Inferring Person-to-person Proximity Using WiFi Signals

Today's societies are enveloped in an ever-growing telecommunication infrastructure. This infrastructure offers important opportunities for sensing and recording a multitude of human behaviors. Human mobility patterns are a prominent example of such a behavior which has been studied based on cell phone towers, Bluetooth beacons, and WiFi networks as proxies for location. However, while mobility is an important aspect of human behavior, understanding complex social systems requires studying not only the movement of individuals, but also their interactions. Sensing social interactions on a large scale is a technical challenge and many commonly used approaches---including RFID badges or Bluetooth scanning---offer only limited scalability. Here we show that it is possible, in a scalable and robust way, to accurately infer person-to-person physical proximity from the lists of WiFi access points measured by smartphones carried by the two individuals. Based on a longitudinal dataset of approximately 800 participants with ground-truth interactions collected over a year, we show that our model performs better than the current state-of-the-art. Our results demonstrate the value of WiFi signals in social sensing as well as potential threats to privacy that they imply

Crowds, Bluetooth and Rock’n’Roll: Understanding Music Festival Participant Behavior

In this paper we present a study of sensing and analyzing an offline social network of participants at a large-scale music festival (8 days, 130,000+ participants). We place 33 fixed-location Bluetooth scanners in strategic spots around the festival area to discover Bluetooth-enabled mobile phones carried by the participants, and thus collect spatio-temporal traces of their mobility and interactions. We subsequently analyze the data on two levels. On the micro level, we run a community detection algorithm to reveal a variety of groups the festival participants form. On the macro level, we employ an Infinite Relational Model (IRM) in order to recover the structure of the social network related to participants' music preferences. The obtained structure in the form of clusters of concerts and participants is then interpreted using meta-information about music genres, band origins, stages, and dates of performances. We show that most of the concerts clusters can be described by one or more of the meta-features, effectively revealing preferences of participants (e.g. a cluster of US bands) and discuss the significance of the findings and the potential and limitations of the used method. Finally, we discuss the possibility of employing the described method and techniques for creating user-oriented applications and extending the sensing capabilities during large-scale events by introducing user involvement.Comment: Presented at Sunbelt 2013 in Hamburg on May, 201

A Privacy Conscious Bluetooth Infrastructure for Location Aware Computing

We present a low cost and easily deployed infrastructure for location aware computing that is built using standard Bluetooth® technologies and personal computers. Mobile devices are able to determine their location to room-level granularity with existing bluetooth technology, and to even greater resolution with the use of the recently adopted bluetooth 1.2 specification, all while maintaining complete anonymity. Various techniques for improving the speed and resolution of the system are described, along with their tradeoffs in privacy. The system is trivial to implement on a large scale – our network covering 5,000 square meters was deployed by a single student over the course of a few days at a cost of less than US$1,000.Singapore-MIT Alliance (SMA

Who Tracks Who? A Surveillance Capitalist Examination of Commercial Bluetooth Tracking Networks

Object and person tracking networks powered by Bluetooth and mobile devices have become increasingly popular for purposes of public safety and individual concerns. This essay examines popular commercial tracking networks and their campaigns from Apple, Samsung and Tile with reference to surveillance capitalism and digital privacy, discovering the hidden assets commodified through said networks, and their potential of turning users into unregulated digital labour while leaving individual privacy at risk.Comment: 14 page

SenseBelt:a belt-worn sensor to support cross-device interaction

Mobile interaction is shifting from a single device to simultaneous interaction with ensembles of devices such as phones, tablets, or watches. Spatially-aware cross-device interaction between mobile devices typically requires a fixed tracking infrastructure, which lim- its mobility. In this paper, we present SenseBelt – a sensing belt that enhances existing mobile interactions and enables low-cost, ad hoc sensing of cross-device gestures and interactions. SenseBelt enables proxemic interactions between people and their personal devices. SenseBelt also supports cross-device interaction be- tween personal devices and stationary devices, such as public displays. We discuss the design and implementation of SenseBelt together with possible applications. With an initial evaluation, we provide insights into the benefits and drawbacks of a belt-worn mediating sensor to support cross-device interactions

Internet of things

Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Digital Earth was born with the aim of replicating the real world within the digital world. Many efforts have been made to observe and sense the Earth, both from space (remote sensing) and by using in situ sensors. Focusing on the latter, advances in Digital Earth have established vital bridges to exploit these sensors and their networks by taking location as a key element. The current era of connectivity envisions that everything is connected to everything. The concept of the Internet of Things(IoT)emergedasaholisticproposaltoenableanecosystemofvaried,heterogeneous networked objects and devices to speak to and interact with each other. To make the IoT ecosystem a reality, it is necessary to understand the electronic components, communication protocols, real-time analysis techniques, and the location of the objects and devices. The IoT ecosystem and the Digital Earth (DE) jointly form interrelated infrastructures for addressing today’s pressing issues and complex challenges. In this chapter, we explore the synergies and frictions in establishing an efficient and permanent collaboration between the two infrastructures, in order to adequately address multidisciplinary and increasingly complex real-world problems. Although there are still some pending issues, the identified synergies generate optimism for a true collaboration between the Internet of Things and the Digital Earth

Home Automation Using SSVEP & Eye-Blink Detection Based Brain-Computer Interface

In this paper, we present a novel brain computer interface based home automation system using two responses - Steady State Visually Evoked Potential (SSVEP) and the eye-blink artifact, which is augmented by a Bluetooth based indoor localization system, to greatly increase the number of controllable devices. The hardware implementation of this system to control a table lamp and table fan using brain signals has also been discussed and state-of-the-art results have been achieved.Comment: 2 pages, 1 table, published at IEEE SMC 201