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Summary: COMMUNICATIONS OF THE ACM September 2005/Vol. 48, No. 9 39
The iBracelet and the Wireless Identification
and Sensing Platform promise the ability to infer
human activity directly from sensor readings.
RFID-BASED TECHNIQUES FOR
HUMAN-ACTIVITY
DETECTION
Many ubiquitous computing scenarios require an intelligent environ-
ment to infer what a person is doing or attempting to do. Historically,
human-activity tracking techniques have focused on direct observa-
tion of people and their behavior--with cameras, worn accelerome-
ters, or contact switches. A recent promising avenue [4, 7] is to
supplement direct observation with an indirect approach, inferring
people's actions from their effect on the environment, especially on the
objects with which they interact.
Researchers have applied three main techniques to human-activity
detection: computer vision, active sensor beacons [4], and passive
RFID. Vision involves well-known robustness and scalability challenges.
Active sensor beacons provide accurate object identification but require
batteries, making them impractical for long-term dense deployment.
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