Virtual trip lines for distributed privacy-preserving traffic monitoring
Proceedings of the 6th international conference on Mobile systems, applications, and services
SoundSense: scalable sound sensing for people-centric applications on mobile phones
Proceedings of the 7th international conference on Mobile systems, applications, and services
Open data kit sensors: mobile data collection with wired and wireless sensors
Proceedings of the 2nd ACM Symposium on Computing for Development
Web squared: paradigms and opportunities
Proceedings of the 5th International ICST Conference on Simulation Tools and Techniques
Open data kit sensors: a sensor integration framework for android at the application-level
Proceedings of the 10th international conference on Mobile systems, applications, and services
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
Distributed and Parallel Databases
A context-rich and extensible framework for spontaneous smartphone networking
Computer Communications
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Although mobile phones are ideal platforms for continuous human centric sensing, the state of the art phone architectures today have not been designed to support continuous sensing applications. Currently, sampling and processing sensor data on the phone requires the main processor and associated components to be continuously on, creating a large energy overhead that can severely impact the battery lifetime of the phone. We will demonstrate Little Rock, a novel sensing architecture for mobile phones, where sampling and, when possible, processing of sensor data is offloaded to a dedicated low-power processor. This approach enables the phone to perform continuous sensing three orders of magnitude more energy efficiently compared to the normal approaches.