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

^*Tämän työn vastaava kirjoittaja

Tutkimustuotos: Lehtiartikkeli › Article › Scientific › vertaisarvioitu

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Abstrakti

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.

Alkuperäiskieli	Englanti
Sivut	1773-1797
Sivumäärä	25
Julkaisu	Software - Practice and Experience
Vuosikerta	51
Numero	8
Varhainen verkossa julkaisun päivämäärä	18 toukokuuta 2021
DOI - pysyväislinkit	https://doi.org/10.1002/spe.2987
Tila	Julkaistu - elokuuta 2021
OKM-julkaisutyyppi	A1 Julkaistu artikkeli, soviteltu

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10.1002/spe.2987Lisenssi: CC BY

ELEC_Pham_etal_Ajalon_Software_Practice_and_Experience_2021_finalpublishedversionFinal published version, 5,04 MBLisenssi: CC BY

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CEAMA: CEAMA Cognitive Engine for Assembly and Maintenance Automation
Lee, J., Pham, T., Wirtanen, S., Xiao, Y., Souza Leite, C., Byvshev, P., Pouta, E., Nyman, P. & Berta, M.
01/08/2018 → 31/01/2020
Projekti: Business Finland: New business from research ideas (TUTLI)

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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.",

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

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",

month = aug,

doi = "10.1002/spe.2987",

language = "English",

volume = "51",

pages = "1773--1797",

journal = "SOFTWARE-PRACTICE AND EXPERIENCE",

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T2 - Simplifying the authoring of wearable cognitive assistants

AU - Pham, Truong An

AU - Wang, Junjue

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

Y1 - 2021/8

N2 - 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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KW - artificial intelligence

KW - augmented reality

KW - cloudlets

KW - computer vision

KW - edge computing

KW - Gabriel

KW - machine learning

KW - mobile computing

KW - software productivity

KW - wearables

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JO - SOFTWARE-PRACTICE AND EXPERIENCE

JF - SOFTWARE-PRACTICE AND EXPERIENCE

SN - 0038-0644

IS - 8

ER -

Ajalon: Simplifying the authoring of wearable cognitive assistants

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YK:n kestävän kehityksen tavoitteet

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CEAMA: CEAMA Cognitive Engine for Assembly and Maintenance Automation

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