@inproceedings{bb352af143ca41509a99167e0dcb1c14,
title = "Cluster segregation for indoor and outdoor environmental monitoring system",
abstract = "In this paper we describe an environmental system that has been developed to provide monitoring of pollutants. Unlike other work in the literature this system allows the collection and location-pinning of data to be carried out indoors as well as outdoors. The mixed indoor and outdoor data collected from different users can be classified into individual category using K-Means algorithm for further data analysis and visualization. Additionally implemented on a smartphone, such system could provide essential information on the air quality in a system, and feed data into an overall monitoring system as well as provide spot information to the user.",
keywords = "K-means clustering, Mobile sensing system, Real time indoor and outdoor pollution monitoring system",
author = "Xu Yang and Erchen Xie and Laurie Cuthbert",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016 ; Conference date: 12-12-2016 Through 14-12-2016",
year = "2017",
month = jan,
day = "20",
doi = "10.1109/HPCC-SmartCity-DSS.2016.0179",
language = "English",
series = "Proceedings - 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1264--1269",
editor = "Yang, {Laurence T.} and Jinjun Chen",
booktitle = "Proceedings - 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016",
address = "United States",
}