Facial Recognition Solution
DallabAI is specifically designed to integrated systems by extracting faces in real time from existing video surveillance systems and matching against a watch list of individuals. When the system identifies an individual of interest from the watch list, it raises an alert, so appropriate actions can be taken rapidly to reduce the risk of public safety threats.
Independent testing confirms that DallabAI technology provides the fastest, most accurate matching capability and is the most resistant to variants in aging, race and pose angle.
DallabAI Watch helps reduce the risk of security threats by integrating face matching technology with video surveillance input while checking individuals against known photographic watch lists, and producing real-time alerts. High performance matching capability with multiple camera feeds. Detection of persons of interest on premises in real-time. Real-time alerts to be acted upon as necessary. Suitable for the detection of both undesirables and VIPs. Ability to process live and archived video images.
The DallabAI Watch application is a Web-based thin client with an easy-to-use user interface. It is unobtrusive and requires no operator interaction. The application can be easily customized and integrated into existing surveillance systems and operational processes.
DallabAI technology’s strength lies in its tolerance of poor quality. Highly compressed surveillance videos and images, previously considered of little to no value, are now usable evidence and leading to higher rates of positive identification. With its proven ability to match low resolution facial images, DallabAI technology outperforms all other face recognition systems in matching accuracy. While searching of latent fingerprints at crime scenes is standard, DallabAI facial recognition technology can now positively identify latent photos with high degree of accuracy.
License Plate Recognition Solution (LPR)
License Plate Recognition (LPR) technology is used to help detect, deter and disrupt criminality at a local, force, regional and national level, including tackling traveling criminals, Organized Crime Groups and terrorists. LPR provides lines of inquiry and evidence in the investigation of crime and is used by law enforcement agencies throughout Peninsular Malaysia and East Malaysia (Malaysian Borneo).
As a vehicle passes an LPR camera, its registration number is read and instantly checked against database records of vehicles of interest. Police officers can intercept and stop a vehicle, check it for evidence and, where necessary, make arrests. A record for all vehicles passing by a camera is stored, including those for vehicles that are not known to be of interest at the time of the read that may in appropriate circumstances be accessed for investigative purposes. The use of LPR in this way has proved to be important in the detection of many offenses, including locating stolen vehicles, tackling uninsured vehicle use and solving cases of terrorism, major and organized crime. It also allows officers’ attention to be drawn to offending vehicles whilst allowing law abiding drivers to go about their business unhindered.
LPR cameras from police forces submit copies of vehicle registration marks to the National LPR Data Center (NADC) daily. LPR data from each police force is stored together with similar data from other forces for a period of two years.
We have clear rules to control access to LPR data to ensure that access is for legitimate investigation purposes. Members of staff only have access to LPR data if it is relevant to their role and the majority of those who have permission may only do so for a maximum period of 90 days from the date it was collected. Some staff are authorized to access data for up to 2 years subject to authorization of a senior officer.
Searches of LPR data can confirm whether vehicles associated with a known criminal has been in the area at the time of a crime and can dramatically speed up investigations.
In addition to being mounted within police vehicles, LPR cameras within police forces are used at fixed locations where they will help to detect, deter and disrupt criminality. In line with national policy, we do not disclose details of our fixed locations as this information is likely to be of benefit to offenders and if known could reduce the value of LPR to policing.
Behavior Recognition Solutions
Dallab is an industry leader in machine learning and the creator of DallabAI, the first Cognitive Neurolinguistics AI System. This multi-sensor, data-fusion software platform leverages machine learning to autonomously learn the normal patterns of behaviors at extreme scale to identify anomalies or potential system threats in real time. Our focused applications enable solutions for Video Analytics, Supervisory Control and Data Acquisition (SCADA), Cyber Security, and other sensory data types.
DallabAI-S provides real-time monitoring of the industrial environment, offering operational intelligence to help prevent safety and loss issues as well as identify opportunities for increased operational uptime.
DallabAI-F augments existing solutions by recognizing and warning against pending upset conditions.
DallabAI-V monitors thousands of cameras at once, learns normal vs. anomalous behavior, and issues real time alerts that enable security personnel to hone in on potential threats as they happen.
DallabAI-C adapts and evolves automatically, allowing the technology to detect anomalies that might lead to cyberattacks or potential data breaches.
DallabAI’s advanced, cognitive neurolinguistic solution autonomously learns the normal patterns of behaviors across massive amount of sensors and sensor types. Its patented, adaptive algorithms provide the “tap on the shoulder” insights to analysts and operators when anomalies occur. DallabAI enables organizations to realize and optimize the values of Big Data Analytics and the Internet of Things.
Dallab Launches New Brand, Bringing to Market Powerful Multi-Sensor Fusion Technology That Learns Anomalous Behavior and Alerts to Security, Operational Threats.