Register online or contact Kristrún Gunnarsdóttir.
The Centre for Research in Social Simulation (CRESS) at the University of Surrey has announced the short course, Using sensors in social research, Wed 4 April and Thu 5 April 2018. Hosted at the University on Stag Hill in Guildford (see Google map), this will be an opportunity for research practitioners to learn about the use of digital sensors from members of the ESRC/NCRM funded HomeSense project.
Using sensors in social research will mix short presentations, interactive hands-on and exploratory sessions, group work and discussions for participants to obtain good understanding of the technologies and operating processes required for effective inclusion and management of this method.
It will also enable researchers to ask ‘how’ and ‘if’ sensors could be used in their own research, and how to address the ethical, consent, data security, confidentiality and other issues involved. Participants will receive a certificate of attendance of this NCRM methods course.
The lessons learned and inside knowledge from HomeSense fieldwork in a number of households, will also be presented, explaining and demonstrating the analytic tools and techniques required for visualising, interpreting and understanding human activities based largely on sensor-generated data.
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HomeSense is a National Centre for Research Methods (NCRM) supported Methodological Research Project that is focused on providing better understanding of the implications of using modern digital sensors in social research. But before the implications can be fully understood methodological issues such as finding meaning in sensor data has to be refined, which was the focus of a paper presented by Dr Jie Jiang at The International Conference on Future Networks and Distributed Systems (ICFNDS’17) in Cambridge in July this year.
The paper discussed, as a case study, data analysis of one testbed home in the early stages of the fieldwork, and dealt with finding meaning in sensor generated data and proposed methods for comparing data generated by sensors with self-reported time-use data generated by participants.
Since one of the implications of using sensors for social research is that, in due course, activities could be recognised automatically, it also proposed a method for modelling a range of activities recorded by sensors.
While the same approach was being applied in an extended version of the study with data from more households added to the mix, publication of the paper in the Proceedings of ICFNDS’17 provided an opportunity for some of its authors – Jie Jiang, Riccardo Pozza, Kristrún Gunnarsdóttir – to sit down and discuss the approach being taken by the HomeSense project.
That extension of the study to three households was also discussed by the team and is available here for download. Using Sensors to Study Home Activities (authors’ copy, freely available for fair use) is the latest HomeSense paper and has been accepted for publication in the Journal of Sensors and Actuator Networks.
Continue reading “Recognising Activities at Home using sensors: a HomeSense fieldwork case study”
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