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BB-400 - Brainboxes RS 232 / 422- 485 8 DIO LINES, ONE ETHERNET PORT FOR WIDER NETWORK, ONE ETHERNE

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$1,123.24
$624.02
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SKU: BB-400
Availability: In Stock
Weight: 1.00 LBS
Shipping: Calculated at Checkout
Networking standards: IEEE 802.11b, IEEE 802.11g, IEEE 802.11n
Ethernet LAN data rates: 10,100 Mbit/s
Frequency band: 2.45 GHz
Ethernet LAN (RJ-45) ports: 2
Weight: 8.75 oz (248 g)
Width: 4.72 (120 mm)"
Height: 1.77 (45 mm)"
Depth: 3.9 (99 mm)"
Package width: 6.3 (160 mm)"
Package height: 1.93 (49 mm)"
Package depth: 5.31 (135 mm)"
Power consumption (typical): 4 W
Input voltage: 5 - 30 V
Operating temperature (T-T): -25 - 80 °C
Storage temperature (T-T): -40 - 85 °C
Built-in processor: Yes
Processor frequency: 1200 MHz
Number of processors installed: 1
Harmonized System (HS) code: 85176990
Internal memory type: DDR2
Internal memory: 1024 MB
Flash memory: 32000 MB
Control display unit: No
Compatible operating systems: Raspberry Pi Android Linux
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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.

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