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Use it free: instantly knowing your phone attitude
TLDR
A3 - an accurate and automatic attitude detector for commodity smartphones that primarily leverages the gyroscope, but intelligently incorporates the accelerometer and magnetometer to select the best sensing capabilities and derive the most accurate attitude estimation.
How Long to Wait? Predicting Bus Arrival Time With Mobile Phone Based Participatory Sensing
TLDR
A bus arrival time prediction system based on bus passengers' participatory sensing that achieves outstanding prediction accuracy compared with those bus operator initiated and GPS supported solutions and is more generally available and energy friendly.
IODetector: a generic service for indoor outdoor detection
TLDR
This paper prototype the IODetector on Android mobile phones and evaluate the system comprehensively with data collected from 19 traces which include 84 different places during one month period, employing different phone models.
DopEnc: acoustic-based encounter profiling using smartphones
TLDR
DopEnc can automatically identify the persons that users interact with in the context of encountering and is extended to support parallel acoustic exploration of many users by incorporating a unique multiple access scheme within the limited inaudible acoustic frequency band.
Memento: An Emotion Driven Lifelogging System with Wearables
TLDR
This paper presents the design and implementation of Memento, an emotion driven lifelogging system on wearables that integrates EEG sensors with smart glasses and presents a customized two-phase emotion recognition architecture, considering both the affordability and efficiency of wearable-class devices.
How Long to Wait? Predicting Bus Arrival Time With Mobile Phone Based Participatory Sensing
TLDR
A bus arrival time prediction system based on bus passengers' participatory sensing that achieves outstanding prediction accuracy compared with those bus operator initiated and GPS supported solutions and is more generally available and energy friendly.
IODetector
TLDR
A lightweight sensing service that runs on the mobile phone and detects the indoor/outdoor environment in a fast, accurate, and efficient manner and greatly benefits many location-based and context-aware applications.
Urban Traffic Monitoring with the Help of Bus Riders
TLDR
The experience of building a participatory urban traffic monitoring system that exploits the power of bus riders' mobile phones and demonstrates the feasibility of such an approach achieving fine-grained traffic estimation with modest sensing and computation overhead at the crowd.
Real-time image-based driver fatigue detection and monitoring system for monitoring driver vigilance
TLDR
The established driver fatigue warning system can meet the real-time requirement of the driver fatigue state detection and the detection rate is higher than 95%.
A Participatory Urban Traffic Monitoring System: The Power of Bus Riders
TLDR
The real-world experiments with a prototype implementation demonstrate the feasibility of the participatory sensing-based urban traffic monitoring system, which achieves accurate and fine-grained traffic estimation with modest sensing and computation overhead at the crowd.
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