A Study of Bluetooth Low Energy performance for human proximity detection in the workplace

Abstract

The ability to detect and distinguish interactions in the workplace can shed light over productivity, team work and on employees' use of space. Questionnaires and direct observations have often been used as mechanisms to identify office based interactions, however, these are either very time consuming, yield coarse grained information or do not scale to large numbers of people. Technology has been recently employed to cut costs and improve output, however precise interaction dynamics gathering often requires individuals to wear custom hardware. In this paper, we present an extensive evaluation of Bluetooth Low Energy (BLE) as a technology to monitor people proximity in the workplace. We examine the key parameters that affect the accuracy of the detected contacts and their impact on power consumption. We study how this system can be implemented on popular wearable devices (i.e., Android Wear and Tizen) and the resulting limitations. Through a real world deployment in a commercial organisation with 25 participants we evaluate the performances of a BLE-based proximity detection technique. Our results show the suitability of BLE for workplace interaction detection and give guidance to vendors and Operating System (OS) developers on the impact of the restrictions regarding the use of BLE on commodity wearables.

Automated sensing of daily activity: A new lens into development

“…For example, radio‐frequency signals and infrared beams can be used to can detect close contact (1–5 feet) as well as directionality, which can be used to detect face‐to‐face contact between individuals (Olguín et al, ). In contrast, Bluetooth radio waves are relatively far‐ranging but provide relatively coarse spatial resolution (e.g., distinguishing whether participants are 1–2, 3–4 vs. 5–10 feet from one another) (Boonstra, Larsen, Townsend, & Christensen, ; Montanari, Nawaz, Mascolo, & Sailer, ; Osmani, Carreras, Matic, & Saar, ). However, Bluetooth is an omnidirectional signal and thus cannot be used to detect face‐to‐face contact.…”

Measuring Interaction Proxemics with Wearable Light Tags

“…However, its high power leads to low sensing granularity (e.g., sampled every few minutes to avoid draining the battery quickly [9, 35,53]). Recent works [20,56,57,88] use Bluetooth Low Energy (BLE) to collect data on user proximity and mobility. Customized devices have also been used to monitor interactions.…”

“…Based on self-reporting, these approaches not only impose high burden on users, imply various biases, but also fail to provide behavioral information during a contact. Technology has progressed substantially in capturing fine-grained face-to-face interactions [28,29,52], however existing work still falls short: some either infer only user proximity [28,29,88] or body distances [52,119], or analyze speech-related non-verbal signals with no information on interaction distance and relative orientation [89]. Others focus on very specific contexts reproduced in the lab (e.g.…”

“…Thus, it is key to recognize both the line-of-sight proximity and user's relative body orientation. To this end, prior methods using radio frequency (RF) signals (e.g., Bluetooth, Wi-Fi) [22,75,88] or microphones [76,107,119] are all prone to false positives, since RF signals and sound penetrate human bodies. Also, relative body orientation cannot be simply obtained by compass sensors, which measure only the absolute orientation of the user/tag itself, rather than how it relates to other tags, as shown in § 4.1.…”

BeaLib: A Beacon Enabled Smart Library System

“…Beacons are small transmitters, run on BLE technology, used as a point of reference for mobile devices and they can detect a Bluetooth enabled device once it enters into its transmission range [4]. In this work, for experimentation purpose, a beacon is linked with a book in the library which provides the basic information of the book to a reader/library user without even picking up the book.…”