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      Personal Data Collection in the Workplace: Ethical and Technical Challenges

      Author(s): , , , ,

      Publication date (Print):

      Conference name: Electronic Visualisation and the Arts (EVA 2017) (EVA)

      Conference theme: Electronic Visualisation and the Arts

      Conference date: 11 – 13 July 2017

      Keywords: Personal Data Collection, Hazardous environments, Rugged IoT, Ethics, Wearables

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          Abstract

          Forestry is a dangerous work environment and collecting data on site to identify and warn about hazardous situations is challenging. In this paper, we discuss our attempts at creating continuous data-collection methods that are ethical, sustainable and effective. We explore the difficulties in collecting personal and environmental data from workers and their work domain. We also draw attention to the specific challenges in designing for sensor-based, wearable rugged IoT solutions. We present a case-study, comprising of a number of experiments, which exemplifies the work we have been undertaking in this domain. The case study is based on our approach to developing a robust, trusted Internet of Things (IoT) solution for dangerous work environments (specifically the forestry environment). We focus the results of this case- study on both the technical successes and challenges as well as the personal and ethical challenges that have been elicited.

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          Most cited references 44

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          On the features and challenges of security and privacy in distributed internet of things

           Rodrigo Roman,  Jianying Zhou,  Javier LÓPEZ-HERNÁNDEZ (2013)
          Article 0 comments Cited 68 times – based on 0 reviews     Review now
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            Work load and work hours in relation to disturbed sleep and fatigue in a large representative sample.

             Torbjorn Akerstedt,  Peeter Fredlund,  Mats Gillberg … (2002)
            To study the relation between work and background factors on the one hand and disturbed sleep and fatigue on the other. A representative national sample of 58,115 individuals was selected at regular intervals over a period of 20 years and interviewed on issues related to work and health. The data were subjected to a multiple logistic regression analysis. The number of cases was 18,828 (32.8%) for fatigue and 7347 (12.8%) for disturbed sleep. For disturbed sleep, the significant predictors became: female gender, age above 49 years, present illness, hectic work, physically strenuous work, and shift work. For fatigue, the significant predictors became female gender, age below 49 years, high socioeconomic status, present illness, hectic work, overtime work, and physically strenuous work. Work stress, shift work, and physical workload interfere with sleep and are related to fatigue.
            Article 0 comments Cited 66 times – based on 0 reviews     Review now
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              An overview of the Internet of Things for people with disabilities

               Mari Domingo (2012)
              Article 0 comments Cited 46 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Judy Bowen
                Annika Hinze
                Christopher Griffiths
                Vimal Kumar
                David Bainbridge
                Conference
                Publication date: July 2017
                Publication date (Print): July 2017
                Pages: 1-11
                Affiliations
                Computer Science Department

                University of Waikato, New Zealand
                Article
                DOI: 10.14236/ewic/HCI2017.57
                Copyright statement: © Bowen et al. Published by BCS Learning and Development. Proceedings of British HCI 2017 – Digital Make-Believe, Sunderland, UK.
                License:

                This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                Conference name: Electronic Visualisation and the Arts (EVA 2017)
                Conference acronym: EVA
                Conference number:
                Conference location: London, UK
                Conference date: 11 – 13 July 2017
                Conference sponsor: Electronic Workshops in Computing (eWiC)
                Conference theme: Electronic Visualisation and the Arts
                Product
                Product Information: 1477-9358BCS Learning & Development
                Self URI (journal page): https://ewic.bcs.org/
                Categories
                Series title: Electronic Workshops in Computing

                Data availability:

                ScienceOpen disciplines: Applied computer science, Computer science, Security & Cryptology, Graphics & Multimedia design, General computer science, Human-computer-interaction

                Keywords: Wearables, Personal Data Collection, Hazardous environments, Rugged IoT, Ethics

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