The performance of AI & Predictive Maintenance in Industrial IoT

IoT technology solves challenges of predictive maintenance by enabling real-time remote status monitoring. Instead of maintaining hardware monthly or every 11 quarters, companies can use IoT health monitoring for direct maintenance. Simple IoT devices can now monitor critical performance metrics in real time and send alerts when problems start.

Industrial IoT on the site

Traditionally, those types of failures were prevented by routine scheduled maintenance by specialized technicians. But as discussed earlier, scheduled maintenance is imperfect. Fear of equipment failure often drives businesses to set aggressive preventative maintenance schedules, which of course raises costs.

The cost of equipment failure tends to cascade. The failure of a single piece of machinery can bring an entire assembly line to a grinding halt. And for every hour that production has stopped, hundreds of thousands of dollars might be slipping out the door. That hiccup in production can also result in unfulfilled contracts, angry customers, and upheaval in your supply chain.

In fact, according to a recent paper from IBM, up to 70% of a company’s investment in preventative maintenance does not affect uptime metrics. This is due largely to the fact that only 11% of machine failures follow an age-degradation pattern. A whopping 89% occur at random.


New features of Edge TPU brought to ModBerry series

In October 2020, with the release of the latest Compute Module 4 from Rasbperry Pi Foundation, TECHBASE announced an upgraded device from ModBerry 500 series, called ModBerry 500 CM4. Thanks to the high-performance PCI-Express bus introduced in Compute Module 4 and Raspberry Pi community, the device itself presents support for a wide range of new applications, such as use of Google’s Artificial Intelligence modules at ease.

Therefore, TECHBASE designed a new device, called ModBerry AI GATEWAY 9500-CM4, utilizing the vertical format of ModBerry 9500, latest Compute Module 4 and Google’s Coral TPU. Installation-ready AI GATEWAY allows direct application in industrial fields.

TECHBASE’s AI GATEWAY series, world-first industrial gateway utilizing Raspberry Pi Compute Module 4 and Google Coral TPU

AI GATEWAY with Coral TPU enhancement 

Neuron network capabilities enhance CM4-based devices, not only collecting and sending data, but also allows local data change predictions and allows direct management on-site. This feature gives the possibility for various applications, such as data analysing and establishing trends predictions, smart alarms and smart monitoring, local notification control, etc.

Used Edge TPU coprocessor via PCI-Express bus is capable of performing 4 trillion operations per second (TOPS), using 0.5 watts for each TOPS (2 TOPS per watt). Google Coral easily integrates with Raspberry Pi Compute Module in Linux and optionally in Windows with full support of TensorFlow Lite framework and AutoML Vision Edge solution.

TECHBASE’s AI GATEWAY series, world-first industrial gateway utilizing Raspberry Pi Compute Module 4 and Google Coral TPU
TECHBASE’s AI GATEWAY series, world-first industrial gateway utilizing Raspberry Pi Compute Module 4 and Google Coral TPU

ModBerry AI GATEWAY 9500-CM4 series also offers a standard PCI module support for various wireless communication protocols, such as:

  • GSM modem (4G/LTE and fast 5G modem, interchangeable with Coral TPU)
  • economic NarrowBand-IoT technology
  • LoRa, ZigBee, Sigfox, Wireless M-Bus
  • secondary Wi-Fi/Bluetooth interface or Wi-Fi Hi-Power
  • custom wireless interfaces

ModBerry AI GATEWAY 9500-CM4 availability

First prototypes are being developed, since Compute Module 4 is already available for the purchase. Delivery time for various configurations of AI GATEWAY will be approximately 2 months, depending on the CM4 supply on the market and chosen expansion cards. For more information contact TECHBASE’s Sales Department via email or Live Chat here.