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Edge Compute: The Silver Lining to Your IoT Cloud

With the increasing demand for edge compute functionality to manage the high volume of data produced by installed IoT applications comes questions and a certain amount of confusion. There are multiple ways to architect edge compute; which one is right for your application, and how can you be sure you address all the considerations along the way to deployment?

This webinar recording, delivered by two knowledge experts from Digi Wireless Design Services, describes the scenarios where edge computing makes operational sense, as well as the stages of edge compute architecture, the key considerations you need to evaluate depending on your type of application, and approaches to edge compute that can dramatically improve efficiency and ensure you can respond to critical events.

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Recorded Webinar

| Length: 50:23

With the increasing demand for edge compute functionality to manage the high volume of data produced by installed IoT applications comes questions and a certain amount of confusion. There are multiple ways to architect edge compute; which one is right for your application, and how can you be sure you address all the considerations along the way to deployment?

This webinar recording, delivered by two knowledge experts from Digi Wireless Design Services, describes the scenarios where edge computing makes operational sense, as well as the stages of edge compute architecture, the key considerations you need to evaluate depending on your type of application, and approaches to edge compute that can dramatically improve efficiency and ensure you can respond to critical events.
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Follow-up Webinar Q&A

Thank you again for attending our session on edge computing with experts from Digi Wireless Design Services (WDS). Here are the questions that followed the presentation and their answers. If you have additional questions, be sure to reach out.

Is there a plan to combine the Python computing power of the XBee 3 with the 900 MHz platform? I find us in the situation where we need to computing power of the new XBee 3 series but with the signal penetration of the 900 MHz series.

Yes. The 900 MHz version of the Digi XBee® 3 is on the roadmap for a future release.

We use the Digi XBee 3 LTE Cat-1 modem with AWS IoT Core over MQTT protocol. My question is how to determine the proper Keep Alive interval so that we can keep the cellular connection without burning too much data?

The valid range for Keep Alive is 30-1200 seconds with a default of 1200. Using the max value of 1200 would minimize the number of pings and keep the amount of data usage to a minimum. Does your device send periodic data? If so, you could set Keep Alive to slightly more than that period to effectively eliminate Keep Alives. If that period is longer than 1.5 * 1200 = 1800 seconds, then you must consider something in between. The broker will terminate the connection at 1.5 times the Keep Alive if a ping or publish is not received.

There is a tradeoff between the number of pings required to hold the connection and how much data usage you can tolerate. I would be curious to hear your experiences so far.

I use a gateway to collect data from remote sensors using XBee Industrial Gateway. Can I use a Network Attached Storage device with it to locally warehouse data?

You should be able to, but this will probably require some custom programming for you to move the data to the storage device. And of course Digi WDS can provide the development support you need for those custom scenarios. In simpler applications, an XBee 3 cellular (LTE Cat-1 or Cat-M/NB-IoT) radio can serve as a gateway for local sensors and Zigbee/DigiMesh radios. The gateway functions can be implemented in MicroPython. Selection of the network protocol usually depends upon the needs of the application. We have a lot of expertise in developing these solutions and would be happy to discuss this further with you.

Any suggestions for a simple POC using WVA to capture key CAN messages from agriculture equipment...tractors, combines, etc?

This sounds like a Digi Sales question. Assuming that the connector is compatible (a simple cable can solve this otherwise), I would assume that the WVA used in conjunction with the Android demo app (or a customized version) should be acceptable for providing a bus monitor. There are other commercially available COTS hardware dongles and software packages that are specifically made for this type of bus monitoring. I own several myself.

Can you share contact information to reach the design services team directory?

Here is a link for contacting us: www.digi.com/contactWDS

What type of edge computing solution are you starting to see more of in the past year or two?

We have been consistently seeing needs for more capable gateways. ML (Machine Learning) is also becoming a much more common ask from our clients. We have been using the Digi ConnectCore® 8X SOM and SBC more due to the enhanced computing capabilities over i.MX6 versions.

For simpler applications, there are new/small/inexpensive microcontrollers coming out with built-in support for AI/ML applications. These can serve as “smart edge gateways” if paired with the appropriate radios. Digi WDS develops custom gateways such as these, on a case-by-case basis.

You mentioned Digital Twins. Can you explain this concept further?

The concept has been around for a while, but with a new market friendly name it is getting more attention. The basic concept entails maintaining individual copies of items such as configuration, device state, health, commanded state, etc. at both the remote end and in the cloud. A more advanced version includes the ability for the cloud twin to be able to simulate and predict behavior of the remote twin. This topic could be a future webinar.

Can you use third party software on your platform?

Digi SOMs and SBCs are Linux-based. Applications or third party software packages for this environment can be used within the limits of the memory of the individual devices.

Digi XBee 3 devices can run MicroPython applications, and Digi has libraries available for that (see the Digi XBee MicroPython Github library). Also, regular Python libraries can be ported to MicroPython in many cases.

What do you use for long distance edge sensor radios? Are these programmable?

We tend to favor sub-GHz radios for long range edge sensors. Digi has several models to choose from: Digi XBee-PRO 900HP and two versions of the Digi XBee SX 900.

  • The 20mW XBee SX radio module is rated for a max range of 9 miles LOS with a high-gain antenna.
  • The 1-Watt XBee SX radio module is rated for a max range of 65 miles LOS.
  • The Digi XBee-PRO 900HP has a rated max range of 28 miles LOS with a high-gain antenna.

All XBee radios are able to be configured for many analog/digital, input/output, and serial communications applications without any coding. As for MicroPython, this is on the roadmap for 900 MHz radios. Links for both are included below:

Can you speak about some of the local sensor technologies such as Zigbee, using a 4G modem as a transport?

We assume that this refers to a gateway. Digi has several gateway products that support Zigbee as a local RF medium and have 4G cellular for the backhaul. In this case, the gateway will act as the Zigbee network coordinator. These same devices may be configured with different firmware to support DigiMesh or base 802.15.4 protocols.

Can you tell me a bit about the differences between Cat-M and NB-IoT? Why would I choose one over the other?

Both are good choices for IoT applications. The main differences are bandwidth and mobility. Cat-M enjoys full LTE signaling and can support mobile applications. Cat-M can also support voice. NB-IoT is intended for stationary applications like parking meters, utilities, and the like. NB-IoT has a higher link budget so it can penetrate buildings better than other cellular categories. NB-IoT is most suitable for applications that can run for years on a small battery when data is small and data-reporting is infrequent.

For clients that are trying to decide on which type of service use, we usually suggest using the Digi XBee LTE-M/NB-IoT module which natively supports both protocols. This module can be configured by application software for either protocol, as needed. Digi WDS can provide further advice and/or programming support when needed.

Are there any limitations on running AI applications on smaller embedded compute platforms?

Obviously, the capabilities and resources of the microcontrollers will limit the type of AI that can be supported. With that said, there are off-the-shelf inference engines that can be used in bare metal or RTOS environments as well as application processors and GPUs.

For simpler applications, there are new/small/inexpensive microcontrollers coming out with built-in support for AI/ML applications. These devices might be suitable for many monitor/control applications.

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