@inproceedings{1cc480055e334876b5bb31238d7a3b20,
title = "Poster-SaveAlert: An efficient and scalable sensor-driven danger detection system",
abstract = "SaveAlert is an adaptive framework for crowd-monitoring and danger-detection using off-the-shelf smartphones and other peripherals such as smartwatches. It is a system that provides users with an increased awareness of their surround- ings by detecting and notifying them of impending danger, by relying only on sensor data collected from the users. Our framework's novelty is in how it performs efficient sensor data collection from potentially a large number of people by limiting the disturbance and stress on the existing Wi-Fi and cellular infrastructure. To the best of our knowledge, this is the first crowd-monitoring framework that takes advantage of peer-to-peer connections to perform local aggregation to alleviate the stress on existing infrastructures for better scal- Ability and efficiency.",
keywords = "Crowd dynamics, Crowd monitoring, Crowd sensing, Dan- ger detection, Safety",
author = "Tuncay, {G{\"u}liz Seray} and Kirill Varshavskiy and Robin Kravets and Klara Nahrstedt",
note = "Publisher Copyright: {\textcopyright} 2014 by the Association for Computing Machinery, Inc. (ACM).; 20th ACM Annual International Conference on Mobile Computing and Networking, MobiCom 2014 ; Conference date: 07-09-2014 Through 11-09-2014",
year = "2014",
month = sep,
day = "7",
doi = "10.1145/2639108.2642908",
language = "English (US)",
series = "Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM",
publisher = "Association for Computing Machinery",
pages = "437--439",
booktitle = "MobiCom 2014 - Proceedings of the 20th Annual",
address = "United States",
}