Abstract
In the current Internet of Things (IoT) environment, objects are tagged with sensors without a clear understanding of people’s individual and collective patterns of behaviour. We argue that designers can create more meaningful and effective networked objects through collaborating with ethnographers and Machine Learning (ML) experts. In this paper, we present the approach and preliminary insights of two analysts from those disciplines on the same data set, and speculate on how they complement one another and the design process. Ethnographic data can indicate the questions that are interesting to study with ML algorithms and help interpret the data generated by ML by positioning it into wider socio-cultural situations. Ultimately, this collaboration can inspire designers to create meaningful products, services, and processes of IoT.
Original language | English |
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Title of host publication | Proceedings of PIN-C 2015 |
Subtitle of host publication | Reframing design, the 4th participatory innovation conference |
Publisher | The Hague University of Applied Sciences |
Pages | 500-506 |
Number of pages | 6 |
Edition | Track 5 |
Publication status | Published - 2015 |
Event | The 4th participatory innovation conference 2015, The Hague, The Netherlands - s.l. Duration: 18 May 2015 → 20 May 2015 |
Conference
Conference | The 4th participatory innovation conference 2015, The Hague, The Netherlands |
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Period | 18/05/15 → 20/05/15 |