User-centric context inference for mobile crowdsensing
Authors:
Open Access
- 15 April 2019
- conference paper
- Published by Association for Computing Machinery (ACM)
- p. 261-266
Abstract
No abstract availableKeywords
This publication has 19 references indexed in Scilit:
- Dos and Don'ts in Mobile Phone Sensing Middleware2016
- Estimate a user's location using smartphone's barometer on a subway2015
- Impact of Indoor-Outdoor Context on Crowdsourcing based Mobile Coverage Analysis2015
- Mobile Crowd Sensing and ComputingACM Computing Surveys, 2015
- An Indoor Scene Recognition Algorithm Based on Pressure Change Pattern2015
- Ear-Phone: A context-aware noise mapping using smart phonesPervasive and Mobile Computing, 2015
- An Energy-Efficient and Robust Indoor-Outdoor Detection Method Based on Cell Identity MapProcedia Computer Science, 2015
- Context-Awareness for Mobile Sensing: A Survey and Future DirectionsIEEE Communications Surveys & Tutorials, 2014
- IODetectorACM Transactions on Sensor Networks, 2014
- Efficient in-pocket detection with mobile phones2013