three points

POINT-1-
Various anomalies that are “unusual” can be detected
"icetana" autonomously learns the normal state from surveillance camera images to detect various abnormalities that are "unusual". Security guards can judge the situation from the detection details and then decide whether or not to respond.

POINT -2-
No need to change settings during operation
"icetana" learns the state of each camera over the past week as the normal state for each day of the week and time period, and automatically updates it. It does not require complicated setting changes and can flexibly respond to changes in the environment of the facility.

POINT -3-
No need for large-scale construction
Existing cameras can be used. There is no need for large-scale preparations or costs when changing or adding cameras, and hundreds of units can be operated. *Some cameras cannot be used. Please contact us for details.

Efficiency and sophistication of facility security

1. Efficient discovery of anomalies from multiple cameras
icetana's original video display function "Real-time Live Wall" displays only the images in which anomalies are detected from multiple surveillance camera images on the monitor in real time. This allows the observer to handle a large number of surveillance cameras.

2. Optimize security resources
It is no longer necessary to supplement the video confirmation of a huge number of cameras with patrols and guards, and it is possible to place security guards intensively at the necessary time and place.

3. Improving ability to detect and respond to various abnormalities
In the case of humans, it takes experience to notice “unusual” situations. Since "icetana" can support the awareness of abnormalities even by non-experts, it prevents personalization and improves the quality of security.

Features of icetana

1. Rapid deployment
It can be installed on-premises (negotiable if a cloud environment is desired). Additionally, all operations can be completed on a web browser.

2. Supports fall detection
It supports the detection of falls, which are the most common cause of accidents in commercial facilities.
*Consumer Affairs Agency: https://www.caa.go.jp/policies/policy/consumer_safety/caution/pdf/safety_caution_161207_0001.pdf

3. Reporting the incident
You can quickly check abnormalities that occurred in the past, and you can also share videos. Reports can be automatically created using ChatGPT integration.

4. Continuous autonomous learning
Learn in the first 24 hours and optimize in a week. We will continue to make improvements for each camera.

5. System coordination
It is also possible to link with your current VMS (Video Management System) or cloud recording service. (Can be linked with ArgosView and Safie *As of August 2023)

Anomaly detection details

1. Unusual “position”

An abnormality is detected when a person, vehicle, or motorcycle is in an area where it should not be.

<Detection example>
・Staying due to eating/drinking/photography or nuisance
・Dangerous acts (children's mischief, delivery on different routes)
・Intrusion into partitions/plants
・Smoking, cigarette littering
・Movement overcoming measures
・ Violation injection, bicycle parking
・Passengers on roadways and vehicles on sidewalks

2. Unusual “number”

Abnormality is detected when the number of people, vehicles, and motorcycles is abnormally larger or smaller than usual.

<Detection example>
・A nuisance such as hanging out, drinking alcohol, or taking photos without permission
·Traffic jam
・Violation of number limit
・Protest
・Using an emergency exit

3. Unusual “speed”

Detects people, vehicles, and motorcycles that move faster than normal as anomalies.

<Detection example>
・Dangerous work (such as unreasonably fast transportation)
·skateboard
・Vehicle slip
・Cars that are speeding
・Bicycle/motorcycle traffic violations

4. Unusual conditions “by time of day”

Anomalies are detected when people, vehicles, or motorcycles are present during an unexpected time period.

<Detection example>
・Nighttime hanging out/drinking
・Intrusion after closing
・Use after hours
・Intrusion into the partition area

5. Unusual “movement in direction”

When a person, vehicle, or two-wheeled vehicle moves in an unusual direction, it is detected as an anomaly.

<Detection example>
・Reversing on the escalator
・Reversing the escalator
・Vehicle/bicycle reverse/slip

6. Human fall

An abnormality is detected when a person lies on the floor for 3 seconds or more.

<Detection example>
・Falling/injured person
・Maintenance worker lying face down
・The child is lying down
Violent behavior leading to falls

7. Generation of fire and smoke

An abnormality is detected when fire or smoke is detected.

<Detection example>
・Ignition and smoke from equipment

8. Retention

Detects when people are staying.

<Detection example>
・A person who stays in the same place for a certain period of time
・Crowds at the entrance/exit of the facility
・Gathering of smokers

9. Person/vehicle count

Displays a count-up of the number of people and vehicles detected per hour/day for each camera.

<Example of use>
・Understanding congestion times and locations
・Understanding traffic volume around the facility
・Obtain marketing data and provide it to tenants

10.Heatmap

Displays the relative value distribution of the residence time/number of people/vehicles/bicycles within the field of view of each camera.

<Example of use>
・Understanding traffic conditions and key areas
・Understanding residence time
・Review and strengthen security system
・Improvement of facility layout

11. Leaving luggage unattended

Detects when luggage (suitcase or backpack) is left unattended for a certain period of time.

<Example of use>
・Prevention of theft
・Reducing potential risks by identifying suspicious objects

Image of system usage

icetana displays only events judged to be abnormal by LiveWall™ on the monitor in real time. Detected images clearly show the reason for the detection and the location of the detection, so it is possible to quickly determine whether there is an abnormality that should be addressed.

In addition, when reviewing detected anomalies, it is possible to filter by detection target, detection reason, and camera, making it easy to find specific anomalies. The video can be downloaded on the spot, and can be shared and reported immediately.

Usage example

Flow until introduction

STEP1. Explanation of “icetana” and survey of current situation
We will explain what can be achieved with "icetana". If you wish to make a detailed proposal, we will investigate the placement/angle of view of surveillance cameras, the current security system, etc.

STEP2. Proposal
We will inform you of the expected cost-effectiveness along with proposals such as quotations, specifications, and installation schedules.

STEP3. System procurement and construction
We will procure the hardware necessary for the demonstration experiment and build the engineering.

STEP4. Demonstration experiment
We will help you understand the usefulness of "icetana" in the field, and will support you by proposing and implementing security operation efficiency.

STEP5. Production operation, post-operation support
We will conduct regular hearings about the effects and issues after the introduction, and support you to maximize the effects of the introduction.

Inquiry

icetana has a lot of adoption results in Japan. Contact us now if you have a problem with facility security.