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Combining industrial hardware connections with the processing power of a Raspberry Pi Compute Module 3+ the BB-400 NeuronEdge gives you the possibilities of open source software in a simple retrofit way, unlocking the potential of your equipment.
The BB-400 NeuronEdge combines Brainboxes proven IO and serial connectivity with a range of network connections to allow data to flow to the application of your choice. The innovative design uses a Raspberry Pi Compute module and an Arduino to provide edge processing. The Pi is supported by a power management system, including a UPS, making it match the robust demands of industry. This allows you to develop on Raspberry Pi and deploy seamlessly to the factory floor.
Multiple hardware interfaces allow for communication with many different types of equipment and machinery. Use Ethernet, Bluetooth, IO, Wi-Fi, NFC, USB, RS232/422/485 to interface with many different types of device from the compact BB-400.
The device offers the flexibility of PC systems with open source API programming options to make integration and customisation user friendly. Combining insights from machinery of all types and ages can be done through a preferred programming language, such as C# and Python or visually in Node-RED, circumventing many of the interoperability issues that have traditionally hampered integrated automation.
Specs
| Technical details |
| Built-in processor |
Y |
| Wi-Fi |
Y |
| Number of processors installed |
1 |
| Processor frequency |
1200 MHz |
| Ports & interfaces |
| Ethernet LAN (RJ-45) ports |
2 |
| Power |
| Power consumption (typical) |
4 W |
| Input voltage |
5 - 30 V |
| Weight & dimensions |
| Width |
120 mm |
| Depth |
99 mm |
| Height |
45 mm |
| Weight |
248 g |
| Package width |
160 mm |
| Package depth |
135 mm |
| Package height |
49 mm |
| Package weight |
334 g |
| Networking |
| Ethernet LAN data rates |
10,100 Mbit/s |
| Networking standards |
IEEE 802.11b,IEEE 802.11g,IEEE 802.11n |
| Frequency band |
2.45 GHz |
| Wi-Fi |
Y |
| Operational conditions |
| Operating temperature (T-T) |
-25 - 80 °C |
| Storage temperature (T-T) |
-40 - 85 °C |
| Operating system/software |
| Compatible operating systems |
Raspberry Pi
Android
Linux |
| Software |
| Compatible operating systems |
Raspberry Pi
Android
Linux |
| Memory |
| Internal memory |
1024 MB |
| Flash memory |
32000 MB |
| Internal memory type |
DDR2 |
| Display |
| Control display unit |
N |
Features
Brainboxes BB-400. Ethernet LAN data rates: 10,100 Mbit/s, Networking standards: IEEE 802.11b,IEEE 802.11g,IEEE 802.11n, Frequency band: 2.45 GHz. Width: 120 mm, Depth: 99 mm, Height: 45 mm. Power consumption (typical): 4 W, Input voltage: 5 - 30 V. Compatible operating systems: Raspberry Pi Android Linux. Internal memory: 1024 MB, Flash memory: 32000 MB, Internal memory type: DDR2
Product Description
Combining industrial hardware connections with the processing power of a Raspberry Pi Compute Module 3+ the BB-400 NeuronEdge gives you the possibilities of open source software in a simple retrofit way, unlocking the potential of your equipment.
The BB-400 NeuronEdge combines Brainboxes proven IO and serial connectivity with a range of network connections to allow data to flow to the application of your choice. The innovative design uses a Raspberry Pi Compute module and an Arduino to provide edge processing. The Pi is supported by a power management system, including a UPS, making it match the robust demands of industry. This allows you to develop on Raspberry Pi and deploy seamlessly to the factory floor.
Multiple hardware interfaces allow for communication with many different types of equipment and machinery. Use Ethernet, Bluetooth, IO, Wi-Fi, NFC, USB, RS232/422/485 to interface with many different types of device from the compact BB-400.
The device offers the flexibility of PC systems with open source API programming options to make integration and customisation user friendly. Combining insights from machinery of all types and ages can be done through a preferred programming language, such as C# and Python or visually in Node-RED, circumventing many of the interoperability issues that have traditionally hampered integrated automation.
