Jon E. Froehlich

Activity sensing in the wild: a field trial of ubifit garden

Recent advances in small inexpensive sensors, low-power processing, and activity modeling have enabled applications that use on-body sensing and machine learning to infer peoples activities throughout everyday life. To address the growing rate of sedentary lifestyles, we have developed a system, UbiFit Garden, which uses these technologies and a personal, mobile display to encourage physical activity. We conducted a 3-week field trial in which 12 participants used the system and report findings focusing on their experiences with the sensing and activity inference. We discuss key implications for systems that use on-body sensing and activity inference to encourage physical activity.

The design of eco-feedback technology

Eco-feedback technology provides feedback on individual or group behaviors with a goal of reducing environmental impact. The history of eco-feedback extends back more than 40 years to the origins of environmental psychology. Despite its stated purpose, few HCI eco-feedback studies have attempted to measure behavior change. This leads to two overarching questions: (1) what can HCI learn from environmental psychology and (2) what role should HCI have in designing and evaluating eco-feedback technology? To help answer these questions, this paper conducts a comparative survey of eco-feedback technology, including 89 papers from environmental psychology and 44 papers from the HCI and UbiComp literature. We also provide an overview of predominant models of proenvironmental behaviors and a summary of key motivation techniques to promote this behavior.

MyExperience: a system for in situ tracing and capturing of user feedback on mobile phones

This paper presents MyExperience, a system for capturing both objective and subjective in situ data on mobile computing activities. MyExperience combines the following two techniques: 1) passive logging of device usage, user context, and environmental sensor readings, and 2) active context-triggered user experience sampling to collect in situ, subjective user feedback. MyExperience currently runs on mobile phones and supports logging of more than 140 event types, including: 1) device usage such as communication, application usage, and media capture, 2) user context such as calendar appointments, and 3) environmental sensing such as Bluetooth and GPS. In addition, user experience sampling can be targeted to moments of interest by triggering off sensor readings. We present several case studies of field deployments on peoples personal phones to demonstrate how MyExperience can be used effectively to understand how people use and experience mobile technology.

Flowers or a robot army?: encouraging awareness & activity with personal, mobile displays

Personal, mobile displays, such as those on mobile phones, are ubiquitous, yet for the most part, underutilized. We present results from a field experiment that investigated the effectiveness of these displays as a means for improving awareness of daily life (in our case, self-monitoring of physical activity). Twenty-eight participants in three experimental conditions used our UbiFit system for a period of three months in their day-to-day lives over the winter holiday season. Our results show, for example, that participants who had an awareness display were able to maintain their physical activity level (even during the holidays), while the level of physical activity for participants who did not have an awareness display dropped significantly. We discuss our results and their general implications for the use of everyday mobile devices as awareness displays.

Route Prediction from Trip Observations

This paper develops and tests algorithms for predicting the end-to-end route of a vehicle based on GPS observations of the vehicle’s past trips. We show that a large portion of a typical driver’s trips are repeated. Our algorithms exploit this fact for prediction by matching the first part of a driver’s current trip with one of the set of previously observed trips. Rather than predicting upcoming road segments, our focus is on making long term predictions of the route. We evaluate our algorithms using a large corpus of real world GPS driving data acquired from observing over 250 drivers for an average of 15.1 days per subject. Our results show how often and how accurately we can predict a driver’s route as a function of the distance already driven.

Disaggregated End-Use Energy Sensing for the Smart Grid

This article surveys existing and emerging disaggregation techniques for energy-consumption data and highlights signal features that might be used to sense disaggregated data in an easily installed and cost-effective manner.

Unifying artifacts and activities in a visual tool for distributed software development teams

In large projects, software developers struggle with two sources of complexity - the complexity of the code itself, and the complexity of the process of producing it. Both of these concerns have been subjected to considerable research investigation, and tools and techniques have been developed to help manage them. However, these solutions have generally been developed independently, making it difficult to deal with problems that inherently span both dimensions. We describe Augur, a visualization tool that supports distributed software development processes. Augur creates visual representations of both software artifacts and software development activities, and, crucially, allows developers to explore the relationship between them. Augur is designed not for managers, but for the developers participating in the software development process. We discuss some of the early results of informal evaluation with open source software developers. Our experiences to date suggest that combining views of artifacts and activities is both meaningful and valuable to software developers.

Ability-Based Design: Concept, Principles and Examples

Current approaches to accessible computing share a common goal of making technology accessible to users with disabilities. Perhaps because of this goal, they may also share a tendency to centralize disability rather than ability. We present a refinement to these approaches called ability-based design that consists of focusing on ability throughout the design process in an effort to create systems that leverage the full range of human potential. Just as user-centered design shifted the focus of interactive system design from systems to users, ability-based design attempts to shift the focus of accessible design from disability to ability. Although prior approaches to accessible computing may consider users’ abilities to some extent, ability-based design makes ability its central focus. We offer seven ability-based design principles and describe the projects that inspired their formulation. We also present a research agenda for ability-based design.

Are GSM Phones THE Solution for Localization

In this paper, we argue that localization solution based on cellular phone technology, specifically GSM phones, is a sufficient and attractive option in terms of coverage and accuracy for a wide range of indoor, outdoor, and placebased location-aware applications. We present preliminary results that indicate that GSM-based localization systems have the potential to detect the places that people visit in their everyday lives, and can achieve median localization accuracies of 5 and 75 meters for indoor and outdoor environments, respectively.

Mind the theoretical gap: interpreting, using, and developing behavioral theory in HCI research

Researchers in HCI and behavioral science are increasingly exploring the use of technology to support behavior change in domains such as health and sustainability. This work, however, remain largely siloed within the two communities. We begin to address this silo problem by attempting to build a bridge between the two disciplines at the level of behavioral theory. Specifically, we define core theoretical terms to create shared understanding about what theory is, discuss ways in which behavioral theory can be used to inform research on behavior change technologies, identify shortcomings in current behavioral theories, and outline ways in which HCI researchers can not only interpret and utilize behavioral science theories but also contribute to improving them.