research-article

An approach based on activity theory and the SRK model for risk and performance evaluation of human activities in a context-aware middleware

Authors:

Alfredo Del Fabro Neto,

Bruno Romero de Azevedo,

Rafael Boufleuer,

João Carlos D. Lima,

Marcia PasinAuthors Info & Claims

MUM '14: Proceedings of the 13th International Conference on Mobile and Ubiquitous Multimedia

Pages 40 - 47

https://doi.org/10.1145/2677972.2677982

Published: 25 November 2014 Publication History

Abstract

Even though human activities may involve physical injuries, there is not much discussion in the academy of how ubiquitous computing could assess the risk related to them. This paper proposes an approach to evaluate the risk of activities considering two factors: actions that compose activities and user performance in such activities. Risk management based on composed actions is measured through the analysis of the frequency of each action for a particular user, so that we are able to capture his customary behaviour. The evaluation of the user's performance is accomplished by addressing performance properties, such as: attention, duration, effectiveness, etc.

Our work has its foundations in the Activity Theory for modeling activities allowing the mediation by tools of the interactions between the subject and the environment and in the behavioural model Skill-Rule-Knowledge for understanding the subject's behaviours. To validate our model we developed a case study to demonstrate the functioning of our work. In this scenario we analyze how activities are detected, actions are evaluated and the performance is inferred. At last, an analysis of the final risk for the activity is presented.

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Cited By

Miranda LViterbo JBernardini F(2021)A survey on the use of machine learning methods in context-aware middlewares for human activity recognitionArtificial Intelligence Review10.1007/s10462-021-10094-055:4(3369-3400)Online publication date: 26-Oct-2021
https://doi.org/10.1007/s10462-021-10094-0

An approach based on activity theory and the SRK model for risk and performance evaluation of human activities in a context-aware middleware
1. Human-centered computing

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cover image ACM Other conferences

MUM '14: Proceedings of the 13th International Conference on Mobile and Ubiquitous Multimedia

November 2014

275 pages

ISBN:9781450333047

DOI:10.1145/2677972

General Chair:
Arkady Zaslavsky,
Program Chairs:
Seng W. Loke,
Lars Kulik,
Evaggelia Pitoura

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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New York, NY, United States

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Published: 25 November 2014

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MUM '14

MUM '14: International Conference on Mobile and Ubiquitous Multimedia

November 25 - 28, 2014

Victoria, Melbourne, Australia

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Cited By

Miranda LViterbo JBernardini F(2021)A survey on the use of machine learning methods in context-aware middlewares for human activity recognitionArtificial Intelligence Review10.1007/s10462-021-10094-055:4(3369-3400)Online publication date: 26-Oct-2021
https://doi.org/10.1007/s10462-021-10094-0

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