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<time>December 4, 2021 <br> 8:26 AM EST</time>
<p>by Mark Moroney</p>
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<p>I'm interested in learning more about the use of AR and AI to manage network inventory.</p>
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AN AI/AR APPROACH TO INVENTORY NETWORK SYNCHRONIZATION
November 8, 2021
Sam Torrente
Director, Blue Planet Principal Solution Architect – AT&T
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I was recently invited to present a paper on the topic of augmented reality (AR)
and artificial intelligence (AI) approaches for inventory network
synchronization at SCTE Cable-Tec 2021. Given the level of interest by
participants in the use of these advanced technologies, I thought I would share
a summary below.
As service providers continue to accelerate their transformation toward
automation to meet growing customer demand for faster and better services, they
are quickly realizing they can’t automate what they can’t see in the network.
True, with network transformation, more devices can be addressed in the network
to discover what is deployed for service. But reality shows us there is still a
lot of “undiscovered” passive equipment in the path of a customer’s end-to-end
service across these rapidly evolving networks.
Telefonica: Evolving the OSS for SDN and Automation
As a growing number of service changes occur to keep pace with customer demand,
the result is an increasing number of discrepancies between the network and the
inventory database used to design these services – thus leading to greater
service fallout rates, impact to customer experience and potential significant
loss of revenue from dissatisfied customers.
And, while network-to-inventory “manual audits” can provide a snap-shot update
in time, most existing inventory systems are unable to stay in lockstep with the
“as-is” state of the network – resulting in the need for ongoing audits that can
cost service providers millions in expenses they can no longer afford.
> Service providers need help now, so introducing approaches that require
> long-term large-scale people/process change is not viable.
Blog Post
Federation: Building the single source of truth for your network
The reality is that traditional manual corrective means are no longer viable to
reconcile a large and rapidly growing number of discrepancies between a service
provider’s network and their inventory.
AR/AI DRIVEN NETWORK RECONCILIATION
Instead, service providers need new approaches in tools and technologies that
support their evolution toward intelligent network automation and corrects data
discrepancies while co-existing with established delivery processes to their
customers. Service providers need help now, so introducing approaches that
require long-term large-scale people/process change is not viable.
A proposed approach is to leverage existing smart device technology that
combines AR and AI with federated data to create a discrepancy detection and
reconciliation solution that can be easily used in the field. Federation unifies
network resources and services data to create an accurate view that enables the
automation of business processes to enable network planning and design and
faster roll-out of new services.
In this new approach, a field technician that traditionally would enter the
central office and approach a device – in this case a patch panel – to connect a
fiber as part of a work order, would first take a picture of the device with a
readily available smartphone or tablet. AR software on the smartphone would
guide the technician to pan/tilt the smartphone to capture a series of
perspectives within seconds – thus having negligible impact on the technician’s
allotted time for work. The AI software creates a digital map of the device
showing all the detected ports used and available – this is the “as-is” state of
the device in the field, as illustrated above.
Through federated operations, the approach compares the device as
designed/assigned in the central inventory system with the real-time digital
device map captured in the field. The system can then determine the
discrepancies between the planned service and “as-is” state of the network and
use the AR-enhanced visualization to guide the field technician in completing
the service delivery first-time right.
eBook: How to break away from legacy inventory systems
In this example scenario, the work order instructs the field technician to
connect a fiber to Port 2 on the panel but in fact that port is already consumed
in the field. This discrepancy can arise due to a previous service that was
terminated or moved, where the fiber should have been removed, but the previous
technician did not complete the task.
In many real-world cases, the field technician will have an agreed protocol in
place with the service provider – for example guiding the field technician that
if the assigned port is consumed, then take next available, in this case Port 3.
The problem in this scenario is that Port 3 looks to have already been planned
for another service but not yet deployed, so this protocol would compound the
discrepancies between inventory and the network. Instead, the federated
operations system can clearly communicate via the AR display the ports that are
truly available (i.e., Port 4) and AR would guide the technician to the correct
port through their smart phone.
It is important to note that in a connected scenario where the field technician
smart device has network access to the AR/AI/federate operations, this full
process can all be achieved in just a few seconds – having little to no impact
to allocated operations time. In cases where field technician cannot have direct
communications to AI, the AR applications can take multiple images for storage
and then download them for later processing and follow-up guidance.
THE BENEFITS OF AN AR/AI DRIVEN APPROACH
Combining the use of AR/AI technologies with federated operations provides a
wide range of data correlation benefits:
* Using vendor and service provider device templates to wireframe the digital
device map over the real-time image of the panel to confirm that the device
detected is aligned with the device planned.
* Combining GIS data to pinpoint the exact location and devices in scope of the
work-order to be completed.
* Generating a real-time list of discrepancies for network/service planners
that can document needed changes/adjustments to the service without lengthy
delays or error-prone manual updates.
* Guiding the field technician to corrective action that not only stops the
current proliferation of discrepancies but allows the reversal of these
discrepancies in real-time.
THE FUTURE OF DISCREPANCY DETECTION AND RECONCILIATION, WITH TECHNOLOGY
AVAILABLE TODAY
Our approach uses off-the-shelf smart device technology with existing AR
software to guide a technician in capturing multi-angle images with little time
and effort while readily available AI technology quickly digitizes the images
and identifies discrepancies between network and inventory. Federated data and
operations are key to guiding the technician, through AR, to complete and
document tasks first-time right, and, to even correct in real-time reported
discrepancies in the field.
Service providers are taking notice of the power of AI for automating
operations. Discussions with our customers tend to focus on how an AI/AR
approach to inventory network synchronization can help them in real-time across
varying scales of network and operations deployment and in cloud, on-premise, or
hybrid environments. Contact us today to learn how your organization could
leverage this technology to gain operational efficiencies in the field. You can
also read the full paper I presented at SCTE Cable-Tec Expo -- either via the
event site (login required) or download the paper PDF directly here.
Blue Planet Inventory: Learn more
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December 4, 2021
8:26 AM EST
by Mark Moroney
I'm interested in learning more about the use of AR and AI to manage network
inventory.
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