Creating people-aware IoT applications by combining design thinking and user-centered design methods

Fauquex, Milene; Goyal, Sidhant; Évéquoz, Florian; Bocchi, Yann

doi:10.1109/wf-iot.2015.7389027

Cited by 28 publications

(21 citation statements)

References 5 publications

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“…In the recent literature, there is a handful of methodologies and guidelines for the design of IoT applications. Examples include: a 7-step methodology (discovery, capturing, research, de-sign, prototype, evaluate and refine) for creating 'people-aware' IoT applications [4] a generic methodology for discovering and eliciting details of IoT use cases (understand, observe, synthesize, ideate, prototype, test and refine) enhanced with some special elements, like augmented representations of IoT elements, points of interest corresponding to places where information is generated, routed, read, etc [5] Typically, these methodologies are not (meant to be) used and tested as teaching/learning tools for IoT. Consequently they are not associated with particular educational goals and, in turn, they are not coupled with an educational assessment strategy.…”

Section: A Iot Design and Teaching Methodologiesmentioning

confidence: 99%

Designing IoT applications in lower secondary schools

Mavroudi

Divitini

Gianni

et al. 2018

2018 IEEE Global Engineering Education Conference (EDUCON)

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The paper reports on a case study where four groups of lower secondary school students participated in a workshop and undertook the demanding role of designers of Internet of Things applications. In doing that, they made use of a dedicated inventor toolkit, which facilitated students' creative solutions to problems that can appear in the context of a smart city. From a pedagogical point of view, the workshop format is in line with the experiential learning approach. The paper presents a holistic student assessment methodology for this nice domain. In particular, to analyse the impact of the workshop for the students we used four different approaches: artefacts analysis of students' design solutions, classroom observations, a post-test and a survey. The results indicate that the intervention has promoted an effective teaching methodology for the basic conceptual and design aspects of the IoT for these lower secondary school students, but it hasn't addressed equally effectively the attitude-related aspects. Nonetheless, the participant students perceived the intervention as very satisfactory in terms of the IoT concept knowledge, smart cities learning, and problem-solving skills acquired, as well as in terms of enjoyment. The paper concludes on the learning gains of the intervention and discusses the motivation aspect for the teacher as well as for the students in this highly innovative learning experience.

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Section: A Iot Design and Teaching Methodologiesmentioning

confidence: 99%

Designing IoT applications in lower secondary schools

Mavroudi

Divitini

Gianni

et al. 2018

2018 IEEE Global Engineering Education Conference (EDUCON)

View full text Add to dashboard Cite

show abstract

“…Apart from card-based ideation toolkits, there are various other design thinking approaches for creating user-centered (Wilson, 2005) and novel solutions in IoT. For example, Fauquex, Goyal, Evequoz, and Bocchi (2015) presented a methodology where user needs and expectations drive the core of the design process. Their methodology has seven stages: discovery, capturing, research, design, prototype, evaluate and refine.…”

Section: Ideation and Creativity In Relation To Iotmentioning

confidence: 99%

Investigating the Crowd’s Creativity for Creating On-Demand IoT Scenarios

Abbas¹,

Markopoulos²,

Khan³

2020

International Journal of Human–Computer Interaction

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The IoT industry supplies a plethora of Internet connected devices and services supporting smart home automation. However, end-users having little knowledge of the features and possibilities of such technologies, face difficulties in conjuring up useful application scenarios combining such devices and services, thus missing out on potential applications outside those provided by vendors. A remedy for such end-users can potentially be found in crowdsourcing IoT scenario creation. For such an enterprise to be viable it is essential to assess whether crowdsourcing can result in practical and original scenarios. This article reports two studies aiming to establish the practicality and originality of crowdsourced IoT scenarios for smart homes. In the first study, we recruited 102 crowd workers who created 306 scenarios in various categories. We then recruited a second cohort of 620 crowd workers to rate the scenarios' creativity. In the second study, we evaluated the corpus of IoT scenarios by 20-experienced smart home users recruited through a screening survey. Our results show that the crowd evaluations of originality and creativity are strongly correlated with those of smart home users. Our major IoT-specific findings in relation to creativity are: a) The number of IoT devices and the number of combination of devices impact how creative the scenarios are perceived; b) Workers with self-reported intermediate programming knowledge wrote more creative scenarios when compared to workers having expert knowledge; c) Computational metrics such as text metrics can provide the basis for automated assessment of the scenarios' creativity. Finally, an inductive thematic analysis of the scenarios revealed interesting themes (e.g., types of rules, automation styles and novel operators) which can serve as a guide for designing more expressive and intuitive end-user development solutions, in the context of IoT.

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“…There have been numerous studies highlighting the need and recognition of the human importance within the IoT [11][12][13]. Atzori et al [7] noted the importance saying "Particular attention has to be paid to the design of effective (better if "intelligent") interfaces both between humans and things and between things" (p. 135).…”

Section: Background and Related Workmentioning

confidence: 99%

Activity recognition evaluation via machine learning

Rameka¹,

Connor²,

Kruse³

2019

ICST Transactions on Ambient Systems

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With the proliferation of relatively cheap Internet of Things (IoT) devices, smart environments have been highlighted as an example of how the IoT can make our lives easier. Each of these 'things' produces data which can work in unison to react to its users. Machine learning makes use of this data to make inferences about our habits and activities, such as our buying preferences or likely commute destinations. However, this level of human inclusion within the IoT relies on indirect inferences from the usage of these devices or services. Activity recognition is already a widely researched area and could provide a more direct way of including humans within this system. This research explores the feasibility of using a cost effective, unobtrusive, single modality ground-based sensor matrix to track subtle pressure changes to predict user activity, in an effort to assess its ability to act as an intermediary interface between humans and digital systems such as the IoT.

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Creating people-aware IoT applications by combining design thinking and user-centered design methods

Cited by 28 publications

References 5 publications

Designing IoT applications in lower secondary schools

Designing IoT applications in lower secondary schools

Investigating the Crowd’s Creativity for Creating On-Demand IoT Scenarios

Activity recognition evaluation via machine learning

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