An elderly woman wanders about aimlessly in a home for assisted living. Suddenly, she collapses on the floor of a lonesome hallway. Usually it can take over two hours until a night nurse passes this spot on her next inspection round. But in this case she is already on site after two minutes, ready to help. She has received an alert message on her beeper: Inhabitant fallen in hallway 2b. The source: the SmartSurv distributed network of smart cameras for automated and privacy respecting video analysis. Welcome to the future of smart surveillance. Although this scenario is not yet daily practice, it shall make clear how such systems will impact the safety of the elderly without the privacy intrusion of traditional video surveillance systems.
%0 Book Section
%1 FleckStrasser10p985
%A Fleck, Sven
%A Straßer, Wolfgang
%B Handbook of Ambient Intelligence and Smart Environments
%C New York
%D 2010
%E Nakashima, Hideyuki
%E Aghajan, Hamid
%E Augusto, Juan Carlos
%I Springer
%K v1500 springer paper embedded ai image video recognition secure user data assist home
%P 985-1014
%R 10.1007/978-0-387-93808-0_37
%T Privacy Sensitive Surveillance for Assisted Living -- A Smart Camera Approach
%X An elderly woman wanders about aimlessly in a home for assisted living. Suddenly, she collapses on the floor of a lonesome hallway. Usually it can take over two hours until a night nurse passes this spot on her next inspection round. But in this case she is already on site after two minutes, ready to help. She has received an alert message on her beeper: Inhabitant fallen in hallway 2b. The source: the SmartSurv distributed network of smart cameras for automated and privacy respecting video analysis. Welcome to the future of smart surveillance. Although this scenario is not yet daily practice, it shall make clear how such systems will impact the safety of the elderly without the privacy intrusion of traditional video surveillance systems.
@incollection{FleckStrasser10p985,
abstract = {An elderly woman wanders about aimlessly in a home for assisted living. Suddenly, she collapses on the floor of a lonesome hallway. Usually it can take over two hours until a night nurse passes this spot on her next inspection round. But in this case she is already on site after two minutes, ready to help. She has received an alert message on her beeper: Inhabitant fallen in hallway 2b. The source: the SmartSurv distributed network of smart cameras for automated and privacy respecting video analysis. Welcome to the future of smart surveillance. Although this scenario is not yet daily practice, it shall make clear how such systems will impact the safety of the elderly without the privacy intrusion of traditional video surveillance systems.},
added-at = {2012-05-30T10:45:59.000+0200},
address = {New York},
author = {Fleck, Sven and Stra{\ss}er, Wolfgang},
biburl = {https://www.bibsonomy.org/bibtex/24381d378934cb122dc3f83dcc38d5f29/flint63},
booktitle = {Handbook of Ambient Intelligence and Smart Environments},
crossref = {NakashimaAghajanAugusto2010},
doi = {10.1007/978-0-387-93808-0_37},
editor = {Nakashima, Hideyuki and Aghajan, Hamid and Augusto, Juan Carlos},
file = {SpringerLink:2010/FleckStrasser10p985.pdf:PDF;Related Web Site:http\://www.smartsurv.de/:URL},
groups = {public},
interhash = {2fdcde28c57ea8cb0973cfc25fa5e5f9},
intrahash = {785435d03f3caf73d0712f2824827f34},
keywords = {v1500 springer paper embedded ai image video recognition secure user data assist home},
pages = {985-1014},
publisher = {Springer},
timestamp = {2015-03-05T14:19:54.000+0100},
title = {Privacy Sensitive Surveillance for Assisted Living -- A Smart Camera Approach},
username = {flint63},
year = 2010
}