Ultra smart video analytics
By using iSentry:
Reduce video archive
Increase situational awareness
Increase operator coverage effectiveness
Improve ratio of operator to feeds
Efficiently use Bandwidth
Harness the power of Self learning
Deploy and train with ease
Monitor areas with high motion
Monitor for unusual behavior in:
Busy shopping centers,
Military bases and
Any high motion environment
under CCTV surveillance
an automated (ultra smart) video analysis system, uses Artificial Intelligence
algorithms to learn the normal behavioral patterns of objects captured on a
CCTV video camera. When an object displays activity that does not fit the model of normal behavior, the
system highlights it as unusual and performs a number of automated responses. iSentry transforms a se-
curity environment from passive to active
This story shows the difference between historic rules based analytics and our ultra smart algorithm based
“A government department overseas was evaluating their top three video ana-
lytic bidders. All three companies were monitoring the same stretch of highway using feeds
from a shared camera. Two of the companies, Company A and Company B were using rules
based video analytics software and company C was using iSentry algorithm based smart ana-
Company A and B were doing a good job of monitoring the highway. They had defined various
rules like zones with exclusion, directional and motion detection. In these areas they per-
formed well, as did the self-learning iSentry system.
The tests continued and all three companies competed until a light aircraft needed to execute
an emergency landing on the monitored highway. The skilled pilot lined his descending air-
plane up and landed it between a gap in the traffic on the highway matching speed and direc-
iSentry immediately alerted the operator and action was taken to safely secure the highway.
The other two companies using rules based software, did not alert on the aircraft as it
dropped out of the sky and landed on the highway. This failure to alert was because the pilot
was intrinsically behaving within the parameters defined in the rules matrix, namely: being
within lane, travelling in the correct direction at the correct speed and not stopping in an un-
authorized area. To iSentry on the other hand, it was clear that a vehicle descending from the
sky did not fit with a normal behavioral pattern and alerted accordingly. It is needless to say
that Company A and B didn’t get the contract. iSentry had effectively identified the unusual
behavior and saved the day.
In various degrees of sophistication rules based systems use four basic variables and then apply these in
various module configurations to try to solve common surveillance threats. Rules are set according to:
duration, direction, speed, size and location of an expected threat relative to the cameras view.
Rules are not perfect because of two vital concepts that must be understood:
Only the rule is monitored, so if something out of the ordinary happens, and a rule was never created
because that item was unforeseen, then the rules based system will never notice it.
One rule set, one camera. When a set of rules to identify loitering is applied to a camera, it is not possi-
ble to apply an additional rule set like trip wire as the rules conflict with each other.
The trouble is that all this time and money has been poured into a system to trigger when motion occurs.
What happens when there is a large amount of motion? Or frequent motion or constant motion like in a
shopping mall, mine or military base? In constant motion environments rules based analytics fail. On the
other hand, iSentry excels with high motion environments, because of its
ability to detect unusual behavior.
Rank these video surveillance challenges by placing a number next to each point :
Storing vast quantities of video data
Low bandwidth environments make the transfer of digital video expensive/unreliable/unavailable
A high camera to operator ratio is needed to be cost effective (but this impacts on quality)
Human operators are unreliable and miss much footage due to a loss of situational awareness
Video feeds are not monitored effectively because humans lose concentration after 25 minutes
Human operators get distracted by attending to one incident while other incidents go unnoticed
Low skilled/low intelligence operators struggle with complex rules based systems
The solution is to use iSentry ultra smart video surveillance.
iSentry has been leading the market since 1999 with the skills needed to improve your surveillance:
IT hardware and software specialization on video camera and security infrastructure.
Artificial intelligence algorithm driven video processing software of which aspects have been tested
in theatres of war.
Vast experience in installation and technical support of risk mitigation systems like iSentry ultra
smart video analytics
With its unique artificial intelligence algorithm, iSentry can monitor every moving object in a camera’s
view. From this it builds a model of behavior, which it considers normal. When an object behaves in a way
that does not fit the normal model, iSentry identifies it as unusual.
iSentry has the power to solve the biggest ground based video surveillance problems:
Detect unusual activity: iSentry can filter out over 95% of normal motion video and only present unusual
activity to operators. It provides excellent & unrivalled situational awareness and the ability to achieve
an effective immediate response
1 operator to 100 cameras: iSentry handles large numbers of cameras by scheduling interesting video,
allowing the operator to shift priorities to other tasks without missing critical incidents.
Highly effective video storage: iSentry has the ability to store video from variable events at different den-
sities. This allows the bulk of unnecessary video to be stored at an efficiency according to its im-
portance, ultimately resulting in massive storage savings without compromising surveillance needs.
Reliable indoor and outdoor left-object detection: Realizing that on occasion it is what doesn’t move ra-
ther than what moves that is important, iSentry can reliably detect small objects left in busy outdoor
areas (or indoor). iSentry can cope with almost all weather conditions, rain, hail or shine.
Video Trip Wires activate alerts based on a person crossing a threshold. Video trip wires include location,
direction, size and speed options which are ideal for no traffic areas like ceilings and perimeter fences.
Digital Video Recording and simple playback: iSentry also enables normal video recording and playback.
iSentry learns normal behavior by observation and detects unusual activity.
By using iSentry:
Reduce video archive: by using iSentry to determine the importance of the motion it is viewing, at
which point it is broken down to an alert, a true motion, any motion and no motion. These differ-
ing importance layers are customizable per camera and are saved at resolution and quality appro-
priate to their importance, thus allowing highly effective storage capabilities.
Increase situational awareness: While viewing 100% of video feeds, iSentry presents the important
parts of the video to the operator. This 98% reduction in unnecessary video puts the operator in a
position to be able to attend to high importance knowledge. The reduction leads to better situa-
tional awareness because there is no operator information over load.
Increase operator coverage effectiveness: Using iSentry’s easy to understand and operate user inter-
face the operator will attend to every single incidence as the clips can be stacked and attended to
on priority- Never miss an alert.
Improve ratio of operator to feeds: While 60 camera feeds to one operator in traditional settings
leads to 98% of video being completely ignored. Using iSentry the operator can manage 100 cam-
eras, knowing that 100% of each video is “viewed” and attended to by iSentry. The operator simp-
ly views the 2% identified by iSentry as unusual and needing human action.
Efficiently use Bandwidth: iSentry does its work of screening 100% of video before its transmitted.
This has the incredible efficiency of cutting down on 98% of video which needs to be transmitted,
so operating in low bandwidth environments is thus feasible. Intelligently consume in high speed
and high bandwidth environments. By iSentry screening video before it’s transmitted, you can rest
assured that the work is carried out at full resolution and not compromised in any way.
Harness the power of Self learning: iSentry is a self-learning artificial intelligence algorithm. This
means that there is very little setup and no need to have programmers and engineers spend hours
configuring rules. iSentry constantly learns from its environment and detects unusual behavior all
on its own.
Deploy and train with ease: iSentry is highly flexible compared to rules based video analytics systems.
It is easy to implement and easy to manage with low administration needs. Operators with low
skills/intelligence are able to grasp the user interface with ease.
Monitor areas with high motion: Traditional video monitoring devices are built to react to motion but
are unable to reduce and analyze video feeds where constant motion is present. iSentry uses its
self-learning ability to effectively monitor for unusual behavior in busy shopping centers, airports,
military bases and mines, any high motion area.
Next step towards solving your surveillance challenges
Refer back to your list of top ground based surveillance challenges. Was it a case of too much video not
enough eyes? High motion environments dazzling operators? Too much video to store/to view/to trans-
We are confident that with your operators easily using iSentry ultra smart video analytics you will solve
your ground based surveillance challenges. To see a demo of iSentry or to learn about our product mod-
ules contact us: