Ajalon: Simplifying the authoring of wearable cognitive assistants

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

doi:10.1002/spe.2987

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

Mobile Cloud Computing

Research output: Contribution to journal › Article › Scientific › peer-review

5 Citations (Scopus)

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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 language	English
Pages (from-to)	1773-1797
Number of pages	25
Journal	Software - Practice and Experience
Volume	51
Issue number	8
Early online date	18 May 2021
DOIs	https://doi.org/10.1002/spe.2987
Publication status	Published - Aug 2021
MoE publication type	A1 Journal article-refereed

Keywords

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1002/spe.2987Licence: CC BY

ELEC_Pham_etal_Ajalon_Software_Practice_and_Experience_2021_finalpublishedversionFinal published version, 5.04 MBLicence: CC BY

Cite this

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title = "Ajalon: Simplifying the authoring of wearable cognitive assistants",

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.",

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author = "Pham, {Truong An} and Junjue Wang and Roger Iyengar and Yu Xiao and Padmanabhan Pillai and Roberta Klatzky and Mahadev Satyanarayanan",

note = "Funding Information: We thank the editor, Dr. Satish Srirama, and the anonymous reviewers for their guidance in improving the presentation of our work. This research was supported by Business Finland under the grant number 1660/31/2018, and by the National Science Foundation (NSF) under grant number CNS‐1518865. Roger Iyengar was supported by an NSF Graduate Research Fellowship under Grants DGE1252522 and DGE1745016. Additional support was provided by CableLabs, Crown Castle, Deutsche Telekom, Intel, InterDigital, Microsoft, Seagate, VMware, Vodafone, and the Conklin Kistler family fund. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the view(s) of their employers or the above funding sources. Publisher Copyright: {\textcopyright} 2021 The Authors. Software: Practice and Experience published by John Wiley & Sons Ltd. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",

year = "2021",

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volume = "51",

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AU - Iyengar, Roger

AU - Xiao, Yu

AU - Pillai, Padmanabhan

AU - Klatzky, Roberta

AU - Satyanarayanan, Mahadev

N1 - Funding Information: We thank the editor, Dr. Satish Srirama, and the anonymous reviewers for their guidance in improving the presentation of our work. This research was supported by Business Finland under the grant number 1660/31/2018, and by the National Science Foundation (NSF) under grant number CNS‐1518865. Roger Iyengar was supported by an NSF Graduate Research Fellowship under Grants DGE1252522 and DGE1745016. Additional support was provided by CableLabs, Crown Castle, Deutsche Telekom, Intel, InterDigital, Microsoft, Seagate, VMware, Vodafone, and the Conklin Kistler family fund. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the view(s) of their employers or the above funding sources. Publisher Copyright: © 2021 The Authors. Software: Practice and Experience published by John Wiley & Sons Ltd. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/8

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AB - 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.

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Ajalon: Simplifying the authoring of wearable cognitive assistants

Abstract

Keywords

UN SDGs

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CEAMA: Cognitive Engine for Assembly and Maintenance Automation

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Ajalon: Simplifying the authoring of wearable cognitive assistants

Abstract

Keywords

UN SDGs

Access to Document

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Fingerprint

Projects

CEAMA: Cognitive Engine for Assembly and Maintenance Automation

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