Network Video Solutions
Designing for the customer's question
A solution starts with the operational question the video must answer: identify a face, read a plate, or detect an event. Define pixel density on target before choosing hardware. Common working figures: roughly 250 px/m for detection, 500 px/m for recognition, and 1000 px/m for identification. Trap: questions that give distance and field of view but expect you to reason about pixels per meter rather than megapixels alone.
Architecture choices
Compare centralized recording, edge (camera/SD) recording, and distributed or redundant designs. Consider failover recording, redundant power, and network topology (star versus daisy-chained). Bandwidth is reduced by recording at the edge and by smart streaming; multicast helps many viewers of the same stream but requires IGMP snooping.
Cybersecurity as a design requirement
Know the baseline: change default passwords, use HTTPS and signed firmware, segment camera VLANs, disable unused services, and manage devices centrally. Trap: options that improve convenience but weaken security, such as universal shared credentials or exposing cameras directly to the internet.
Integration and analytics
ONVIF profiles, VAPIX-style APIs, and metadata enable integration with access control and analytics. Analytics shift from server to edge, reducing bandwidth by sending metadata rather than video.
Worked example
A parking lot needs plate reading at 30 m. At 1000 px/m for identification, a 3 m wide lane needs about 3000 px horizontally - so a 4K camera framed tightly on the lane, not a wide overview camera, is the correct answer.