Using AI and AR to Address 5G Labor Shortages

As you may have read in recent articles by AGL and RCR, the wireless infrastructure industry is facing a serious labor shortage in conjunction with the rapidly advancing rollout of 5G.    

A recent panel titled “AI and AR: Working Smarter, Not Harder” at the 2019 Wireless West Conference in Scottsdale, Arizona, discussed new technologies that may help address the impending labor shortage.

CTIA forecasts in its report The State of Wireless 2018 that mobile network operators (MNOs) will deploy 800,000 new small cells in the USA by 2026. That is more than twice the number of sites that have been deployed over the last 25 years. While small cells may be smaller than traditional macro sites, the deployment process remains labor intensive and the ongoing management of those leases and site data is no less complex.  

The panel focused on evolving technologies in Artificial Intelligence (AI) and Augmented Reality (AR) that can ease the strain of a labor shortage and even accelerate 5G deployments in three specific areas.

Inspections and audits of tower sites

AI and drones can be combined to save money and increase safety by reducing the number of truck rolls and tower climbs. Former tower climber Sam McGuire described how Red Mountain Scientific uses AI techniques to capture and analyze drone inspection data and generate tower-specific reports for visual inspections, closeout packages, and asset audits.

Site acquisition for small cells

Scout, a mobile application developed by Overlay and Md7, uses AR to accelerate the field-to-final process by capturing and synchronizing field data with the back office. Chris Morace, Founder of Overlay, noted that, by combining Scout with a survey-grade GPS, the app creates a video audit for virtual site walks as well as a 3D model that can be used to measure the site and auto-generate final deliverables such as candidate packages, 1As, topographic surveys, and CAD files.

Lease reading and ongoing lease data management

For every site on-air, there are numerous lease and other real estate-related documents that have to be maintained and managed throughout its operational life. MNOs spend tens-of-millions of dollars each year to read and reread cell site leases to identify key terms such as rent obligations and upgrade rights.  This often results in inconsistent interpretation of these key terms further costing MNOs millions of dollars. Md7 uses Machine Learning and AI software to find and maintain key lease provisions and categorize data. This allows Md7 to increase the accuracy and reduce the time needed for file audits and other ongoing lease management decisions as well as keep this information up-to-date to avoid rereading leases in the future.

Conclusion

The panel, which also included Casey Lynch, a Professional Land Surveyor and founder of Rancho Land Services in Ramona, California, all agreed that the key to a successful implementation is for the wireless infrastructure industry to embrace these evolving technologies. It is not enough for the developers of AI and AR to learn about wireless infrastructure. We must learn about their tech, and the sooner the better.

May 6, 2019
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