The Raspberry Pi is widely utilized for its project capabilities among engineers and makers alike. It has been used to create everything from robots to remote monitoring devices since its release back in 2012. Not long after, industry managers took note of the tiny board's capabilities and adapted them for use in manufacturing and automation operations, with some using the famous board to build specialized equipment to make those applications more efficient and cost-effective.


On its own, the Raspberry Pi provided an attractive alternative to PLCs (Programmable Logic Controllers), which are prominent in many industries, including manufacturing, automation, and IIoT platforms. Being cost-effective and efficient at carrying out programmed tasks via a simple GPIO interface, allowed the Raspberry to break open the doors to those industries and be used for general operations. The board's use in an industrial setting was so widespread that the Foundation designed a dedicated board based on the Pi for the sole purpose of being implemented into industrial operations. Thus the Raspberry Pi Compute Module was born.


The Raspberry Pi Compute Module 3 + Development kit allows engineers to design and test applications before deploying an SoM into a system. (Image credit: Newark)


When the Raspberry Pi 3 Model B was released in 2016, the Compute Module 3 followed shortly afterward. While it retains the same SoC (Broadcom BCM2837) as the development board, it features a SODIMM form factor with the signals for the missing ports transferred through the Edge connector rather than the Pi's GPIO. The design of the Compute Module was intentional, so it could easily be integrated into existing industrial and automation systems without the need for a complete overhaul of the hardware and Linux-based software stack. It also makes it easy to upgrade as new modules (currently the Compute Module 3 +) are introduced.


After the Raspberry Compute Module hit the market, manufacturers scrambled to incorporate the card into various modular design enclosures to target specific industry systems, such as those requiring slim DIN-rail platforms, internal power supplies for redundancy, and relays to drive automation systems. Some of the more notable Pi-powered devices targeted at industry end-users include Hilscher's netPi RTE 3 IoT gateway, which packs a Raspberry Pi 3-based netX SoC designed for Edge Automation. The module packs a pair of Industrial Ethernet ports to connect to systems such as PROFINET and EtherNet/IP. It features an open-ended bottom for adding extension modules for sensor and actuator-level communications such as RFID and digital I/Os.



The ModBerry 500 is driven by a Raspberry Pi Compute Module 3 + and offers a wide range of Serial ports, analog inputs/outputs, wireless communications, and more. (Image credit: TechBase via IIoT shop)


Another excellent example of the incorporation of the Compute Module for industrial, IIoT, and automation applications comes from TechBase, with its ModBerry 500/9500 industrial computer. Everything about the ModBerry can be customized for targeted platforms, including the number of Serial ports, analog inputs/outputs, Ethernet ports, wireless/GSM modems, software options, and even the way the enclosure can be mounted.


The great thing about the Raspberry Pi is it isn't limited to large-scale industrial settings, as it can be incorporated into small operations as well. Some great examples include being used to monitor temperatures in bakeries, including Zaro's in NYC, who used the board, a Kosmos IoT system, and NCD industrial wireless sensors to provide optimal cooling in the company's freezers. The platform helped the company save time by monitoring temperature readings, as employees were tasked at performing that job throughout the day.


Former embedded systems designer Makoto Koike took his knowledge of designing automobile systems, and used a Raspberry Pi 3 to help his parents with their cucumber farm. Specifically, he created an industrial sorting machine using the Pi to separate thorny vegetables during harvest processing. Makoto tasked the Pi as a controller for a camera that sends real-time video to a TensorFlow-based neural network that identifies different types of plants and separates them accordingly. His system helped save the farmers eight to nine hours of extra work every day, thus making his parent's farm more efficient and profitable.


Manufacturers and industries have been upgrading their respective systems over the years to take advantage of Industry 4.0 and even 5.0 technology to stay competitive. The Raspberry Pi has remained a reliable platform for industrial applications for the better part of a decade, and the Foundation is on point to release a Compute Module version of the Raspberry Pi 4 at some point (if the rumors are true, there's no official statement as of yet) in the near future. So it's a good bet we will continue to see the Pi continue to evolve right alongside industrial and automation systems for the foreseeable future.      


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