CAMPUSLIFEHealth and Technology
Together with Dartmouth University, Carnegie Mellon University and Cornell University, we at Georgia Tech are interested in extending the seminal work of StudentLife, started by Dartmouth’s Andrew Campbell a few years ago. Campbell sought to determine if mental health and academic performance could be correlated, or even predicted, through a student’s digital footprint. We are proposing the CampusLife project as a logical extension, which aims to collect data from relevant subsets of a campus community through their interactions with mobile and wearable technology, social media and the environment itself using an Internet of Things instrumentation. What drives this project is both a human goal of understanding wellness for young adults, as well as how one can perform such experimentation and address the significant security and privacy challenges. We invite everyone from the Georgia Tech community to join a conversation with the lead researchers from four universities to help influence the directions of this nascent effort.
For more information, contact Gregory Abowd.
COSMOSHuman-Environment Interactions Computational Materials
COSMOS is an interdisciplinary collaboration to design, manufacture, fabricate, and apply COmputational Skins for Multi-functional Objects and Systems (COSMOS). COSMOS consist of dense, high-performance, seamlessly-networked, ambiently-powered computational nodes that can process, store, and communicate sensor data. Achieving this vision will redefine the basis of human-environment interactions by creating a world in which everyday objects and information technology become inextricably entangled. COSMOS seeks to rethink the embodiment of computing through the integration of materials science and computation, literally realizing Weiser’s figurative “weaving” of technology into the fabric of everyday life.
For more information, contact Dingtian Zhang.
Computational Behavioral Science and AnalysisAutismChronic Diseases
A collaboration between developmental psychologists and computer scientists seeks to develop novel computational tools and methods to objectively measure behaviors in natural settings. The goal is to develop tools that can help us better detect, understand, and ultimately treat autism or other chronic diseases. Current standard practices for extracting useful behavioral information are typically difficult to replicate and require a lot of human time. For example, extensive training is typically required for a human coder to reliably code a particular behavior/interaction. Also, manual coding typically takes a lot more time than the actual length of the video. The time intensive nature of this process puts a strong limitation on the scalability of studies.
For more information, contact Agata Rozga, Rosa Arriaga, and Gregory Abowd.
Activity and Gesture Recognition for Mobile and Wearable ComputingActivity RecognitionGesture Recognition
Over the past few years, we have seen a number of wearable devices emerge that did a small number of tasks well (e.g., step counting). As these wrist-worn health trackers gained in popularity, commercial devices sought to do even more things around the wrist, to the point where a smartwatch is trying to become an all-purpose interaction device. Our group is working on a variety of explorations of mobile and on-body activity and gesture recognition systems, using both commodity sensing in existing devices and new form factors with novel sensing. Our goal is to expand the richness of existing interactions and activity recognition capabilities for everyday mobile and wearable computing users.
For gesture recognition and interaction systems, reach out to Cheng Zhang.
For activity recognition and passive sensing systems, reach out to Dingtian Zhang.
Eating DetectionHealth and Technology
Chronic and widespread diseases such as obesity, diabetes, and hypercholesterolemia require patients to monitor their food intake, and food journaling is currently the most common method for doing so. However, food journaling is subject to self-bias and recall errors, and is poorly adhered to by patients. This project explores the different ways eating episodes can be recognized as well as the potential applications of being able to recognize these episodes.For more information, please refer this page or contact Richard Li or Mehrab Bin Morshed
A great deal of work in personal informatics has focused on health and well-being, including areas such as fitness, eating, and sleep. Relatively little work has focused on transportation. According to the Bureau of Labor Statistics, transportation (mostly driving) is the second highest expense for the average American household, ahead of food and healthcare and behind only housing. Transportation Planners have long explored various strategies (mostly incentive-based) to encourage people to choose alternatives to driving alone, such as ride sharing, transit, and walking or biking. We have developed a personal informatics system that allows individuals to track their driving trips, and provides the user with an estimated cost for each trip (including fuel, vehicle depreciation, maintenance, insurance, taxes, and fees). By aggregating these dispersed costs on a per-trip basis, we provide drivers with a way to directly compare the cost of each driving trip to alternatives, such as Uber, transit, and so forth. We are exploring how revealing this personalized cost information impacts individual awareness, including the potential for behavior change, in how people make choices about their transportation modes and discretionary trips.
For more information, contact Caleb Southern.
Security and PrivacySecurityPrivacy
As the Internet of Things (IoT) and ubiquitous sensing technology emerges, users are exposed to large attack interfaces. IoT (smart home devices, cars, cameras, wearable devices) collect users’ private data and are involved with users’ daily life but can be remotely compromised. Compromising IoT devices such as cars can even jeopardize lives. While users are adopting IoT devices, new usable security mechanisms can be built on top of IoT infrastructure. Our group is working on a variety of explorations of security and privacy issues related to human beings and ubiquitous computing, building next-generation usable, secure, and privacy-preserving ubiquitous computing systems.
For more information, contact Weiren Wang.