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Displaying 1-22 out of 22 total
Community-Aware Smartphone Sensing Systems
Found in: IEEE Internet Computing
By Nicholas D. Lane
Issue Date:May 2012
pp. 60-64
Despite people's central role within smartphone sensing, such systems remain largely oblivious to the effects of social networks and community dynamics. How might smartphone sensing systems change if they could see more than isolated individuals? What if s...
 
Exploiting Social Networks for Large-Scale Human Behavior Modeling
Found in: IEEE Pervasive Computing
By Nicholas D. Lane,Ye Xu,Hong Lu,Andrew T. Campbell,Tanzeem Choudhury,Shane B. Eisenman
Issue Date:October 2011
pp. 45-53
The Cooperative Communities (CoCo) learning framework leverages everyday social connections between people to personalize classification models. By exploiting social networks, CoCo spreads the burden of providing training data over an entire community.
 
The Rise of People-Centric Sensing
Found in: IEEE Internet Computing
By Andrew T. Campbell, Shane B. Eisenman, Nicholas D. Lane, Emiliano Miluzzo, Ronald A. Peterson, Hong Lu, Xiao Zheng, Mirco Musolesi, Kristóf Fodor, Gahng-Seop Ahn
Issue Date:July 2008
pp. 12-21
Technological advances in sensing, computation, storage, and communications will turn the near-ubiquitous mobile phone into a global mobile sensing device. People-centric sensing will help drive this trend by enabling a different way to sense, learn, visua...
 
Piggyback CrowdSensing (PCS): energy efficient crowdsourcing of mobile sensor data by exploiting smartphone app opportunities
Found in: Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems (SenSys '13)
By Fan Li, Feng Zhao, Hojung Cha, Nicholas D. Lane, Yohan Chon, Yongzhe Zhang, Dongwon Kim, Guanzhong Ding, Lin Zhou
Issue Date:November 2013
pp. 1-14
Fueled by the widespread adoption of sensor-enabled smartphones, mobile crowdsourcing is an area of rapid innovation. Many crowd-powered sensor systems are now part of our daily life -- for example, providing highway congestion information. However, partic...
     
2nd ACM international workshop on mobile systems for computational social science
Found in: Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication (UbiComp '13 Adjunct)
By Mirco Musolesi, Nicholas D. Lane
Issue Date:September 2013
pp. 875-882
The speech modality is a rich source of personal information. As such, speech detection is a fundamental function of many social sensing applications. Simply the amount of speech present in our surroundings can give indications about our socialbility and c...
     
Understanding the coverage and scalability of place-centric crowdsensing
Found in: Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing (UbiComp '13)
By Feng Zhao, Hojung Cha, Nicholas D. Lane, Yohan Chon, Yunjong Kim
Issue Date:September 2013
pp. 3-12
Crowd-enabled place-centric systems gather and reason over large mobile sensor datasets and target everyday user locations (such as stores, workplaces, and restaurants). Such systems are transforming various consumer services (for example, local search) an...
     
On the feasibility of user de-anonymization from shared mobile sensor data
Found in: Proceedings of the Third International Workshop on Sensing Applications on Mobile Phones (PhoneSense '12)
By Feng Zhao, Junyuan Xie, Nicholas D. Lane, Thomas Moscibroda
Issue Date:November 2012
pp. 1-5
Underpinning many recent advances in sensing applications (e.g., mHealth) is the ability to safely collect and share mobile sensor data. Research has shown that even from seemingly harmless sensors (e.g., accelerometers, gyroscopes, or magnetometers) an ev...
     
CarSafe: a driver safety app that detects dangerous driving behavior using dual-cameras on smartphones
Found in: Proceedings of the 2012 ACM Conference on Ubiquitous Computing (UbiComp '12)
By Andrew T. Campbell, Chuang-Wen You, Giuseppe Cardone, Hong Lu, Lorenzo Torresani, Martha Montes-de-Oca, Nicholas D. Lane, Thomas J. Bao
Issue Date:September 2012
pp. 671-672
Driving while being tired or distracted is dangerous. We are developing the CafeSafe app for Android phones, which fuses information from both front and back cameras and others embedded sensors on the phone to detect and alert drivers to dangerous driving ...
     
CarSafe demo: supporting driver safety using dual-cameras on smartphones
Found in: Proceedings of the 2012 ACM Conference on Ubiquitous Computing (UbiComp '12)
By Andrew T. Campbell, Chuang-Wen You, Giuseppe Cardone, Hong Lu, Lorenzo Torresani, Martha Montes-de-Oca, Nicholas D. Lane, Thomas J. Bao
Issue Date:September 2012
pp. 547-547
We demonstrate CarSafe, a driver safety application for Android phones that fuses information from both front and back cameras and others embedded sensors on the phone to detect and alert drivers to dangerous driving conditions in and outside of the car. I...
     
Automatically characterizing places with opportunistic crowdsensing using smartphones
Found in: Proceedings of the 2012 ACM Conference on Ubiquitous Computing (UbiComp '12)
By Fan Li, Feng Zhao, Hojung Cha, Nicholas D. Lane, Yohan Chon
Issue Date:September 2012
pp. 481-490
Automated and scalable approaches for understanding the semantics of places are critical to improving both existing and emerging mobile services. In this paper, we present CrowdSense@Place (CSP), a framework that exploits a previously untapped resource -- ...
     
Balancing energy, latency and accuracy for mobile sensor data classification
Found in: Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems (SenSys '11)
By Cong Pang, David Chu, Fan Li, Feng Zhao, Nicholas D. Lane, Qing Guo, Ted Tsung-Te Lai, Xiangying Meng
Issue Date:November 2011
pp. 54-67
Sensor convergence on the mobile phone is spawning a broad base of new and interesting mobile applications. As applications grow in sophistication, raw sensor readings often require classification into more useful application-specific high-level data. For ...
     
Mobile sensing: challenges, opportunities and future directions
Found in: Proceedings of the 13th international conference on Ubiquitous computing (UbiComp '11)
By Feng Zhao, Nicholas D. Lane, Tanzeem Choudhury
Issue Date:September 2011
pp. 637-638
The emerging field of mobile sensing has engaged computer scientists from a variety of existing communities, such as, mobile systems, machine learning and human computer interaction. Each community approaches the challenges of mobile sensing research with ...
     
Enabling large-scale human activity inference on smartphones using community similarity networks (csn)
Found in: Proceedings of the 13th international conference on Ubiquitous computing (UbiComp '11)
By Andrew T. Campbell, Feng Zhao, Hong Lu, Nicholas D. Lane, Shaohan Hu, Tanzeem Choudhury, Ye Xu
Issue Date:September 2011
pp. 355-364
Sensor-enabled smartphones are opening a new frontier in the development of mobile sensing applications. The recognition of human activities and context from sensor-data using classification models underpins these emerging applications. However, convention...
     
Tapping into the Vibe of the city using VibN, a continuous sensing application for smartphones
Found in: Proceedings of 1st international symposium on From digital footprints to social and community intelligence (SCI '11)
By Andrew T. Campbell, Andy M. Sarroff, Emiliano Miluzzo, Michela Papandrea, Nicholas D. Lane, Silvia Giordano
Issue Date:September 2011
pp. 13-18
We present VibN, a mobile sensing application deployed at large scale through the Apple App Store and the Android Market. VibN has been built to determine "what's going on" around the user in real-time by exploiting multiple sensor feeds. The application a...
     
The Jigsaw continuous sensing engine for mobile phone applications
Found in: Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems (SenSys '10)
By Andrew T. Campbell, Hong Lu, Jun Yang, Nicholas D. Lane, Tanzeem Choudhury, Zhigang Liu
Issue Date:November 2010
pp. 71-84
Supporting continuous sensing applications on mobile phones is challenging because of the resource demands of long-term sensing, inference and communication algorithms. We present the design, implementation and evaluation of the Jigsaw continuous sensing e...
     
Hapori: context-based local search for mobile phones using community behavioral modeling and similarity
Found in: Proceedings of the 12th ACM international conference on Ubiquitous computing (Ubicomp '10)
By Andrew T. Campbell, Dimitrios Lymberopoulos, Feng Zhao, Nicholas D. Lane
Issue Date:September 2010
pp. 109-118
Local search engines are very popular but limited. We present Hapori, a next-generation local search technology for mobile phones that not only takes into account location in the search query but richer context such as the time, weather and the activity of...
     
BikeNet: A mobile sensing system for cyclist experience mapping
Found in: ACM Transactions on Sensor Networks (TOSN)
By Andrew T. Campbell, Emiliano Miluzzo, Gahng-Seop Ahn, Nicholas D. Lane, Ronald A. Peterson, Shane B. Eisenman
Issue Date:December 2009
pp. 1-39
We present BikeNet, a mobile sensing system for mapping the cyclist experience. Built leveraging the MetroSense architecture to provide insight into the real-world challenges of people-centric sensing, BikeNet uses a number of sensors embedded into a cycli...
     
SoundSense: scalable sound sensing for people-centric applications on mobile phones
Found in: Proceedings of the 7th international conference on Mobile systems, applications, and services (Mobisys '09)
By Andrew T. Campbell, Hong Lu, Nicholas D. Lane, Tanzeem Choudhury, Wei Pan
Issue Date:June 2009
pp. 1-2
Top end mobile phones include a number of specialized (e.g., accelerometer, compass, GPS) and general purpose sensors (e.g., microphone, camera) that enable new people-centric sensing applications. Perhaps the most ubiquitous and unexploited sensor on mobi...
     
Integrating sensor presence into virtual worlds using mobile phones
Found in: Proceedings of the 6th ACM conference on Embedded network sensor systems (SenSys '08)
By Andrew T. Campbell, Emiliano Miluzzo, Mirco Musolesi, Nicholas D. Lane, Shane B. Eisenman, T. Choudhury
Issue Date:November 2008
pp. 1-2
WirelessHART is the first open wireless standard for the process control industry. Previously we demonstrated a three-node prototype network based on an early release of the protocol stack. In this demonstration we build a fully operational WirelessHART se...
     
Urban sensing systems: opportunistic or participatory?
Found in: Proceedings of the 9th workshop on Mobile computing systems and applications (HotMobile '08)
By Andrew T. Campbell, Emiliano Miluzzo, Mirco Musolesi, Nicholas D. Lane, Shane B. Eisenman
Issue Date:February 2008
pp. 1-2
The development of sensing systems for urban deployments is still in its infancy. An interesting unresolved issue is the precise role assumed by people within such systems. This issue has significant implications as to where the complexity and the main cha...
     
Ambient beacon localization: using sensed characteristics of the physical world to localize mobile sensors
Found in: Proceedings of the 4th workshop on Embedded networked sensors (EmNets '07)
By Andrew T. Campbell, Hong Lu, Nicholas D. Lane
Issue Date:June 2007
pp. 38-42
There is a growing need to support localization in low-power mobile sensor networks, both indoors and outdoors, when mobile sensor nodes (e.g., mote class) are incapable of independently estimating their location (e.g., when GPS is inappropriate or too cos...
     
People-centric urban sensing
Found in: Proceedings of the 2nd annual international workshop on Wireless internet (WICON '06)
By Andrew T. Campbell, Emiliano Miluzzo, Nicholas D. Lane, Ronald A. Peterson, Shane B. Eisenman
Issue Date:August 2006
pp. 18-es
The vast majority of advances in sensor network research over the last five years have focused on the development of a series of small-scale (100s of nodes) testbeds and specialized applications (e.g., environmental monitoring, etc.) that are built on low-...
     
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