Features & Benefits:
• Conforms to BACnetTM Standard 135 protocol version 1.15 (ISO 16484-5)
• Multi-color LEDs to show the operational status of the isolated RS485
communications, HMI device, Ethernet connection, and Service state of the
controller
• Multiple Ethernet connector options
• RJ11 interface to connect with an HMI device for field operations
• All RS485 channels support PanelBus, BACnetTM MS/TP, Modbus, and M-Bus
• Support C-Bus data sharing

• Touchflake to support RS485 Snapon I/O devices
• Built-in advanced diagnostics software facilitating troubleshooting for IP and
MSTP devices
• WIFI models are available and configurable for Client Mode or Access Point Mode.
When setup as a Client, this allows the controller to connect to WIFI networks as a
discoverable device to minimize cables to the controller. When setup as an Access
Point, the controller broadcasts a secure WIFI connection and when established,
provides secure engineering access to the controllers on the network with up-to-date
security protocols to ensure robust system security. This is ideal for installations
where physical patch points are limited or inaccessible
• FRAM to store the live data for the controller, including storing the last known
values when power is removed
• UTF-8 and UCS-2 character encoding formats are supported
• Support Peer-to-Peer communication
• Supports DHCP (Automatic IP address assignment)
• Supports Daisy-chain connection
• Supports full Niagara 4 Framework with FOX and Fox-S communications, N4 Drivers
and Interfaces
• Removable terminal blocks with Screw (factory installed) or Push-in terminals
• Built-in Web server with HTML5 graphics support
• Terminal covers to protect the terminals
• Protective covers to protect the Touchflake and Snapon I/O
• i.MX 8M Plus, quad Arm® Cortex®-A53 processor, long life industrial grade,
Frequency: 1.2GHz
• Ubuntu Core OS with snap container based modular software design (Cyber Secure)
• Support for Azure IOT remote device management and update services
• Neural Net Accelerator for future development of low latency AI/ML algorithms
at the Edge
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