A framework for the automated generation of power-efficient classifiers for embedded sensor nodes
Proceedings of the 5th international conference on Embedded networked sensor systems
A building block approach to sensornet systems
Proceedings of the 6th ACM conference on Embedded network sensor systems
Nericell: rich monitoring of road and traffic conditions using mobile smartphones
Proceedings of the 6th ACM conference on Embedded network sensor systems
VTrack: accurate, energy-aware road traffic delay estimation using mobile phones
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
In-car positioning and navigation technologies: a survey
IEEE Transactions on Intelligent Transportation Systems
Using mobile phones to determine transportation modes
ACM Transactions on Sensor Networks (TOSN)
Towards mobile phone localization without war-driving
INFOCOM'10 Proceedings of the 29th conference on Information communications
Privacy risks emerging from the adoption of innocuous wearable sensors in the mobile environment
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Energy-efficient positioning for smartphones using Cell-ID sequence matching
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
Review: From wireless sensor networks towards cyber physical systems
Pervasive and Mobile Computing
Social-Loc: improving indoor localization with social sensing
Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
Wearable sensor empowered smart tele-robotics system for patient and senior independent living
Journal of Computing Sciences in Colleges
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We present AutoWitness, a system to deter, detect, and track personal property theft, improve historically dismal stolen property recovery rates, and disrupt stolen property distribution networks. A property owner embeds a small tag inside the asset to be protected, where the tag lies dormant until it detects vehicular movement. Once moved, the tag uses inertial sensor-based dead reckoning to estimate position changes, but to reduce integration errors, the relative position is reset whenever the sensors indicate the vehicle has stopped. The sequence of movements, stops, and turns are logged in compact form and eventually transferred to a server using a cellular modem after both sufficient time has passed (to avoid detection) and RF power is detectable (hinting cellular access may be available). Eventually, the trajectory data are sent to a server which attempts to match a path to the observations. The algorithm uses a Hidden Markov Model of city streets and Viterbi decoding to estimate the most likely path. The proposed design leverages low-power radios and inertial sensors, is immune to intransit cloaking, and supports post hoc path reconstruction. Our prototype demonstrates technical viability of the design; the volume market forces driving machine-to-machine communications will soon make the design economically viable.