Public eyes get smart [CCTV camera]

2011 ◽  
Vol 6 (1) ◽  
pp. 38-41 ◽  
Author(s):  
M. Courtney
Keyword(s):  
Author(s):  
Saurabh Bhoite ◽  
Nagalakshmi Ravi ◽  
Kunal Giri ◽  
Kunal Gupta
Keyword(s):  

2018 ◽  
Vol 44 (2) ◽  
pp. 148-164 ◽  
Author(s):  
Jerry H. Ratcliffe ◽  
Elizabeth R. Groff

Methodological challenges have hampered a number of previous studies into the crime reduction effectiveness of closed-circuit television (CCTV) surveillance systems. These have included the use of arbitrary fixed distances to represent estimated camera deterrence areas and a lack of control for camera sites with overlapping surveillance areas. The current article overcomes the first of these challenges by using camera view areas individually constructed by researchers viewing and manipulating cameras to determine precise camera viewsheds. The second challenge is addressed by grouping cameras into clusters of combined viewshed areas. The longitudinal crime and disorder reduction effectiveness of these clusters of overlapping CCTV cameras is tested in Philadelphia, PA. Multilevel mixed-effects models with time-varying covariates and measures from a noncomparable control area are applied to 10 years of crime data (2003–2012) within the viewsheds of 86 CCTV cameras grouped into 13 clusters. Models applied across violent street felonies and disorder incidents find no significant impact associated with the introduction of CCTV surveillance. Potential reasons for this are discussed.


PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0259713
Author(s):  
Adarsh Jagan Sathyamoorthy ◽  
Utsav Patel ◽  
Moumita Paul ◽  
Yash Savle ◽  
Dinesh Manocha

Observing social/physical distancing norms between humans has become an indispensable precaution to slow down the transmission of COVID-19. We present a novel method to automatically detect pairs of humans in a crowded scenario who are not maintaining social distancing, i.e. about 2 meters of space between them using an autonomous mobile robot and existing CCTV (Closed-Circuit TeleVision) cameras. The robot is equipped with commodity sensors, namely an RGB-D (Red Green Blue—Depth) camera and a 2-D lidar to detect social distancing breaches within their sensing range and navigate towards the location of the breach. Moreover, it discreetly alerts the relevant people to move apart by using a mounted display. In addition, we also equip the robot with a thermal camera that transmits thermal images to security/healthcare personnel who monitors COVID symptoms such as a fever. In indoor scenarios, we integrate the mobile robot setup with a static wall-mounted CCTV camera to further improve the number of social distancing breaches detected, accurately pursuing walking groups of people etc. We highlight the performance benefits of our robot + CCTV approach in different static and dynamic indoor scenarios.


Author(s):  
W. K. Chung ◽  
B. Yi ◽  
E. K. Choi ◽  
J. H. Kim ◽  
S. D. Ahn ◽  
...  

2019 ◽  
Vol 1361 ◽  
pp. 012086
Author(s):  
Ummul Khair ◽  
Yuyun Dwi Lestari ◽  
Adidtya Perdana ◽  
Arief Budiman
Keyword(s):  

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