T
Tanzeem Choudhury
Researcher at Cornell University
Publications - 146
Citations - 15264
Tanzeem Choudhury is an academic researcher from Cornell University. The author has contributed to research in topics: Ubiquitous computing & Mental health. The author has an hindex of 56, co-authored 146 publications receiving 13618 citations. Previous affiliations of Tanzeem Choudhury include National Institute for Health and Care Excellence & Dartmouth College.
Papers
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Journal ArticleDOI
A survey of mobile phone sensing
Nicholas D. Lane,Emiliano Miluzzo,Hong Lu,Daniel Peebles,Tanzeem Choudhury,Andrew T. Campbell +5 more
TL;DR: This article surveys existing mobile phone sensing algorithms, applications, and systems, and discusses the emerging sensing paradigms, and formulates an architectural framework for discussing a number of the open issues and challenges emerging in the new area ofMobile phone sensing research.
Proceedings ArticleDOI
SoundSense: scalable sound sensing for people-centric applications on mobile phones
TL;DR: This paper proposes SoundSense, a scalable framework for modeling sound events on mobile phones that represents the first general purpose sound sensing system specifically designed to work on resource limited phones and demonstrates that SoundSense is capable of recognizing meaningful sound events that occur in users' everyday lives.
Journal ArticleDOI
The Mobile Sensing Platform: An Embedded Activity Recognition System
Tanzeem Choudhury,Sunny Consolvo,Beverly L. Harrison,Jeffrey Hightower,Anthony LaMarca,Louis LeGrand,Ali Rahimi,Adam D. Rea,G. Bordello,Bruce Hemingway,Predrag Klasnja,Karl Koscher,James A. Landay,Jonathan Lester,Danny Wyatt,D. Haehnel +15 more
TL;DR: In this article, a wearable activity recognition system is proposed to recognize human activities from body-worn sensors, which can further open the door to a world of healthcare applications, such as fitness monitoring, eldercare support, long-term preventive and chronic care, and cognitive assistance.
Proceedings ArticleDOI
The Jigsaw continuous sensing engine for mobile phone applications
TL;DR: The design, implementation and evaluation of the Jigsaw continuous sensing engine is presented, which balances the performance needs of the application and the resource demands of continuous sensing on the phone, to demonstrate its capability to recognize user activities and perform long term GPS tracking in an energy-efficient manner.
Journal Article
A practical approach to recognizing physical activities
TL;DR: In this paper, a personal activity recognition system based on a cell phone platform augmented with a Bluetooth-connected sensor board is proposed to recognize 8 different activities collected from 12 different subjects.