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.

Pham, T. A., Wang, J., Iyengar, R., Xiao, Y., Pillai, P., Klatzky, R., & Satyanarayanan, M. (2021). Ajalon: Simplifying the authoring of wearable cognitive assistants. Software: Practice and Experience. 2021; 51: 1773– 1797 Wiley

https://doi.org/10.1002/spe.2987