Canon goes beyond surveillance with versatile camera, LiDAR solutions
Possibilities include analytics, fall detection, enhanced surveillance, and more.
What can you do with a bunch of digital cameras? A lot, it turns out - analytics, fall detection, enhanced surveillance, and more.
I've always been fascinated with networked IP cameras, the type which enterprises and facilities deploy for surveillance and safety.
I thought I knew it all until I stopped by Canon's booth at its recent Think Big conference. Well, it opened my eyes to the latest possibilities.
Beyond simple surveillance
A problem faced by many firms is the consolidation of surveillance footage with other key data or data points into a single screen.
- Air quality.
- Employee count.
- Live video footage.
- Recent badge swipes.
The DS Box is a compact, edge computing device that runs Milestone software to meld everything above into a single dashboard.
It can be configured to run AI models, too!
Advanced insights
By pairing traditional cameras with LiDAR imaging systems, it's possible to offer far more advanced insights.
- Age.
- Gender.
- People tracking.
For instance, I heard how Universal Studios leveraged (anonymous) people tracking to shorten waiting time by matching crowds with precise staffing levels.
GenAI can also be used to generate additional insights from the analytics, or to identify areas with lower footfall in train stations or retail malls.
Photo Captions: (Left to right, top to bottom) Canon's showcase. A single dashboard for everything. Universal Studios use case. Video camera (bottom); LiDAR (top). A uHoo air quality monitor. The incredibly compact DS Box.
Diverse use cases
Globally, it turns out Canon solutions have made its way into these places such as:
- Subways.
- Retail shops.
- Amusement parks.
- Expressway tunnels.
- Educational institutions.
So yes, cameras are no longer used simply for mundane surveillance.
Putting everything together
With a deep understanding of use cases, a tech-agnostic approach, and its own core technologies, I was told that all kinds of solutions can be customised.
Some examples:
- A local educational institution wanted to determine whether students are conforming to dress code regulations, footwear-wise, using AI.
- Fall detection at nursing homes, or to sound an alert should residents attempt to leave designated zones - for those with dementia.
- For use in preschools to monitor existing video management system (VMS) feeds for potential abuse using a specially trained AI model.
What are your thoughts about the above?
