Electrical grounding and bonding, as a means to provide a low-impedance electrical connection between two or more metallic bodies that are normally not current-carrying, has long been a necessary task for the industry. Electrical grounding prevents circuit overloads and removes dangerous ground-fault voltage on conductive parts. Primarily, grounding and bonding is a mechanism to protect homes and businesses, and their contents (including people), from electricity surges, such as from lightning.
When all of the communication and power grounds are working at a home or business, and a real “good grounds,” any stray current in the system goes to ground and no voltage differences exist between them which is the desired state. However, when grounds are bad, the current can and will find its way into the CATV network. When voltage appears in the CATV network the voltage potential problem appears to “drop the voltage” of anything connected to the network.
Set-top boxes, modems, gateways, or, in the case of large MDUs, line extenders all have seen the drop in voltage. Stories abound from technicians taking the hit of 90-volt shocks from power passing taps, or 120-volt shocks when hooking cable up to taps in MDU lockboxes – which makes for a decidedly unpleasant site visit! Proper electrical grounding and bonding is as equally or more important to business/enterprise customers especially when lightning hits a facility, knocks out half of its servers, and turns out to be a grounding issue – as in, “our fault” (pun intended.) This paper describes the use of Computer Vision (CV), Artificial Intelligence (AI) and Machine Learning (ML) to provide technicians with a visual verification that gives them a high level of confidence that the structure (the home or business) they’re visiting is properly grounded and bonded, using an app developed at Comcast Labs, on their work-issued iPhone or iPad. The paper covers the background and history of grounding and bonding; why those activities continue to be vitally important in communications network performance; and the importance of images and image annotation to build a production-grade database of proper grounds/bonds that can be put to work by field technicians when assessing a home or business.