Among the many improvements in surveillance technology, several companies specifically pointed to artificial intelligence (AI) and improvements in video analytics as being key developments in improved seaport surveillance.
“The continued development of artificial intelligence algorithms, especially for video surveillance, will allow ports to more effectively monitor ‘soft events,’ whereby the event does not entail an intrusion, but rather a set of suspicious actions that may indicate threat, vandalism or other form of security breach," said Eric Olson, VP of Marketing for PureTech Systems
. "The advancement of more intelligent video forensic algorithms, to provide quicker and more specific searches across video and other security sensors, will also be a great help to ports to speed up the investigation process and provide more accurate search results.”
Jumbi Edulbehram, Regional President of Americas at Oncam
, explained that AI, machine learning and video analytics are combining to create one of the most beneficial aspects of video surveillance systems: proactivity.
“These technologies allow the system to pick up on unusual or suspicious activity before an incident occurs, which is crucial for seaport security. Machine learning and AI probably have some of the most promising advancements for transportation, namely airports and seaports because they make existing applications such as facial recognition much more accurate,” Edulbehram said. “They also help identify anomalies which can indicate a security threat in environments in which traditional analytics fall short due to the complexity of the scenes. Being able to detect and mitigate a threat in advance can save countless lives and property in an environment where so many important pieces are gathered.”
Mark Brown, Director of Research and Development for Security at FLIR Systems
, believes developments in deep learning/CNN (convolutional neural networks) and their contributions to improved video analytic performance hold a lot of promise for the seaport environment.
Brown identified several types of video analytic functions that are improving seaport surveillance security, such as license plate recognition (LPR) and optical character recognition for the control of vehicular and container traffic entering, leaving and within the facility; object tracking analytics for forklift, truck, crane and container movements; and facial recognition and people counting analytics are applicable for many seaport facilities servicing cruise ships.
How PSIM makes monitoring seaports more effective, efficient
To properly surveil seaports, many disparate systems have been used over time. Erez Goldstein, Director of Global Marketing at Qognify, explains how using a PSIM to integrate these systems can create a more effective, efficient system.
Seaports are both sensitive in terms of their operations and unique in terms of their structure — its open environment to the sea makes it hard to close by usual means, as well as the high volumes of employee and visitor traffic. As such they have invested heavily over time in safety and security systems including: video surveillance, video analytics, intruder and hold up alert systems, access control, sonar, radar, automatic identification system, and GPS, as well as the increasing use of drones, according to Goldstein.
“With so many disparate systems in operation, the big challenge (and opportunity) is to integrate them in a way that delivers a common operating picture that security teams can use to proactively monitor, manage and maintain the security of the port, its people, vessels and cargo,” he added. “However, seaports have also realized that while a single centralized platform can help to significantly reduce exposure to risks and improve incident management, it can also make them more operationally efficient.”
Take for example, Naftoport — Poland’s only oil transshipment port, where it is estimated that just one day of not operating would result in a loss as high as US$200,000.
“The seaport is using our PSIM solution, Qognify Situator, to integrate its diverse array of security systems and sensors. This includes 21 channels of our intrusion detection video analytics technology for both analog and infrared,” he added.
In doing so, Naftoport has been able to automate 40 day-to-day security procedures and implement a response plan that helps its security teams to pre-plan, coordinate and manage the response to emergency situations in real-time, as well as effectively manage routine security operations.
Edge computing and cloud management could play key roles in seaport surveillance, according to Steve Hu, Product Manager of Merit LILIN
. This is due to their maintainability and construction cost.
Seaports are vast and require a large number of cameras to adequately monitor the entire premises. This is where edge computing and the cloud could help seaport security operators manage systems more efficiently.
“Without edge computing, a great burden will be imposed on the central management system. Also, due to the huge size of the areas needed to be covered, cameras are usually installed in places that are difficult to reach. Cloud management could make maintenance much easier and reduce relevant costs,” Hu said.
In the past, edge computing and cloud management were limited by poor computing performance and limited network connection capability. However, these two issues are now more stable and reliable, making it possible to upgrade and operate surveillance systems in a more efficient way.
“In terms of cloud management, IPv6 was the key to implement a firewall-less or NAT-less remote-control system. But now LILIN has developed a remote management system — DeviceHub,” Hu explained. “No more complicated network settings should be made, just plug and play. That can be seen as an important milestone in breaking the limits of existing network conditions.”