The modern security system of cargo warehouse needs to go beyond pure video surveillance. The video monitoring system driven by real-time and artificial intelligence (AI) can automatically monitor and send an alarm when abnormal conditions occur. This enables the monitoring personnel to take actions quickly and effectively to avoid losses. In addition, the collected data can also generate many insights for improvement.
These are the main motivations for a large global warehouse and logistics operator to seek to update the existing monitoring system, which monitors a distribution center of 93000 square meters.
The distribution center is staffed by 1200 long-term employees and 2000 seasonal workers to handle 150000 orders every day. Considering this scale, a large number of cameras have been installed, which in itself has brought huge challenges to the monitoring work. In addition, the existing closed-circuit television system is only reactively used for post-event analysis.
About 227 incidents were discovered every semester. Therefore, it is necessary to shift from a passive CCTV network to an active CCTV network to highlight events in real time. Another task of improving the monitoring system is to make better use of the CCTV network to meet the organization's risk management strategy.
Self-learning AI system
Icetana's self-study AI driven solution meets these requirements and is distributed by Macnica ATD Europe in Europe.
Icetana is a global SaaS software company that provides video analysis technology, aiming to identify abnormal events and unexpected behaviors in real time for large-scale monitoring networks. Its software is integrated with the existing video management system and IP camera, and uses artificial intelligence and machine learning technology to learn and filter conventional motion, only displaying abnormal behavior. This enables operators to automatically give priority response to precursor activities and current events.
Using artificial intelligence and machine learning technology, icetana software learns and filters out regular movements, and only displays unusual behaviors. Icetana technology has been widely implemented in private, public and government industries in more than 40 locations on four continents. For more than 11 years, icetana has helped customers utilize rich data streams from their existing security networks to improve situational awareness and deeper operational insight.
By automatically determining normal and abnormal events in a specific environment, the plug-in greatly facilitates anomaly detection after being easily installed into the existing video management system. Icetana's software provides indicators to speed up the review of camera images and performance to optimize security assets and ensure high-level event detection.
After integrating Icetana's AI solution into the warehouse's video surveillance security system, people noticed that it had some positive effects on the efficiency of the warehouse security system. Up to 140 unusual or abnormal events were automatically identified and reported to the warehouse's loss prevention department, which means an increase of 1500%. 65% of these incidents are related to health and safety practices, which need to be highly monitored. These incidents include, among other things, violations of directional stairs and walkways, uncontrolled rolling cages, non-compliance with forklift safety regulations, or smoke emissions.
The event report in the warehouse has been greatly accelerated, and the image review has also been accelerated. Under the Icetana solution, a single camera can review 24 hours of video in less than 2 minutes. Therefore, when evaluating the recorded video sequence, the manpower saved is proportional to the time saved; Moreover, the visual fatigue of security personnel who usually monitor many cameras has also decreased.
