Understanding the Role of Edge Computing in Post-COVID Restaurant Recovery

Lewis Carr, senior director of product marketing at Actian, discusses how edge computing solutions can help restaurants build trust with customers in the post-COVID-19 era through the use of customized mobile and IoT applications.

While COVID-19 has hammered industries across the board, restaurants have suffered more than the rest. About 17% of America’s eating establishments closed permanently during 2020, and those still standing have a long struggle still ahead.

The restaurant industry, as well as other service-oriented industries, need a real, tangible solution to return to profitability. Effective COVID-19 vaccines may well provide that solution by enabling people to achieve immunity. But it may take a while for the government to roll out vaccines on a large scale to immunize the entire population. What if the pandemic lingers on longer than expected? Or if a new contagion threatens society in the future and forces communities to adopt new restrictions? How will restaurants convince consumers that it’s safe to return to public dining? How do they rebuild trust until the general public achieves complete immunity from the virus?

A longer-term solution – for restaurants and other industries – will involve the deployment of mobile and IoT applications that can generate useful data for multiple purposes. Creative uses of technology at our networks’ edge will enable restaurants and other businesses to solve seemingly impossible problems through the magic of data.

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A Hypothetical Edge Computing Solution for Restaurants

An integrated system that helps restaurants rebuild trust, governments to trace infected citizens, and restaurant apps to do more business can come into effect if there is a seamless flow of data between the three parties. 

The process can start with restaurant inspections. County and local governments now rate restaurants for cleanliness in the form of letter grades based on periodic assessments. These are generally paper certificates posted in the window. What if an electronic certificate posted on restaurant windows could change based not just on regular inspections but on other factors as well? 

These could track COVID-19 safety levels based on how well tables inside are spaced out, how crowded the restaurant is at any given time, whether the restaurant performs temperature readings for patrons and its employees, and whether anyone exhibits high temperatures. All of these can be graded and displayed separately or weighted and aggregated as category grades.

To enable such a system to function at all times, restaurants, restaurant apps, and local governments will need to leverage IoT and wireless technologies. Here are some examples of solution elements that could be used in various combinations to deliver real-time grading. 

• Tracking: NFC or RFID tracking technologies could be used in tandem with customers’ mobile phones to track their entry and exit from restaurants or to show how separated they are from each other. A local app may also track RFID-tagged tables and chairs to monitor adherence to physical distancing rules.
• Temperature readings: This data could be uploaded into a local app and be compared with unique but masked identifiers such as cell phone IMEIs to avoid duplications for the same location but still provide tracking across regions. 
• Restaurant ratings: Yelp! and equivalent restaurant reviewers would then need to take parts of this information and add it to their applications. Their restaurant profiles could let potential diners know that Restaurant X is enforcing physical distancing and mask-wearing except when seated, and if it’s currently registering at 50% of physically distanced capacity. The status may also say how many elevated temperature cases have been seen over the last day, week, or month.  

Restaurants that elect to opt-in and provide useful information to customers will quickly build trust, whereas those that do not may have a more challenging time rebuilding customer trust. Incentives for Yelp! and their equivalents would include stickier information, undoubtedly correlating with the increased use of their app and, in turn, improved profitability based on their revenue models.  

In this scenario, governments that collect and aggregate local data will better understand if bars and restaurants are spreading the virus or not. They could also identify factors determining higher or lower risks. Additionally, this data could also define and trigger indicators to identify outbreaks earlier.

Employee and patron identities can be kept hidden without removing critical information regarding physical distancing. For track and trace, an agreement between cellular service providers, government, and citizens is required to allow for information to be shared as a baseline to add this valuable information to the track and trace data sets. 

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Applying This Scenario in Other Industries

The tracking of entry and exit data is essential in any physical on-premise setting. Data collected across large sets of buildings and locations, if tracked in real-time, can generate gargantuan sets of data. Therefore, analysis should be done locally so that implementing similar sets of mobile and IoT systems Opens a new window with local applications that deliver information to other remote applications would be very similar.

As briefly mentioned above, policy decisions must be agreed upon to allow for these scenarios to be implemented. However, many of the underlying technology requirements to make these scenarios work are already underway. 

For example, 5G networks will provide the bandwidth, segregation and quantity of channels with proper security necessary for the edge applications of tomorrow. While 4G/LTE can handle pilot projects, full implementations of multiple industries tied to government support for oversight and track and trace, will run into bandwidth limitations that 5G solves.  

The key difference that 5G brings is at the network level with respect to applications. Now that we’ve moved virtualization functions deeper into the stack of compute, storage and network and towards convergence of a single elemental virtualized environment, we’re beginning to move the virtualization and convergence model from the data center and the cloud and out to the edge. 

As this movement solidifies, we can expect to see an improved environment for distributed applications with shared data. This is a core requirement for the scenarios described above that rely on a combination of local applications at the physical point of presence – the restaurant – and elements of the application function and data being handled remotely and independently within the government and commercial entities like Yelp!

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Taking It to the Edge

Edge computing has made rapid advances in recent years, spurred on further by the remote work boom that took hold during the pandemic. Expect it to play an even bigger role over time in industries such as restaurants, commercial real estate, retail and more as companies look to revitalize their businesses in a post-pandemic environment.  

Do you think the service industry needs edge computing solutions to build trust with customers? Let us know your thoughts on LinkedInOpens a new window , TwitterOpens a new window , or FacebookOpens a new window . We would love to hear from you!