Choosing a campus security camera system is filled with questions. We relied on our sister site, Campus Safety, to provide some key answers.
Question 1: How does the security camera perform in low-light conditions?
Campus security camera systems should always be active. Getting accurate and useful images at night has previously been a challenge for cameras, but technology has improved since the narrow and fuzzy green images of the past.
While IR illumination can help, illumination distance is usually limited and narrow compared to the camera’s daytime field of view. For high-quality, low-light camera performance, there are three important elements to consider — the camera lens, the sensor and image processing.
- The Lens: For low-light conditions, a lens must be able to deliver as much light as possible from the environment to the sensor with minimum loss. A lens should have a small F-stop number (aperture opening) to gather all available light. Cameras designed for video surveillance typically use IR corrected lenses since CMOS sensors are sensitive in the infrared range and can look out of focus or softer in IR light. IR corrected lenses allow for the best day/night focus and produce brighter images with lower F-stop values.
- The Sensor: After the lens, it is necessary to have a high-sensitivity sensor that reacts well in low-light environments. Larger sensors and larger pixels exhibit the best low-light sensitivity as they have a greater surface area per pixel, so more light is able to affect each pixel. The best sensors preserve color detail at night. Look for ½-inch sensors with a high signal-to-noise ratio (SNR).
- Image Processing Technology: The SNR is high during the day, so any sensor noise is almost impossible to detect. At night, when the sensor gain increases, sensor background noise also increases. During amplification, any noise contained within the image signal is amplified proportionally, so less light always equals more noise. This noise can be reduced through proper use of image processing technology. The way a camera handles the noise inherent in its sensor is important when designing for low-light environments, so it’s important to evaluate cameras in worst-case environments, such as low-light.
Question 2: Are built-in analytics available?
Perimeter fencing might be impractical and send the wrong message to students, patients, visitors and staff, so monitoring access to the campus, particularly through non-approved routes, is essential.
Built-in camera analytics (on the edge) enable staff to receive real-time alerts and mark events should an investigation be necessary. More than simple motion detection, analytics should include activities like line-crossing, loitering and tampering.
Using in-camera analytics significantly reduces the cost requirements associated with server-side analytics.
Coupled with a capable video management system (VMS), security and administrative staff can receive real-time notifications on their computers or their phones when an incident happens without having to physically monitor the system 24/7.
Until recently, analytics that triggered based on motion events, such as leaves blowing in the wind or a plastic bag drifting by, were susceptible to false positives.
With today’s artificial intelligence (AI)-based cameras, powerful object recognition algorithms all but eliminate these problems since these cameras can detect people and vehicles as well as colors and other traits, while ignoring non-important motion such as rain and wind.
If you are looking for reliable and powerful analytics to assist in notification and tagging events of interest, it’s worth looking into the new breed of AI-assisted cameras.
Question 3: What about sound classification and sound threshold alerts?
It’s important to be notified immediately when glass is smashed and a building is in the process of being burglarized.
If a camera with a microphone can detect and correctly identify the sound of glass breaking, then it’s a perfect complement to any security system and can help reduce overall costs of installing purpose-built glass break sensors at every point of ingress.
Gunshots, screams, explosions or even just noise going beyond a normal threshold can all be detected by modern built-in camera sound classification technology. Audio analytics can quickly alert security staff, which can dramatically shorten response times to incidents.
Audio-derived data also provides a secondary layer of verification that an event is taking place, which can help prioritize responses from police and emergency personnel.
With many state laws governing audio recording, having audio analytics on the edge overcomes legal challenges as it never passes audio outside of the camera. The result of audio analytics processed at the camera is simply an event message saying a certain type of sound was identified.
Processing audio analytics in-camera provides excellent privacy since audio data is analyzed internally with a set of algorithms that only compares and assesses the audio content.
Processing audio analytics on the edge also reduces latency compared with any system that needs to send the raw audio to an on-premises or cloud server for analysis.
Question 4: Does the security camera support specialized hallway fields of view?
There are plenty of hallways to cover in campus security.
In a vertical shaped environment, such as corridors, hallways, tunnels or aisles, traditional horizontal shaped videos focus on unnecessary edges of the area, causing bandwidth and storage waste. By utilizing a hallway view mode, 3:4 and 9:16 vertical aspect ratios can be created (versus traditional 4:3 and 16:9).
Vertically oriented video maximizes image quality in narrow locations. Picking a camera with a lens that can be configured for hallway views is an important consideration for schools and universities.
Question 5: Is privacy masking available?
Privacy will always be an important consideration with security systems and putting measures in place to ensure it builds trust and confidence.
Since cameras can sometimes see more than we want them to, it’s very useful to select cameras that can mask out certain areas, such as doors to restrooms or other personal spaces so that privacy is maintained at all times.