Multiple-Perspective Clustering of Passive Wi-Fi Sensing Trajectory Data

12/22/2020
by   Zann Koh, et al.
23

Information about the spatiotemporal flow of humans within an urban context has a wide plethora of applications. Currently, although there are many different approaches to collect such data, there lacks a standardized framework to analyze it. The focus of this paper is on the analysis of the data collected through passive Wi-Fi sensing, as such passively collected data can have a wide coverage at low cost. We propose a systematic approach by using unsupervised machine learning methods, namely k-means clustering and hierarchical agglomerative clustering (HAC) to analyze data collected through such a passive Wi-Fi sniffing method. We examine three aspects of clustering of the data, namely by time, by person, and by location, and we present the results obtained by applying our proposed approach on a real-world dataset collected over five months.

READ FULL TEXT

page 5

page 8

page 11

page 13

page 15

research
02/05/2020

Understanding Crowd Behaviors in a Social Event by Passive WiFi Sensing and Data Mining

Understanding crowd behaviors in a large social event is crucial for eve...
research
10/27/2020

Dataset: LoED: The LoRaWAN at the Edge Dataset

This paper presents the LoRaWAN at the Edge Dataset (LoED), an open LoRa...
research
12/19/2017

Passive ans Active Observation: Experimetal Design Issues in Big Data

Data can be collected in scientific studies via a controlled experiment ...
research
12/19/2017

Passive ans Active Observation: Experimental Design Issues in Big Data

Data can be collected in scientific studies via a controlled experiment ...
research
12/19/2017

Passive and Active Observation: Experimental Design Issues in Big Data

Data can be collected in scientific studies via a controlled experiment ...
research
02/24/2019

Machine Learning Aided Anonymization of Spatiotemporal Trajectory Datasets

The big data era requires a growing number of companies to publish their...
research
01/09/2018

Robust Propensity Score Computation Method based on Machine Learning with Label-corrupted Data

In biostatistics, propensity score is a common approach to analyze the i...

Please sign up or login with your details

Forgot password? Click here to reset