Pixels per Dollar (Pp$): Rethinking the ROI of surveillance cameras
Whether for home or business, most buyers make purchase decisions by comparing product costs. When considering surveillance cameras, the detail of the image, as measured in pixels, dictates whether one can read a license plate or recognise a face. Therefore, one of the most important criteria when evaluating the ROI of a camera is the number of pixels delivered per dollar spent (Pp$).
Megapixel cameras provide superior performance and imaging capabilities versus legacy analogue technology and standard-definition IP cameras. To understand the real value of megapixel cameras, it’s important to evaluate the total system cost, not simply the price of a single camera. Analogue and standard definition IP cameras may be priced less than megapixel cameras on a per-camera basis, but they deliver significantly less value when total system costs are evaluated. This white paper will analyse the additional value of megapixel cameras through a quantifiable measure of that value: pixels per dollar (Pp$).
- Understanding the superior value of megapixel cameras
- Purchasing results, not cameras
- Understanding resolution
- Analogue/VGA vs. Megapixel cost comparison — Parking lot
- System cost vs. Camera cost
- The conclusion
Thank you for submitting your information.
Thank you for your download. Please check your inbox shortly – the asset will be emailed to you.
No email? Please check your Junk or Clutter folders; your email is likely to have been delivered there. To prevent this happening again, please white list our domain @SourceSecurity.com. Instructions can be found here.
Your request has been sent to the company. A representative from the company will get in touch with you shortly via the email / phone number you have provided.
Have a great day!
Wide Dynamic Range Imaging - dispelling myths
Powerful video surveillance protects Red Bull Racing
Safeguarding food production with video surveillance
Innovative edge storage solutions for the video surveillance industry