CenceMe – Injecting Sensing Presence into Social Networking Applications

Miluzzo, Emiliano; Lane, Nicholas D.; Eisenman, Shane B.; Campbell, Andrew T.

doi:10.1007/978-3-540-75696-5_1

Cited by 148 publications

(114 citation statements)

References 26 publications

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“…In [2], Bao and Choudhury introduce MoVi that employs smartphones to enable collaborative sensing using videos for recognizing socially interesting events. In [20] Miluzzo et al utilize smartphone sensors to infer user's status and share on Facebook.…”

Section: Smartphone Sensingmentioning

confidence: 99%

LineKing: Crowdsourced Line Wait-Time Estimation Using Smartphones

Bulut

Yilmaz

Demirbaş

et al. 2013

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Abstract. This paper describes the design, implementation and deployment of LineKing (LK), a crowdsourced line wait-time monitoring service. LK consists of a smartphone component (that provides automatic, energy-efficient, and accurate wait-time detection), and a cloud backend (that uses the collected data to provide accurate wait-time estimation). LK is used on a daily basis by hundreds of users to monitor the wait-times of a coffee shop in our university campus. The novel wait-time estimation algorithms deployed at the cloud backend provide mean absolute errors of less than 2-3 minutes.

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Section: Smartphone Sensingmentioning

confidence: 99%

LineKing: Crowdsourced Line Wait-Time Estimation Using Smartphones

Bulut

Yilmaz

Demirbaş

et al. 2013

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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“…CenceMe [8], [9] developed by Emiliano et al automatically detects activities of individuals and shares the sensing results through social networks such as Facebook. In their work, various types of data such as location, acceleration, and audio signals are collected by sensors on mobile phones.…”

Section: Related Workmentioning

confidence: 99%

Multi-modal in-person interaction monitoring using smartphone and on-body sensors

Chen

Stankovic

2013

2013 IEEE International Conference on Body Sensor Networks

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Abstract-Various sensing systems have been exploited to monitor in-person interactions, one of the most important indicators of mental health. However, existing solutions either require deploying in-situ infrastructure or fail to provide detailed information about a person's involvement during interactions.In this paper, we use smartphones and on-body sensors to monitor in-person interactions without relying on any in-situ infrastructure. By using state-of-art smartphones and on-body sensors, we implement a multi-modal system that collects a battery of features to better monitor in-person interactions. In addition, unlike existing work that monitors interactions only based on data collected from one person, we emphasize that in-person interactions intrinsically involve multiple participants, and thus we aggregate information from nearby people to identify more interaction details. Evaluation shows our solution accurately detects various in-person interactions and provides insights absent in existing systems.

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“…In the future the system assumes that the user will be doing the same activity at that location. CenceMe system [12], senses low level user activity information (standing/walking/running and stationary/driving are the activities sensed currently) and shares the same presence information across all social networking sites. Sensors inbuilt like the accelerometer on the Nokia N95, Nokia 5500 Sport mobile phone or the Nike+ and microphones and web cameras on the mobile phone were used.…”

Section: Introductionmentioning

confidence: 99%

CrysP: Multi-Faceted Activity-Infused Presence in Emerging Social Networks

Saguna

Zaslavsky

Chakraborty

2010

Smart Spaces and Next Generation Wired/Wireless Networking

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Abstract. This paper presents Crystal Presence (CrysP) approach where we fuse presence and activity in the realm of social networking. CrysP functions on the basis of the activity-infused multi-faceted presence information. This information is derived from user's involvement in multiple activities at any point in time. We propose and develop the CrysP System (CrysPSys) to determine CrysP from the user and his/her environmental context information (mainly relating to user activity, moods/emotions and cognition/thoughts) and then sharing the relevant CrysP with the appropriate devices, services and social-networks (Corporate, Personal and Interest networks) and blogs (text, micro, video, photo and voice). We also highlight the benefits and challenges faced in developing such a system. This paper proposes the architecture and its test-bed and prototype implementation.

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CenceMe – Injecting Sensing Presence into Social Networking Applications

Cited by 148 publications

References 26 publications

LineKing: Crowdsourced Line Wait-Time Estimation Using Smartphones

LineKing: Crowdsourced Line Wait-Time Estimation Using Smartphones

Multi-modal in-person interaction monitoring using smartphone and on-body sensors

CrysP: Multi-Faceted Activity-Infused Presence in Emerging Social Networks

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