@inproceedings{9637aee5e82b4be681bc1620d087b712,
title = "Radioactive source localization in urban environments with sensor networks and the Internet of Things",
abstract = "The use of radiation detectors as an element in the so-called 'Internet of Things' has recently become viable with the available of low-cost, mobile radiation sensors capable of streaming geo-referenced data. New methods for fusing the data from multiple sensors on such a network is presented. The traditional simple and ordinary Kriging methods present a challenge for such a network since the assumption of a constant mean is not valid in this application. A variety of Kalman filters are introduced in an attempt to solve the problem associated with this variable and unknown mean. Results are presented on a deployed sensor network.",
author = "Sullivan, {Clair J.}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE lnternational Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2016 ; Conference date: 19-09-2016 Through 21-09-2016",
year = "2016",
month = jul,
day = "2",
doi = "10.1109/MFI.2016.7849518",
language = "English (US)",
series = "IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "384--388",
booktitle = "2016 IEEE lnternational Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2016",
address = "United States",
}