You could be forgiven for thinking spatial intelligence is a purely psychological phenomenon.
Commonly defined as the ability to generate, retain, retrieve, and transform well-structured visual images, spatial intelligence as a quality or trait has almost exclusively been applied as a human characteristic.
A key protagonist in this field is Howard Gardner, the Harvard psychologist who outlined his theory of multiple intelligences in 1983.
He outlines eight strands of intelligence, one of which is spatial. Gardner identifies people who have strong spatial intelligence as typically good with directions and maps, charts, videos and pictures, commonly associated with professions such as architecture, art and engineering.
While Gardner’s theory has been subject of rigorous academic debate, in today’s world the concept of spatial intelligence is increasingly being applied to physical and technological contexts.
This is clearly the case in the physical security domain, and for good reason.
There are obvious parallels from a definition perspective – the ability to generate, retain, retrieve, analyze and transform well-structured visual images is fundamentally what effective video surveillance is all about.
The key question, therefore, is how can the spatial intelligence of video surveillance systems be enhanced?
Let’s take a crowded train station as an example. The priority for security operations here is to ensure the safety of passengers, staff and vendors at the platform edge and inside and outside the venue, a complex task given the size and complexity of the space to be monitored.
Cameras and sensors are one way of constantly monitoring events, but it is near impossible to cover all blind spots without an unviable amount of hardware and personnel being deployed in every corner of the stadium.
The answer to improving stadium spatial awareness, therefore, is software.
By fusing disparate information gathered by multiple cameras and sensors, you will be able to see far more and identify trends and patterns – to cite the commonly used sporting phrase, the team is greater than the sum of its individual parts.
Spatial intelligence, in this sense, has been limited to a human’s visual and spatial ability as per Gardner’s theory. Now, thanks to the aid of technology, our understanding of spaces are enhanced beyond anything an individual mind could process.
Key data points such as access control, video surveillance, and WiFi can be joined up by AI-powered solutions to provide real-time predictive analytics and help prevent incidents like bottlenecks or overcrowding.
In other words, spatial intelligence can be viewed as an approach to physical security that allows its operators to obtain, manage and analyze data in a single platform, unifying data from information silos to facilitate better informed operational decisions.
LiDAR (3D imaging) technology has a crucial role to play in presenting this enhanced spatial intelligence picture.
By fusing video surveillance and 3D together in a single platform, higher quality and more accurate data can be leveraged to generate superior spatial intelligence – packed crowds can be dissected with pinpoint precision and accurate safety decisions made at the platform edge, helping to ensure safety and monitor the flow of people in stations, stadiums, and other settings.
Through our Fusion camera solution, Oyla helps to deliver enhanced spatial intelligence. Our LiDAR enhanced video systems provide the insight needed to inform and enable optimized security in a range of physical environments.