IDLA represents a new paradigm for video surveillance, leveraging artificial intelligence and deep learning algorithms to perform previously labor-intensive tasks at an industry-leading 98% accuracy rate.
IDLA can be used for all types of security and life safety applications, and applied to surveillance systems installed for public safety, in schools, retail stores, traffic control infrastructure, hospitals and so on. IDLA accurately monitors images, events and scenes that are easily missed by human operators, and it enables smart searching with high accuracy and outstanding results. IDLA ensures personal safety and the protection of assets by enabling control room staff to respond to issues more quickly than ever before.
IDLA provides accurate event notification and filters out the frequency of false alarms associated with real-time video monitoring.
Object Detection (Intrusion, Loitering, People Count), Action Recognition (Fall Detection)
Public Safety, Traffic Monitoring, Manufacturing, Education, Retail
With IDLA, multiple camera images can be retrieved at the same time, enabling quick action in the event of an event.
IMF(Instant Meta Filtering) search, Smart Search, Person Match search
Retail, Government, Education
IDIS Object Detection technology allows operators to automatically identify and track target objects by using modelling technology that creates a fixed background in the scene, allowing the detection and monitoring of moving objects across the top.
In practice it can analyze loitering and trespassing, and handle people counting in both real-time video streaming as well as recorded footage.
Action Recognition is an AI technology that uses advanced automated algorithms to provide high accuracy and automated event recognition, self-learned from various cases.
For example, Action Recognition can spot a person falling over, in real-time, and trigger a notification. This ensures that critical events never go undetected and enables control room operators to initiate fast, appropriate responses to incidents.
IMF (Instant Meta Filtering)
As surveillance footage is recorded, the IDIS AI engine automatically recognizes objects, places, and movements and then extracts and stores metadata relating to every scene. This metadata provides classification, identity and context to video streams, allowing operators to organize, search and retrieve intelligent information from huge amounts of video footage quickly and easily.
IMF rapidly sorts through fine-grained meta-data - as easily as performing a simple text search – to locate a specific person or vehicle of interest across a site or even multiple facilities. In turn this reduces investigation time for often critical incidents from days and hours down to minutes.
IDIS Person Match technology that extracts the characteristics of a person in order to search for the same person or persons across single or multiple recorded video streams.
This allows users to quickly search vast amounts of video data to monitor and track people of interest, to reveal their behavior and movements over time, and to allow rapid investigation of incidents or suspicious activity.
The IDIS Deep Learning Engine is an artificial neural network that acts like the human brain, learning from experience. Out-performing human capability it can analyze vast amounts of data points taken from video footage across single or multiple cameras, covering an area, a site or multiple facilities simultaneously. This allows it to first detect and then identify an event or threat, while filtering out false alarms.
The industry’s most advanced and accurate AI engine
The IDIS Deep Learning Engine has been designed and developed in-house by our own team of AI experts using deep neural network technology to deliver industry-leading accuracy. Its capability has been proven in independent testing at live customer sites using high-quality video footage.
Learning from Big Data in Video
The IDIS Deep Learning Engine is constantly improving, with ongoing system development and big data learning - an evolution that started with the first generation in 2017 and has already progressed to our third-generation V3 engine, launched in 2019.
Today, the IDIS Deep Learning Engine is achieving 98% accuracy and outperforming other top-tier surveillance vendors.
Up to 98% accurate
IDIS has developed its Deep Learning Engine specifically for security and life safety applications.
The engine has evolved using big data from surveillance footage where security and safety breaches have occurred - events such as intrusions or people having slips, trips or falls. It has also learned by analyzing data from video streams that capture the behavior of people and the movement of vehicles and objects.
Accurate, fast, simple, and scalable, IDIS Deep Learning Analytics (IDLA) powered by the IDIS Deep Learning Engine, offers agile object detection and classification of people, cars, and bicycles, intrusion detection, and loitering detection—all adapted to fit a 16:9 ratio.