Tracking moving devices with the cricket location system

By Adam Smith, Hari Balakrishnan, Michel Goraczko, Bodhi Priyantha. ACM SIGMOBILE International Conference on Mobile Systems, Applications, and Services, 2004

488 citations recorded by the source corpus.

We study the problem of tracking a moving device under two indoor location architectures: an active mobile architecture and a passive mobile architecture. In the former, the infrastructure has receivers at known locations, which estimate distances to a mobile device based on an active transmission from the device. In the latter, the infrastructure has active beacons that periodically transmit signals to a passively listening mobile device, which in turn estimates distances to the beacons. Because the active mobile architecture receives simultaneous distance estimates at multiple receivers from the mobile device, it is likely to perform better tracking than the passive mobile system in which the device obtains only one distance estimate at a time and may have moved between successive estimates. However, an passive mobile system scales better with the number of mobile devices and puts users in control of whether their whereabouts are tracked.We answer the following question: How do the two architectures compare in tracking performance? We find that the active mobile architecture performs better at tracking, but that the passive mobile architecture has acceptable performance; moreover, we devise a hybrid approach that preserves the benefits of the passive mobile architecture while simultaneously providing the same performance as an active mobile system, suggesting a viable practical solution to the three goals of scalability, privacy, and tracking agility.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/4d6e5f04444523fd68099d951055a0aa232c3bcc

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Pedestrian localisation for indoor environments (2008, background): “As a result the accuracy is significantly worse relative to that of a comparable multilateral system [30].”
The Cricket indoor location system (2005, methodology): “As long as the active listener mode is infrequent, it does not significantly degrade scalability [92].”
Dude, where's my card?: RFID positioning that works with multipath and non-line of sight (2013, background): “PinIt is related to a wide range of work in locating wireless user devices [9, 39, 31, 11, 35, 45, 23].”
Robust distributed network localization with noisy range measurements (2004, unknown): “[22]).”
Reinforcement Learning in Sensor-Guided AIBO Robots (2007, background): “Whether this improvement outweighs loss of some original Cricket design goals, particularly privacy, is addressed in [7].”
A Review of Wearable Technologies for Elderly Care that Can Accurately Track Indoor Position, Recognize Physical Activities and Monitor Vital Signs in Real Time (2017, background): “Table 2 lists speciﬁc criteria and brief descriptions for elderly care systems [33,37,41].”
You are facing the Mona Lisa: spot localization using PHY layer information (2012, methodology): “The Cricket system [10, 27] and AH-LoS [28] utilize propagation delays between ultrasound and RF signals to estimate location of wireless devices.”
BreadCrumbs: forecasting mobile connectivity (2008, background): “Other work focuses on indoor localization at very small scales, either by deploying custom hardware [24] or mapping existing WiFi beacon sources [11].”