Over the past decade video surveillance has migrated from analog closed circuit television systems with point-to-point connections to modern digital systems that run on IP networks. Enterprise video surveillance systems can scale to hundreds or thousands of cameras spread across geographically dispersed facilities, but this presents bandwidth, processing and storage challenges. The cost to deploy and maintain such systems over their lifetime can be staggering, but new video analytics technology offers a compelling alternative.
Video analytics is the automated analysis of video content for user-defined events of interest. The technology is primarily used for physical security and business intelligence applications. Capabilities range from simple
motion detection to sophisticated algorithms for detection
of people, vehicles, objects and their behaviors or interactions. The best techniques ignore normal scene
changes in a camera view as well as motion due to snow, rain and tree foliage.
Examples of physical security applications include perimeter breach, loitering or removal of an object, while business intelligence applications include measurement
of customer traffic and analysis of customer behavior. However, video analytics does much more than optimize safety and security and enable better business decisions ā it also reduces the total cost of IP video surveillance system
ownership.
The major elements of an IP video surveillance system
are cameras, recorders, servers and software. Cameras are distributed across monitored locations, while
recorders and servers are typically centralized for ease of
management. A video management system (VMS) provides
unified access to live and recorded video and aggregates
hardware from multiple vendors.
New cameras employ MPEG-4 and H.264 compression to
provide DVD or HD-resolution video at bit rates between
1M and 12Mbps. It is desirable to consolidate recorders
and servers centrally for ease of configuration and
maintenance. This video can then be distributed to one or
more security/network operations centers and streamed
on demand to responders and emergency personnel in
the field.
A VMS is employed to provide recording, streaming,
switching and multiplexing functionality. It can normalize
streaming video from multiple sources into a common
format as well as provide recording and playback services.
It also functions as a video server by relaying video to
multiple endpoints, each with different resolution and bit
rate requirements.
VMS functionality increasingly runs as software on
enterprise servers instead of on custom embedded
hardware. A single server can handle the recording and
streaming tasks for 64 or more cameras, with video
stored on internal drives or on a storage-area network.
Management software typically combines a database
server and a Web server, which enables configuration and
monitoring over the network and notification to mobile
endpoints.
A medium to large deployment can involve hundreds if not
thousands of cameras distributed over tens or hundreds of
locations. Most security policies require video to be stored
for a week to a month, and some require it to be archived
for a year or longer. The operational and maintenance
costs over the lifetime of such a system can easily exceed
the upfront capital expenditure.
For illustrative purposes, letās examine a 1,000-camera
system spread over 10 sites streaming at 4Mbps per
camera. If recording is done locally at each facility, it
consumes 400Mbps on the LAN and 4.3TB of storage per
day per site. With a one-month retention policy, over a
petabyte of storage is needed for all sites. It is also likely
that monitoring operations are centralized in a security/
network operations center, which requires video to be
streamed to a remote site with dedicated WAN links at
hundreds of megabits.
Given these challenges, enterprises are forced to
compromise a great deal. One option is to limit video
surveillance to forensic evidence ā i.e., no active
streaming or monitoring, with recorded video reviewed
only after an incident occurs. Other options include
dropping the resolution and frame rate for video streamed
over a WAN, which makes it difficult to detect security
violations.
In short, the massive investment in security infrastructure
pays poor dividends because incidents cannot be
detected and intercepted as they are happening.
Fortunately, video analytics present a compelling solution
to this problem.
Video analytics addresses infrastructure challenges by
enabling content-aware storage and routing. The software is the equivalent of having a tireless, unblinking person watch each
camera, detect relevant events, and make decisions on what events to store and when to stream video. An
analytics-enabled VMS addresses the three big scalability
challenges of enterprise video deployments ā human
resources, storage and bandwidth ā more effectively and
cost-efficiently than a system without this capability.
Analytics serve as a force multiplier, freeing personnel
from continuous monitoring and eliminating the need to
hire additional staff even as the number of cameras grows.
The software reduces storage requirements by a factor of
100 by recording video only when events of interest occur.
It also reduces bandwidth requirements by a similar factor
by streaming video only to endpoints that have subscribed
to those events.
Most surveillance video is either monitoring normal,
routine activities such as people entering and leaving
a parking lot, or no activity, such as around a remote
fence line. Simple motion detection is sometimes used
to reduce the amount of video recorded or streamed, but
it is prone to false alarms and creates unwanted events.
Advanced video analytics can be configured to look for a
person loitering in a parking lot or crossing over a fence,
and only record and stream video when that happens. The
technology can also alert personnel to loss of video or
tampering.
Video analytics software is best integrated with the VMS at
each site. It intercepts the video feed from all cameras and
then analyzes live video in real time with minimal latency.
Events are stored in a database and posted to one or more alert consoles that have subscribed to those events. Video corresponding to those events is also streamed
to these consoles. In effect, video analytics serves as a traffic cop, interacting closely with the VMS. In most cases, an analytics enabled VMS can be deployed on existing
infrastructure with minimal changes.
Video analytics provide a win-win situation, by enabling security personnel to prevent crime instead of investigating it after the incident, and by allowing IT staff
to provide a compelling solution that is cost-effective to
deploy and maintain. It greatly reduces the operational
expense of a distributed video surveillance solution while
allowing centralized administration and monitoring. This
mature technology is transforming the way enterprises
plan and deploy IP video surveillance systems.
CheckVideo is the leader in intelligent video security solutions. Starting with breach detection solutions for airports in 1999, CheckVideo serves thousands of customers today with pro-active security solutions meant to stop crime and prevent losses. Its unique combination of AI-based
video detection along with the award-winning CloudVMS provides the most cost-effective,
extensible and complete video solution available.
CheckVideo has won over 10 awards and holds over 25 patents on video technology including detection, compression and transmission. All CheckVideo software is developed in Virginia, and supported by a team of experienced engineers.
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