In our previous blogs, we’ve explored the type of tests involved to successfully pass the criteria of GR-63-CORE, Physical Protections, GR-1089-CORE, Electromagnetic Compatibility, and Electrical Safety.  The goal of successfully completing these tests is to create Carrier Grade, NEBS compliant equipment.  However, outside of highlighting the set of documents that compose NEBS, nothing is mentioned of the NEBS levels and the requirements to achieve each level. NEBS levels are defined in Special Report, SR-3580.  

Figure 1. NEBS Certification LevelsNEBS Level 3 compliance is expected from most Telecom environments, outside of a traditional data center. So, what NEBS level do equipment manufacturers aim to achieve?  

At first, I created Figure 1 as a pyramid, not inverted, with Level 1 as the base and Level 3 as the peak. However, I reorganized the graphic because Level 1 isn’t really a foundation, it is a minimum acceptable level. Let’s dive into what is required to achieve each NEBS certification level. 

NEBS Level 1

NEBS Level 1 is the lowest level of NEBS certification. It provides the minimum level of environmental hardening and stresses safety criteria to minimize hazards for installation and maintenance administrators.  

This level is the minimum acceptable level of NEBS environmental compatibility required to preclude hazards and degradation of the network facility and hazards to personnel.

This level includes the following tests:

• Fire resistance
• Radiated radiofrequency (RF)
• Electrical safety
• Bonding or grounding

Level 1 criteria does not assess Temperature/Humidity, Seismic, ESD or Corrosion.

Operability, enhanced resilience, and environmental tolerances are assessed in Levels 2 and 3.

NEBS Level 2

Figure 2. Map of Seismic Potential in the US

NEBS Level 2 assesses some environmental criteria, but the target deployment is in a “normal” environment, such as data center installations where temperatures and humidity are well controlled. These environments typically experience limited impacts of EMI, ESD, and EFTs, and have some protection from lightning, Surges and Power Faults.  There is also some Seismic Testing performed on the EUT, but only to Zone 2. While there is no direct correlation between seismic zones and earthquake intensity, in the United States, zone 2 generally covers the Rocky Mountains, much of the West and parts Southeast and Northeast Regions. 

NEBS Level 2 certification may be sufficient for some Central Office (CO) installations but is not sufficient for deployment to Far Edge or Cell Site Enclosures which can be exposed to environmental and electromagnetic extremes, or in regions covered by seismic zones 3 or 4.

NEBS Level 3

Figure 3. Level 3 criteria

NEBS Level 3 certification is the highest level of NEBS Certification and is the level  that is expected by most North American telecom and network providers when specificizing equipment requirements for installation into controlled environments.

Level 3 is required to provide maximum assurance of equipment operability within the network facility environment. 

Level 3 criteria are also suited for equipment applications that demand minimal service interruptions over the equipment’s life.

Full NEBS Level 3 certification can take from three to six months to complete. This includes prepping and delivering the hardware to the lab, test scheduling, performance, analysis of test results, and the production of the final report. If a failure occurs, systems can be redesigned for retesting.  

Conclusion

While environmental, electrical, electromagnetic, and safety specifications described in NEBS Level 3 certification, it is the minimum required for deployment into a controlled telecom network environment; these specifications are only the beginning for outdoor deployments. The next blog in this series will explore more of these specifications such as GR-3108-CORE and general requirements for Network Equipment in Outside Plant (OSP). Stay tuned.

As discussed in Part 1 and Part 2, this blog provides a comprehensive analysis of potential edge computing solutions for those current problems in the retail sector, including retail shrink, stocking, and item locations.

In this part, we will be looking at a consolidated solution for the problems discussed in Part 1 and Part 2. 

Consolidated solution

Solution overview

All three solutions I have created for the retail problems involve the use of smart cameras and computer vision to analyze products and their whereabouts in the store. Since there are so many common pieces between the solutions, it would be easy to create a fourth solution that encompasses and solves the three problems.

For this solution, there are many different items you will need. The retail store’s pre-existing or newly installed cameras must be placed throughout the store aisles, the self-checkout stations, and the storefront. You also need the Dell VxRail cluster which has the compute power, storage, machine learning models, and computer vision applications. The computer vision applications themselves are use real-time video analysis to identify, track, and count products on the shelves, validate self-checkout items, and monitor where the items are located. The self-checkout machines must be connected to the cluster. Optionally, you can use the shelf weight sensors to complement the cameras in the aisle for better estimates of the number of items on the shelves.

There are many different problems that are solved with this solution, the first being shoplifting. At the self-checkout machines, the customers scan their items like normal, but the cameras send the feed to the ML models to verify in real-time whether the item is correctly labeled. If a mismatch is detected, then the customer is prompted to try again. If the customer is unable to fix it, then the system can alert the cashiers to assist. The system can also track products throughout the store to make sure nobody is storing items in their clothing or refusing to scan them at the self-checkout. If they do, the system can alert a staff member to handle it.

The next problem being solved with this solution is the monitoring of stock in the shelves. The cameras stationed throughout the aisles record and send real-time footage back to the cluster, which can count how many items there are on the shelf. The store can set thresholds to determine low-stock situations, and when the amount of the product enters that threshold, the system will alert the employees to go and restock the shelf. Additionally, the customer can add weight sensors to the shelf to aid the system in determining how many items there are on the shelf. This will enhance the inventory management, and it will minimize the amount of time a product is unable to be purchased due to empty shelves.

The last problem to be solved with this solution is misplaced items in the store. Using the same cameras and real time footage from the last problem, the models on the cluster will determine what products there are on the shelf. The cameras will be assigned an aisle when they are installed, and the store will enter beforehand what camera corresponds with which aisle and tray. A separate store database will contain information on what item goes where in the store, and the application will check the item location against the store database to make sure it is in the right spot. If it is not, the system can alert an employee to return the item to its proper location.

From combining all three solutions, the store can gain valuable data about the store and its items as well. The system can record what items are attempted to be shoplifted, and if enough people are trying to steal the items, the store may want to take precautions by putting them behind glass or storing them in the back. The store will also gain data on how fast a product’s available stock is being sold, so that the store can determine which items sell slowly and have too much shelf space, and which items need more shelf space so they can put more in the aisles. The system will also record what items are frequently misplaced, which the store owners can use to reorganize the layout and optimize the shelf arrangements to encourage more sales.

Figure 1. Technological diagram

This solution would use the same sequence diagrams as the other three, since they are all different use cases that would be running concurrently.

Figure 2. Shelf-checkout sequence diagram

Figure 3. Shelf stock sequence diagram

Figure 4. Location check sequence diagram

Why edge?

Why do we need to use edge computing in these solutions as opposed to something like the cloud? While you can run apps and databases in the cloud, there are two main reasons why it is imperative that we use edge computing to create these solutions.

The first of these reasons is that we need real-time analysis of the camera footage. Having to transfer your camera footage to the machine learning models and back would be extremely time consuming, and you would lose all the benefits of running the analysis on-site. For example, in the time it would take for you to receive your data back about the stock levels of a product, you may have lost out on many sales because the product was not available.

The second reason is the cost of using a cloud service. Not only is transferring all your camera footage to another server in the cloud extremely slow, but it would also be very expensive. Stores have a lot of cameras and sending the video to another site would take all of your bandwidth, and it would cost a lot of money to get it transferred over there. The price it would take to hold all your camera footage while you did analysis on it would cost more than it would be worth to get the analysis.

More possible problems

Introduction

I took the time to interview people about what problems they encountered when they went to the store. By interviewing actual customers of retail environments, I could gather more insight into what problems affected the lives of shoppers, problems that could possibly lose the business of the customer. If the customer has their problems solved, it may result in more business for the store. These problems are not directly solved by the edge computing solutions I designed, but I believe the impact the solutions make on store efficiency and sales will help to lessen the impact of these problems.

Interviewees and their problems

Interviewee 1: Undergraduate intern, Dell Technologies

Problem: Every store is different

Having a consistent layout in stores can be important because it can help customers find what they are looking for more easily. When walking into a brand-new store, even if the franchise is the same, the layout of the store will be different. This can make it harder for customers to find what they want, which could make the customer go to another store the next time they need to buy something. In addition, having things hard to find can negatively affect the customer experience. Customers may become frustrated if they cannot find what they are looking for and may leave the store without making a purchase.

On the other hand, having things hard to find can also cause the customers to spend more time in the store looking around, which can make them more likely to pick up and buy things that they do not need.

Interviewee 2: Undergraduate intern, Dell Technologies

Problem 1: Occupancy is high

High occupancy can be a problem for stores because it can negatively affect the customer experience. When stores are crowded, customers may feel uncomfortable and may not want to spend as much time in the store. In addition, high occupancy can also lead to safety concerns. If there are too many people in the store at once, it can be difficult for customers to move around and for employees to keep track of everyone.

Problem 2: Time it takes to get checked out is high

Having a long checkout time will negatively impact the sales of the business. Waiting customers could give up and abandon their carts, and they may even go to a different store where the checkout time is shorter.

Interviewee 3: Undergraduate intern, Dell Technologies

Problem 1: Labels of what items in the aisle are not detailed enough

When aisle signs are not detailed enough, it can affect the customer flow, the customer experience, and the sales performance of the store. If aisle signs do not correctly communicate what is in the aisle, then customers will spend more time wandering in the store, when they could be getting checked out to make room for more customers.

Problem 2: Calling for help needs to be easier

Sometimes, customers need to call upon staff to find help. If a customer does not know where something is at in a store, it is possible that one of the retail workers knows instead. In some stores, a customer getting help requires them searching the store for an available attendant.

Interviewee 4: Undergraduate intern, Dell Technologies

Problem: Too expensive

Having an item at a high price means that the company will get more money when it is sold, but sometimes it means that the company will have a harder time selling the item. If an item is priced to highly, a customer may choose to go to a competing store where the prices are lower instead.

Interviewee 5: Undergraduate intern, Dell Technologies

Problem: It is too hard to find things in the store

When it is hard to navigate a store, customers will not be able to find what they are looking for and may leave the store without making a purchase. This can lead to the store losing sales. If a customer leaves the store once because it is too confusing, it is unlikely that they will enter the store again.

Conclusion

In conclusion, edge computing is a valuable resource that can help retail owners elevate and exceed in their business. Edge computing is becoming increasingly valuable for retailers looking to do real-time analysis of data and management of different machines, allowing them to solve new problems and generate more sales. I looked over three different problems in the retail sector that impacted sales, those being retail shrink, empty shelves, and misplaced items, and discussed how those could be solved using edge computing through a text overview and diagrams. I then went over how these solutions all had similar parts, and how you could combine them into one solution to solve all three problems at once. I then went over why edge computing was the right tool for the job and how it was a better choice than other computing options. To end it off, I talk about how I interviewed multiple shoppers on their problems in retail stores. Overall, edge computing is a powerful tool that can help retailers improve their business and provide better customer experiences.

Read more

For more information about using edge computing to enhance the customer experience and operational efficiency, see Part 1 and Part 2 of this blog.