How we created edge computing

Edge computing processes data on infrastructure that is located close to the point of data creation. Mahadev Satyanarayanan recounts how recognition of the potential limitations of centralized, cloud-based processing led to this new approach to computing.Satyanarayanan, M.Nature Electronics, 2(1), January 2019

15-821 Fall 2018

6 course projects (many based on cloudlets and Gabriel)The Fall 2018 offering of 15-821/18-843 "Mobile and Pervasive Computing" course included several 2- and 3-person student projects based on cloudlets and wearable cognitive assistance. Examples include efficient searching of data stored on cloudlets, leveraging cloudlets for DNN gesture or

OpenRTiST

OpenRTiST utilizes Gabriel, a platform for wearable cognitive assistance applications, to transform the live video from a mobile client into the styles of various artworks.

Bandwidth-efficient Live Video Analytics for Drones via Edge Computing

Real-time video analytics on small autonomous drones poses several  difficult challenges at the intersection of wireless bandwidth,  processing capacity, energy consumption, result accuracy, and timeliness  of results. In response to these challenges, we describe four  strategies to build an adaptive computer vision pipeline for search  tasks in domains such as

Edge-based Discovery of Training Data for Machine Learning

The generation of high-quality training data has become the key  bottleneck in the use of deep learning across many domains. We describe  Eureka, an interactive system that leverages edge computing and early  discard to greatly improve the productivity of experts in the  construction of a labeled data set. Our experimental

Disk Tray Assembly

Disk Tray AssemblyIn collaboration with the company inwinSTACK, we created a Gabriel application for training a new worker in disk tray assembly for a desktop.   This demo was shown live at the Computex 2018 show in Taiwan in June 2018.   The application was created by Junjue Wang of CMU, and