Abstract
In this paper, we present a systematic analysis of large-scale human mobility patterns obtained from a passive Wi-Fi tracking system, deployed across different location typologies. We have deployed a system to cover urban areas served by public transportation systems as well as very isolated and rural areas. Over 4 years, we collected 572 million data points from a total of 82 routers covering an area of 2.8 km2. In this paper we provide a systematic analysis of the data and discuss how our low-cost approach can be used to help communities and policymakers to make decisions to improve people’s mobility at high temporal and spatial resolution by inferring presence characteristics against several sources of ground truth. Also, we present an automatic classification technique that can identify location types based on collected data.
Highlights
Introduction and motivationUnderstanding human mobility through wireless sensing and social networks is commonplace [15, 23]
We describe our results in terms of the different location typologies covered in our deployment
We start by presenting an overall view of the deployment and comparing the five different typologies, followed by a detailed analysis of the different locations where ground truth data was provided
Summary
Introduction and motivationUnderstanding human mobility through wireless sensing and social networks is commonplace [15, 23]. We can more analyze human mobility at unprecedented spatial and temporal resolutions This information is useful for many domains. Collecting mobility data at scale enables dataintensive services operating in real-time as well as offline data mining. These methods are useful to extract data about mobility-related domains such as tourism, visitors, interests, and site loads from social media, and compare it to the traditional sources [1, 10, 18]. This allows the system to be deployed ubiquitously in locations that lack the traditional counting methods, while locations that hold ground truth support the data analysis with as an automatic source of data and analytics, historical database, and human-free alternative
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