Your Security Camera Just Got a New Job

Since their introduction into the mainstream half a century ago, smoke detectors have saved countless lives and prevented untold amounts of property damage. But despite their obvious utility, these little devices do have one big flaw: they need to be close enough to the source of the fire to detect its smoke. In some cases, it can take a significant amount of time for smoke to reach an alarm. Time is critical in any structural fire, and the time between when a fire starts and when a smoke detector alarms can be enough for the blaze to get completely out of hand.

Smoke detectors may be nearly ubiquitous in today’s world, but in recent years another device has become nearly as common. Security cameras have become so inexpensive, small, and easy to install that more than half of all homes in the US now have at least one. Engineers at New York University recognized that this massive base of installed hardware presents an opportunity to detect fires quicker than existing systems. Using computer vision, they have shown that a security camera can detect even a distant fire in a matter of milliseconds.

A vision for early detection

The project, led by the NYU Fire Research Group at the Tandon School of Engineering, uses artificial intelligence (AI) to analyze video streams in real time. Their system can recognize signs of fire at a rate of just 0.016 seconds per frame, which is literally faster than the blink of an eye. Unlike standard smoke detectors, which require significant smoke buildup to trigger, this approach can identify the earliest stages of a blaze before it grows uncontrollable. Moreover, a single camera can monitor an entire room, hall, or outdoor space.

To avoid false alarms the team built an ensemble system combining multiple AI models. Only when the algorithms agree does the system confirm a fire. The models were trained on a custom dataset that included all five classes of fires recognized by the National Fire Protection Association, ranging from electrical faults to cooking accidents. The result is a detection accuracy above 80 percent, with temporal analysis boosting reliability further by distinguishing dynamic flames from static, fire-like images.

Expanding the scope of safety

Because the technology can run on ordinary CCTV infrastructure, it could be rolled out quickly in homes, offices, and public spaces without major upgrades. Integrated with drones or unmanned vehicles, it could scan for wildfires in remote areas, buying valuable time for containment and evacuation. Firefighters themselves could also benefit from helmet- or vehicle-mounted cameras equipped with the system, giving them better situational awareness and safer ways to locate blazes.

Beyond fires, the team believes this approach could extend to other emergencies, from security threats to medical crises. We already have millions of cameras watching over us, so why not let them pull double duty to better protect us?