# Advanced Assistive Maintenance Based on Augmented Reality and 5G Networking
###### Abstract  
Internet of Things (IoT) applications play a relevant role in today's industry in sharing diagnostic data with off-site service teams, as well as in enabling reliable predictive maintenance systems. Several interventions scenarios, however, require the physical presence of a human operator: Augmented Reality (AR), together with a broad-band connection, represents a major opportunity to integrate diagnostic data with real-time in-situ acquisitions. Diagnostic information can be shared with remote specialists that are able to monitor and guide maintenance operations from a control room as if they were in place. Furthermore, integrating heterogeneous sensors with AR visualization displays could largely improve operators' safety in complex and dangerous industrial plants. In this paper, we present a complete setup for a remote assistive maintenance intervention based on 5G networking and tested at a Vodafone Base Transceiver Station (BTS) within the Vodafone 5G Program. Technicians' safety was improved by means of a lightweight AR Head-Mounted Display (HDM) equipped with a thermal camera and a depth sensor to foresee possible collisions with hot surfaces and dangerous objects, by leveraging the processing power of remote computing paired with the low latency of 5G connection. Field testing confirmed that the proposed approach can be a viable solution for egocentric environment understanding and enables an immersive integration of the obtained augmented data within the real scene.  
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Nowadays, however, these solutions alone are not enough: the whole system can be made more efficient by adopting newer models that enable the assistive guidance of experienced workers without being physically on-site, and deliver guidance to more apprentices at the same time. An effective back-office interaction with field employees is thus becoming a crucial point for an efficient maintenance policy. Moreover, thanks to emerging technologies such as AR helmets and 5G networking, traditional interactions by means of cellphones or work-specific messenger applications are overtaken by more immersive and interactive approaches.  
In this paper, we present a complete advanced assistive maintenance framework (Figure 1), deployed and tested in a real-world scenario. The on-site operator is provided with an AR helmet equipped with a thermal camera and a depth sensor. All these devices are connected in a WLAN based on the IEEE 802.11 ac protocol and send data to a customer-premises equipment (CPE). The CPE provides a 5G connection to a remote control room, which hosts a Multi-access Edge Computer (MEC) that enables performing complex processing tasks for the egocentric vision system in real-time. A further remote call with a fully shared augmented reality environment was also implemented to allow an advanced support by an expert from a control room. The MEC approach represents in fact an affordable compromise to bring applications from centralized data centers in the cloud to the network edge, closer to the consumers and the data acquired by multiple sensors, and is acknowledged as the main brick to accomplish 5G 3 GPP specifications [3].  
The rest of the paper is organized as follows. Section 2 overviews the field of AR for egocentric vision systems. Section 3 frames the proposed system within the 5G panorama. Sections 4 and 5 describe the algorithms developed to process the acquired 3D scene and integrate the information from heterogeneous sensors (depth and thermal cameras), respectively. Section 6 illustrates the prototyping and testing phase, along with a discussion of the obtained results. Finally, Section 7 concludes the paper and draws the overall conclusions.