CMU-CS-13-134
Computer Science Department
School of Computer Science, Carnegie Mellon University



CMU-CS-13-134

Towards Wearable Cognitive Assistance

Kiryong Ha, Zhuo Chen, Wenlu Hu, Wolfgang Richter,
Padmanabhan Pillai*, Mahadev Satyanarayanan

December 2013

CMU-CS-13-134.pdf


Keywords: Mobile computing, cloud computing, Google Glass, virtual machines, system architecture, cloudlets, face detection, face recognition, object recognition, OCR, activity recognition, motion classification, context awareness, graceful degradation

We describe the architecture and prototype implementation of an assistive system based on Google Glass devices for users in cognitive decline. It combines the first-person image capture and sensing capabilities of Glass with cloud processing to perform real-time scene interpretation. The system architecture is multi-tiered. It offers tight end-to-end latency bounds on compute-intensive operations, while addressing concerns such as limited battery capacity and limited processing capability of wearable devices. The system gracefully degrades services in the face of network failures and unavailability of distant architectural tiers.

25 pages

*Intel Labs



Return to: SCS Technical Report Collection
School of Computer Science

This page maintained by reports@cs.cmu.edu