Collecting complex activity data sets in highly rich networked sensor environments
Sprache des Titels:
Englisch
Original Kurzfassung:
We deployed 15 wireless and wired networked
sensor systems comprising 72 sensors of 10 modalities - in
the environment, in objects, and on the body - to create a
sensor rich environment for the machine recognition of human
activities.We acquired data from 12 subjects performing morning
activities, yielding over 25 hours of sensor data. We report the
number of activity occurences observed during post-processing,
and estimate that over 11000 and 17000 object and environment
interactions occurred. We describe the networked sensor
setup and the methodology for data acquisition, synchronization
and curation. We report on the challenges and outline lessons
learned and best practice for similar large scale deployments
of heterogeneous networked sensor systems. We evaluate data
acquisition quality for on-body and object integrated wireless
sensors; less than 2.5% packet were lost lost after tuning. We
outline our use of the dataset to develop new sensor network
self-organization principles and machine learning techniques for
activity recognition in opportunistic sensor configurations.
Sprache der Kurzfassung:
Englisch
Journal:
Seventh International Conference on Networked Sensing Systems
Erscheinungsjahr:
2010
Anzahl der Seiten:
8
Publikationstyp:
Aufsatz / Paper in sonstiger referierter Fachzeitschrift