedestrian flow monitoring tool that offers high quality and valuable information for urban planners or other professionals so they can improve their policies and benefit all the citizens by, for example, chosing the best location for a public transport stations, events like exhibitions and similar or even predict the pedestrian flow when we direct traffic away from a certain street.
Language: Spanish
Appears in Collections:Bachelor thesis, research projects, etc.

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adelgado4TFM0119.pptxPresentación Powerpoint del proyecto.17.82 MBMicrosoft Powerpoint XMLView/Open
adelgado4TFM0119.pdfMemoria del proyecto.2.14 MBAdobe PDFView/Open

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