Ajalon: Simplifying the authoring of wearable cognitive assistants

Truong An Pham*, Junjue Wang, Roger Iyengar, Yu Xiao, Padmanabhan Pillai, Roberta Klatzky, Mahadev Satyanarayanan

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Wearable Cognitive Assistance (WCA) amplifies human cognition in real time through a wearable device and low-latency wireless access to edge computing infrastructure. It is inspired by, and broadens, the metaphor of GPS navigation tools that provide real-time step-by-step guidance, with prompt error detection and correction. WCA applications are likely to be transformative in education, health care, industrial troubleshooting, manufacturing, assisted driving, and sports training. Today, WCA application development is difficult and slow, requiring skills in areas such as machine learning and computer vision that are not widespread among software developers. This paper describes Ajalon, an authoring toolchain for WCA applications that reduces the skill and effort needed at each step of the development pipeline. Our evaluation shows that Ajalon significantly reduces the effort needed to create new WCA applications.

Original languageEnglish
Number of pages25
JournalSoftware - Practice and Experience
DOIs
Publication statusE-pub ahead of print - 18 May 2021
MoE publication typeA1 Journal article-refereed

Keywords

  • artificial intelligence
  • augmented reality
  • cloudlets
  • computer vision
  • edge computing
  • Gabriel
  • machine learning
  • mobile computing
  • software productivity
  • wearables

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