Ensembling neural networks: many could be better than all
Artificial Intelligence
SATIRE: a software architecture for smart AtTIRE
Proceedings of the 4th international conference on Mobile systems, applications and services
The BikeNet mobile sensing system for cyclist experience mapping
Proceedings of the 5th international conference on Embedded networked sensor systems
The pothole patrol: using a mobile sensor network for road surface monitoring
Proceedings of the 6th international conference on Mobile systems, applications, and services
Body posture identification using hidden Markov model with a wearable sensor network
BodyNets '08 Proceedings of the ICST 3rd international conference on Body area networks
Proceedings of the 6th ACM conference on Embedded network sensor systems
SoundSense: scalable sound sensing for people-centric applications on mobile phones
Proceedings of the 7th international conference on Mobile systems, applications, and services
A framework of energy efficient mobile sensing for automatic user state recognition
Proceedings of the 7th international conference on Mobile systems, applications, and services
IEEE Transactions on Knowledge and Data Engineering
SurroundSense: mobile phone localization via ambience fingerprinting
Proceedings of the 15th annual international conference on Mobile computing and networking
A hybrid discriminative/generative approach for modeling human activities
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Mercury: a wearable sensor network platform for high-fidelity motion analysis
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Activity recognition from on-body sensors: accuracy-power trade-off by dynamic sensor selection
EWSN'08 Proceedings of the 5th European conference on Wireless sensor networks
Darwin phones: the evolution of sensing and inference on mobile phones
Proceedings of the 8th international conference on Mobile systems, applications, and services
Exploring link correlation for efficient flooding in wireless sensor networks
NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation
ZiFi: wireless LAN discovery via ZigBee interference signatures
Proceedings of the sixteenth annual international conference on Mobile computing and networking
The κ factor: inferring protocol performance using inter-link reception correlation
Proceedings of the sixteenth annual international conference on Mobile computing and networking
Bridging the gap between physical location and online social networks
Proceedings of the 12th ACM international conference on Ubiquitous computing
EmotionSense: a mobile phones based adaptive platform for experimental social psychology research
Proceedings of the 12th ACM international conference on Ubiquitous computing
Using wearable activity type detection to improve physical activity energy expenditure estimation
Proceedings of the 12th ACM international conference on Ubiquitous computing
SensLoc: sensing everyday places and paths using less energy
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems
The Jigsaw continuous sensing engine for mobile phone applications
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems
How long to wait?: predicting bus arrival time with mobile phone based participatory sensing
Proceedings of the 10th international conference on Mobile systems, applications, and services
IODetector: a generic service for indoor outdoor detection
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
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The vast array of small wireless sensors is a boon to body sensor network applications, especially in the context awareness and activity recognition arena. However, most activity recognition deployments and applications are challenged to provide personal control and practical functionality for everyday use. We argue that activity recognition for mobile devices must meet several goals in order to provide a practical solution: user friendly hardware and software, accurate and efficient classification, and reduced reliance on ground truth. To meet these challenges, we present PBN: Practical Body Networking. Through the unification of TinyOS motes and Android smartphones, we combine the sensing power of on-body wireless sensors with the additional sensing power, computational resources, and user-friendly interface of an Android smartphone. We provide an accurate and efficient classification approach through the use of ensemble learning. We explore the properties of different sensors and sensor data to further improve classification efficiency and reduce reliance on user annotated ground truth. We evaluate our PBN system with multiple subjects over a two week period and demonstrate that the system is easy to use, accurate, and appropriate for mobile devices.