Geert Vanderhulst

Tiny habits in the giant enterprise: understanding the dynamics of a quantified workplace

We offer a reflection on the technology usage for workplace quantification through an in the wild study. Using a prototype Quantified Workplace system equipped with passive and participatory sensing modalities, we collected and visualized different workplace metrics (noise, color, air quality, self reported mood, and self reported activity) in two European offices of a research organization for a period of 4 months. Next we surveyed 70 employees to understand their engagement experience with the system. We then conducted semi-structured interviews with 20 employees in which they explained which workplace metrics are useful and why, how they engage with the system and what privacy concerns they have. Our findings suggest that sense of inclusion acts as the initial incentive for engagement which gradually translates into a habitual routine. We found that incorporation of an anonymous participatory sensing aspect into the system could lead to sustained user engagement. Compared to past studies we observed a shift in the privacy concerns, due to the trust and transparency of our prototype system. We conclude by providing a set of design principles for building future Quantified Workplace systems.

Detecting human encounters from WiFi radio signals

We present the design, implementation and evaluation of a novel human encounter detection framework for measuring and analysing human behaviour in social settings. We propose the use of WiFi probes, management frames of WiFi, that periodically radiate from mobile devices (as proxies for humans), and existing WiFi access points to automatically capture radio signals and detect human copresence. Based on the spatio-temporal properties of this copresence and their interplay we defined a model, borrowing theories from sociology, to detect human encounters -- short-lived, spontaneous human interactions. We evaluated our framework using controlled and in-the-wild experiments yielding a detection performance of 96% and 86% respectively. As such, our framework opens up interesting opportunities for designing proxemic and group applications, as well as conducting large-scale studies in the areas of computational social sciences.

Quantified Workplace: Opportunities and Challenges

We present the design of a Quantified Workplace system which has been deployed in two European offices of a research organization since October 2014. So far, the system has collected more than 680,000 samples of various environment metrics in the workplace (e.g., noise, air quality, . . . ) and 57,340 data points on the indoor location of employees. In addition, the system has received 7504 participatory inputs from the users about their moods and physical activities in the workplace. We present the system and its different services, discuss our initial findings on the user engagement, and highlight the challenges of device heterogeneity, privacy and trust. We conclude by discussing potential applications of workplace quantification that can be developed using the data we are collecting.

Understanding the impact of personal feedback on face-to-face interactions in the workplace

Face-to-face interactions have proven to accelerate team and larger organisation success. Many past research has explored the benefits of quantifying face-to-face interactions for informed workplace management, however to date, little attention has been paid to understand how the feedback on interaction behaviour is perceived at a personal scale. In this paper, we offer a reflection on the automated feedback of personal interactions in a workplace through a longitudinal study. We designed and developed a mobile system that captured, modelled, quantified and visualised face-to-face interactions of 47 employees for 4 months in an industrial research lab in Europe. Then we conducted semi-structured interviews with 20 employees to understand their perception and experience with the system. Our findings suggest that the short-term feedback on personal face-to-face interactions was not perceived as an effective external cue to promote self-reflection and that employees desire long-term feedback annotated with actionable attributes. Our findings provide a set of implications for the designers of future workplace technology and also opens up avenues for future HCI research on promoting self-reflection among employees.

Exploring space syntax on entrepreneurial opportunities with Wi-Fi analytics

Industrial events and exhibitions play a powerful role in creating social relations amongst individuals and firms, enabling them to expand their social network so to acquire resources. However, often these events impose a spatial structure which impacts encounter opportunities. In this paper, we study the impact that the spatial configuration has on the formation of network relations. We designed, developed and deployed a Wi-Fi analytics solution comprising of wearable Wi-Fi badges and gateways in a large scale industrial exhibition event to study the spatio-temporal trajectories of the 2.5K+ attendees including two special groups: 34 investors and 27 entrepreneurs. Our results suggest that certain zones with designated functionalities play a key role in forming social ties across attendees and the different behavioural properties of investors and entrepreneurs can be explained through a spatial lens. Based on our findings we offer three concrete recommendations for future organisers of networking events.

Capturing Personal and Crowd Behavior with Wi-Fi Analytics

We present a solution for analysing crowds at events such as conferences where people have networking opportunities. Often, potential social relations go unexploited because no business cards were exchanged or we forget about interesting people we met earlier. We created a solution built on top of ubiquitous Wi-Fi signals that is able to create a memory of human trajectories and touch points. In this paper we elaborate on the technological assets we designed to perform crowd anlaytics. We present small wearable Wi-Fi badges that last for the duration of an event (up to 3 days) with a single charge, as well as network equipment that senses the signals radiating from these badges and contemporary mobile devices.

Exploring the design space for geo-fenced connected devices and services at home

This paper offers a reflection on the design space for a geo-fenced connected device and service (GFS) - a specification enforcing that a connected device can only be used within a virtual perimeter. Many connected devices are nowadays being accessed through applications running on mobile devices instead of tangible controls. Whilst this ubiquitous access is highly convenient, it is also making connected devices more vulnerable. As such, we reintroduce location-constrained interaction, adapted to connected devices present in a modern home, and explore three design cardinals: (i) spatial granularity, (ii) roles and delegation, and (iii) access control. We report on a qualitative study that explored this design space through a prototype geo-fenced connected lighting system. Our findings suggest that users would like to have geo-fencing for a subset of connected devices, prefer to define geo-fences statically but with different granularities for different devices, and desire access control through location verification and credentials.

A case study on capturing and visualising face-to-face interactions in the workplace

Face-to-face interactions have proven to accelerate team and larger organisation success. Many past research has explored the benefits of quantifying face-to-face interactions for informed workplace management, with little attention being paid to how this information is perceived by the employees. In this paper, we offer a reflection on the automated feedback of personal interactions in a workplace through a longitudinal study of capturing, modelling and visualisation of face-to-face interactions of 47 employees for 4 months in an industrial research lab in Europe. We conducted semi-structured interviews with 20 employees to understand their perception and experience with the system. Our findings suggest that the short-term feedback on personal face-to-face interactions was not perceived as an effective external cue to promote self-reflection by most, and that employees desire long-term feedback annotated with actionable attributes.

An Autonomous Reputation Framework for Physical Locations based on WiFi Signals

Online reviews are used on the large scale to assess the quality and reputation of urban venues like hotels, restaurants, museums, etc. However, contributing reviews requires manual effort in the digital world, undertaken by only a small fraction of a venues visitors. In this position paper, we present a framework that automatically assigns an offline reputation score by only relying on the physical presence of a user at a venue. In our approach, we passively capture the list of preferred WiFi networks (PNL) radiating from users smartphone as part of WiFi Probe requests in order to anonymously detect similar and recurrent users and to derive a personalised reputation score for an urban venue. By leveraging these ubiquitous WiFi radio signals, we seek to gather participation from a much broader set of visitors than online contributors. In this position paper, we outline our scoring technique, an early prototype architecture and discuss the potential of the proposed framework.

CrumblR: Enabling proxemic services through opportunistic location sharing

The need for a device to determine its own location and share it with individual Location-Based Services (LBSs) prevents large-scale adoption of indoor services, specially those belonging to small businesses or those intrinsic to short-lived events. We present CrumblR - a proxemic service broker platform that advocates anonymised location sharing with place owners instead of LBS providers to receive value-added contextual services. By decoupling location detection from LBSs, CrumblR liberates users from disclosing their locations to individual service providers. Our platform relies on opportunistic sharing of wireless signal fingerprints with nearby places to enable discovery of proxemic services associated with the place. In this WiP paper, we present the architectural design and the simple place proximity detection algorithms used in CrumblR.