Camera intelligence · Feature guide

AI CCTV camera night vision

Night footage can look bright yet contain too little usable detail. AI image processing can reduce noise and improve a difficult scene, but it works with the light and detail the camera actually captures. A good night-view demonstration should include movement, not just an empty entrance.

Illustrative comparison of noisy and clearer footage of the same Indian factory gate at night
AI-generated illustration of ai-enhanced low-light imaging. The scene and overlays explain the concept; they are not a PGAK screenshot or measured result.

How it works

Use AI image processing to reduce noise and improve detail in difficult lighting.

Where it could help your business

Evaluate night visibility at entrances exposed to rain and vehicle headlights.

Test a walking person and moving vehicle under your real lights. Look for motion blur, smeared detail and headlights obscuring plates. Compare the original footage at a useful playback size rather than judging a small preview on a phone.

What your camera setup needs

Depends on the camera sensor, lens and illumination. Processing cannot recover details that were never captured.

Can AI night vision see clearly in complete darkness?

It cannot create reliable scene information without a usable signal. The camera may need infrared or visible illumination, depending on its design and the detail you need.

Check it on your own site

Bring a camera model list and explain the event you want to find or detect. We can use that to scope a compatibility assessment. Ask for a written proposal naming the supported functions, processing hardware, licences and pilot checks before agreeing to an installation.

Check my camera setup →

Calculator · C19

Low-light imaging: estimate it for your site

Use your own measurements. The result is the energy and tariff difference on your own figures, using the formula below. It runs in your browser and nothing is sent anywhere.

Fields start empty. A blank is “not entered”, not zero; type 0 where 0 is true.

Keep this equal to the current wattage until a site test shows the scene is still lit enough for people as well as cameras.

Money (optional)

Only from your own records. May be negative.

Licences, support, connectivity. Enter 0 if there is none.

Hardware, installation, commissioning. Enter 0 if there is none.

Enter every amount on the same basis — all including GST or all excluding it. Nothing here adds or removes tax. Values are nominal rupees, not discounted.

Result

Enter your own figures, or load the worked example, to see the result.

How it is calculated

kWh difference = (old − new light watts) × lights × hours × days ÷ 1000 − added camera watts × hours × days ÷ 1000; cash = kWh × tariff

Worked example (illustrative inputs)

100 W to 60 W; 10 lights; 12 h; 30 nights; 20 W extra; ₹8/kWh (illustrative tariff).

energy difference: 136.8 kWh a month; cash difference: ₹1,094 a month.

Formula version 1.0.0. The full standalone tool: electricity cost.

What this does not tell you

  • Do not reduce lighting that people need for safety or security. The example's reduction is illustrative; set the proposed wattage equal to the current one until it is validated on site.
  • The tariff in the worked example is illustrative. Use the rate on your own bill.

Evidence status: Supplier/integration or marketed capability; PGAK availability and site performance require verification.

Request a site-specific assessment with these assumptions

Your result stays on this page either way. If you want it checked against your cameras and quotation, leave a number; mention the figures on the call. Nothing you typed into the calculator is sent with this form.

Request a camera assessment. Timing and scope agreed on the call. By submitting, you ask PGAK to contact you about this enquiry. Privacy notice.