IND360 integration with MQTT

Connect the Mettler Toledo IND360 weighing controller to MQTT and stream live weight data into Node-RED and Ignition SCADA. No OPC license. No custom driver. Just MQTT.

In this video and guide, we explore how IND360 can be seamlessly integrated via MQTT with:

• Node-RED: A flow-based, low-code programming tool for wiring together hardware, APIs, and online services, ideal for rapid IIoT prototyping. 🔗 https://nodered.org/docs/getting-started/local

• Ignition by Inductive Automation is an industrial application platform for building SCADA, HMI, and IIoT solutions with unlimited clients and a web-based deployment model. 🔗 https://inductiveautomation.com/downloads/ignition

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📺 Video Tutorial

https://youtu.be/7Ml6OcBUadAyoutu.be

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🔑 What You Will Learn in This Video

In this hands-on demo, you will learn:

• How to connect IND360 with Node-RED and Ignition SCADA using MQTT

• How to read weight & status data in real time

• How to send commands such as:

  • Zero scale

  • Tare scale

  • Preset tare

  • Clear tare

• How to log the feedback in the database

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Prerequisites

Requirement	Details	Status
Mettler Toledo IND360	With network access via Ethernet	● Required
MQTT Broker	Shiftr (for testing) or Ignition Distributor	● Required
Node-RED	Installed locally or on server	Use Case 1
Ignition Gateway	Standard edition v8.3.4+	Use Case 2
Cirrus Link Modules	MQTT Distributor + MQTT Engine	Use Case 2

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1. MQTT Broker Setup

Before connecting the IND360, you need a running MQTT broker. For initial testing, we use Shiftr, an MQTT broker with a visual connection map.

For production use, Ignition's built-in broker is used.

1

Download and install the Shiftr desktop app

Visit https://www.shiftr.io/desktop and install the broker locally.

2

MQTT Broker parameters

Note the MQTT port address

3

Verify port 1883 is open

Open PowerShell and run the commands below.

# Verify Port is Open and Listening
netstat -ano | findstr :1883

# Find Which App Owns the Port
tasklist -ano | findstr <pid>

# Open port 1883 in Windows Firewall
New-NetFirewallRule -DisplayName "MQTT Broker" -Direction Inbound -Protocol TCP -LocalPort 1883 -Action Allow

Important — Firewall

If the IND360 cannot connect via IP address, the Windows Firewall is blocking port 1883. Run the PowerShell command above to open it.

2. Enabling MQTT on IND360

In this step, we need to enable the MQTT service on the IND360 device.

1

Open the IND360 web interface

Navigate to https://192.168.0.8 (replace with your IND360 IP) and login using 002.

2

Navigate to MQTT settings

Go to Communication → Service and find the MQTT section.

3

Configure MQTT parameters

Fill in all fields as shown in the table below.

Parameter	Value	Notes
Client ID	IND360	Unique identifier for this device
Host	192.168.0.24	IP of your broker machine
Port	1883	Standard MQTT port
Topic		Root topic prefix
Username		Must match broker user
Supervision	Enabled	Enables keep-alive monitoring

Topic Structure

The IND360 automatically appends its serial number and sub-paths to the root topic. For example: ind360/devices/C249346600/scales/_/measurements

4

Click SET, then CONNECT

Status should change to Connected.

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3. Testing with Shiftr

Use Shiftr's visual broker map to confirm the IND360 is publishing data before integrating with Node-RED or Ignition.

Open the Shiftr dashboard to visualize the data flowing from the IND360 device

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Use Case 1: Node-RED Integration

Use Node-RED as a lightweight MQTT client to read live weight data and send commands to the IND360 via the Shiftr broker.

Reading Weight Data

Subscribe to the measurements topic to receive live weight data as a JSON array.

• ind360/devices/C249346600

• ind360/devices/C249346600/alarms

• ind360/devices/C249346600/scales/_

• ind360/devices/C249346600/scales/_/measurements

//function 21
msg.payload = msg.payload[0].gross + ' ' + msg.payload[0].uomCode;
return msg;

//function 22
msg.payload = msg.payload[0].net;
return msg;

//function 23
msg.payload = msg.payload[0].tare + ' ' + msg.payload[0].uomCode;
return msg;

Sending Commands

Each command follows the same pattern — an Inject node triggers a Function node that builds the payload, which is then published via an MQTT Out node.

Command	Description	Topic
tare	Sets net weight to zero using current gross as tare offset	Invoke: ind360/devices/C249346600/commands/tare/invoke Result: ind360/devices/C249346600/commands/tare/result
tare-clear	Removes the tare offset, gross equals net again	Invoke: ind360/devices/C249346600/commands/tare-clear/invoke Result: ind360/devices/C249346600/commands/tare-clear/result
zero	Sets current gross weight as the new zero reference point	Invoke: ind360/devices/C249346600/commands/zero/invoke Result: ind360/devices/C249346600/commands/zero/result
tare-preset	Applies a manually entered known tare value	Invoke: ind360/devices/C249346600/commands/tare-preset/invoke Result: ind360/devices/C249346600/commands/tare-preset/result

Tare Command — Function Node

msg.payload = {
    "$correlation": "TareTest1",   // Unique ID to track this request
    "$ttl": 42,                   // Time-to-live in seconds
    "responseTopic": null,         // Set null if no response topic needed
    "command": "tare",             // Command to execute
    "content": null               // Not required for tare
}
return msg;

Clear Command — Function Node

msg.payload =
{
    "$correlation": "TareTest1",
    "$ttl": 42,
    "responseTopic": null,
    "command": "tare-clear",
    "content" : null
}
return msg;

Zero Command — Function Node

msg.payload =
{
    "$correlation": "Zero-Test1",
    "$ttl": 42,
    "responseTopic": null,
    "command": "zero",
    "content" : null
}
return msg;

Preset Tare Command — Function Node

msg.payload = {
    "$correlation": "Tare-PresetTest1",
    "$ttl": 42,
    "responseTopic": null,
    "command": "tare-preset",
    "content": {
        "value": "2.0",             // Preset tare value
        "unit": "Kg"               // Unit — must match scale config
    }
}
return msg;

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Dashboard

You can use the dashboard 2.0 to visualize your value as shown below. Feel free to use the NodeRed flow for a ready-to-use dashboard.

27KB

node-red_flow.json

Open

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Use Case 2: Ignition Integration

Ignition acts as both the MQTT broker (via MQTT Distributor) and the subscriber (via MQTT Engine). No external broker needed.

1

Install Ignition

Sign up for an account, download, and install Ignition. https://inductiveautomation.com/

2

Install MQTT Modules

Visit https://inductiveautomation.com/downloads/third-party-modules/8.3.4 — Match the version to your Ignition installation.

Install via Gateway → Platform → Modules

Module	Role	Port
MQTT Distributor	Acts as the MQTT broker inside Ignition	1883
MQTT Engine	Subscribes and converts MQTT data to Ignition tags	—

3

Configure MQTT Distributor

Gateway → Connections → MQTT Distributor → Settings

Enable the distributor and verify that the port is set to 1883.

Create broker users

Go to Users and create two accounts:

Username	Password	Used by
ind360	ind360	IND360 device
ignition	ignition	MQTT Engine internal connection
nodered	nodered	(Optional) For Node-RED to subscribe and publishdata

4

Configure MQTT Engine

Gateway → Connections → MQTT Engine → Servers → Add Server

Field	Value
URL	tcp://192.168.0.24:1883
Server Set	Default Set
Username	ignition
Password	ignition

5

Create Custom Namespace

Why a Custom Namespace?

MQTT Engine's default namespaces (Sparkplug B and Elecsys) expect specific structured payload formats. The IND360 publishes plain JSON — so we must create a custom namespace that tells the Engine how to parse and tag the incoming data.

Gateway → MQTT Engine → Namespaces → Custom → Create New

Field	Value	Notes
Namespace Name	IND360	Unique identifier
MQTT Topic	#	Wildcard captures all sub-topics
Root Folder	IND360_folder	Tag browser folder name
JSON Payload	✅ Checked	Auto-parses JSON into tags
Create Writable Tags	✅ Checked	Enables writing back to device

6

Dashboard & Commands

Once tags appear in the Tag Browser under MQTT Engine, bind them to Vision components for live display.

Useful scripts

Below are the scripts that are used for publishing the data to the MQTT broker via buttons

Tare Button Script

import json

# Build the tare command payload
payload = json.dumps({
    "$correlation": "IgnitionTare1",   # Unique ID to track this request
    "$ttl": 42,                        # Time-to-live in seconds
    "responseTopic": None,             # No response topic needed
    "command": "tare",                 # Command to execute on IND360
    "content": None                   # Not required for tare
})

# Publish to IND360 via Ignition MQTT Engine
system.cirruslink.engine.publish(
    "Ignition Distributor",                                     # Server name in MQTT Engine → Servers
    "ind360/devices/C249346600/commands/tare/invoke",           # Command topic
    payload.encode(),                                           # Must be bytes — .encode() converts string
    1,                                                          # QoS 1 = at least once delivery
    False                                                       # Retain = False
)

The payload must be byte-encoded using .encode(). Passing a plain string causes a silent failure; no error is shown, but the command is never published. Learn more about Python scripting here: https://docs.chariot.io/display/CLD80/ME%3A+Python+Scripting

Clear Button Script

import json

# Build the tare-clear command payload
# Tare-clear resets the tare back to zero (removes the tare offset)
payload = json.dumps({
    "$correlation": "IgnitionClear1",  # Unique ID to track this request
    "$ttl": 42,                        # Time-to-live in seconds before message expires
    "responseTopic": None,             # Set to None if no response topic is needed
    "command": "tare-clear",           # The command to execute — clears the existing tare value
    "content": None                    # Additional content — not required for tare-clear command
})

# Publish the clear command to the MQTT broker via Ignition MQTT Engine
system.cirruslink.engine.publish(
    "Ignition Distributor",                                        # MQTT server name as configured in MQTT Engine > Servers
    "ind360/devices/C249346600/commands/tare-clear/invoke",        # MQTT topic — tare-clear command path for device C249346600
    payload.encode(),                                              # Payload must be bytes — .encode() converts string to bytes
    1,        

Zero Button Script

import json

# Build the zero command payload as a Python dictionary
# Zero command sets the current scale reading as the new zero reference point
payload = json.dumps({
    "$correlation": "IgnitionZero1",   # Unique ID to track this request (can be any string)
    "$ttl": 42,                        # Time-to-live in seconds before message expires
    "responseTopic": None,             # Set to None if no response topic is needed
    "command": "zero",                 # The command to execute on IND360 (zero = set current weight as new zero)
    "content": None                    # Additional content — not required for zero command
})

# Publish the zero command to the MQTT broker via Ignition MQTT Engine
system.cirruslink.engine.publish(
    "Ignition Distributor",                                    # MQTT server name as configured in MQTT Engine > Servers
    "ind360/devices/C249346600/commands/zero/invoke",          # MQTT topic — device serial number C249346600 is part of the path
    payload.encode(),                                          # Payload must be bytes — .encode() converts string to bytes
    1,                                                         # QoS level 1 = at least once delivery (reliable)
    False                                                      # Retain flag — False means broker won't store this message
)

Preset Tare Button Script

• Take an input field and rename that to 'presetTare'

• Add the script below to the Preset Tare button.

import json

# Read the preset value from the input field on the dashboard
preset_value = event.source.parent.getComponent("presetTare").value

if preset_value <= 0:
    system.gui.messageBox("Please enter a valid preset tare value", "Invalid Input")
else:
    payload = json.dumps({
        "$correlation": "IgnitionPresetTare1",
        "$ttl": 42,
        "responseTopic": None,
        "command": "tare-preset",
        "content": {
            "value": str(preset_value),     # Dynamic value from input field
            "unit": "Kg"
        }
    })
    system.cirruslink.engine.publish(
        "Ignition Distributor",
        "ind360/devices/C249346600/commands/tare-preset/invoke",
        payload.encode(), 1, False
    )

7

Feedback Logging to Database

Log real device confirmation to SQLite using a Gateway Tag Change script triggered by the result timestamp.

Create Database Table

First, create a table in the default database. Run the following script in the Tools > Database Query browser.

CREATE TABLE IF NOT EXISTS ind360_command_log (
        id          INT AUTO_INCREMENT PRIMARY KEY,
        command     TEXT,
        result      TEXT,
        timestamp   TEXT
    )

To delete the table, use the following script

Drop table <table name>

Gateway Tag Change Script:

tare_result

Watch tag: [MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/tare/result/_timestamp

def onTagChange(initialChange, newValue, previousValue, event, executionCount):
	
    # Get raw IND360 timestamp e.g. "2026-04-28T11:45:41.000Z"
    raw_timestamp = str(newValue.value)

    # Convert ISO 8601 format to SQLite compatible format
    # Replace the T separator with a space and remove the Z suffix
    clean_timestamp = raw_timestamp.replace("T", " ").replace("Z", "")
    # Result: "2026-04-28 11:45:41.000" ✅

    # Read result fields from MQTT Engine tags
    description = system.tag.readBlocking([
        "[MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/tare/result/content/description"
    ])[0].value

    code = system.tag.readBlocking([
        "[MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/tare/result/code"
    ])[0].value

    correlation = system.tag.readBlocking([
        "[MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/tare/result/_correlation"
    ])[0].value

    # Log to database with cleaned SQLite compatible timestamp
    system.db.runPrepUpdate(
        "INSERT INTO ind360_command_log (command, result, timestamp) VALUES (?, ?, ?)",
        ["tare", description, clean_timestamp],
        database="Sample_SQLite_Database"
    )

clear_result

Watch tag: [MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/clear/result/_timestamp

def onTagChange(initialChange, newValue, previousValue, event, executionCount):
	
    # Get raw IND360 timestamp e.g. "2026-04-28T11:45:41.000Z"
    raw_timestamp = str(newValue.value)

    # Convert ISO 8601 format to SQLite compatible format
    # Replace the T separator with a space and remove the Z suffix
    clean_timestamp = raw_timestamp.replace("T", " ").replace("Z", "")
    # Result: "2026-04-28 11:45:41.000" 

    # Read result fields from MQTT Engine tags
    description = system.tag.readBlocking([
        "[MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/tare-clear/result/content/description"
    ])[0].value

    code = system.tag.readBlocking([
        "[MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/tare-clear/result/code"
    ])[0].value

    correlation = system.tag.readBlocking([
        "[MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/tare-clear/result/_correlation"
    ])[0].value

    # Log to database with cleaned SQLite compatible timestamp
    system.db.runPrepUpdate(
        "INSERT INTO ind360_command_log (command, result, timestamp) VALUES (?, ?, ?)",
        ["clear", description, clean_timestamp],
        database="Sample_SQLite_Database"
    )

zero_result

Watch tag: [MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/zero/result/_timestamp

def onTagChange(initialChange, newValue, previousValue, event, executionCount):
	
    # Get raw IND360 timestamp e.g. "2026-04-28T11:45:41.000Z"
    raw_timestamp = str(newValue.value)

    # Convert ISO 8601 format to SQLite compatible format
    # Replace the T separator with a space and remove the Z suffix
    clean_timestamp = raw_timestamp.replace("T", " ").replace("Z", "")
    # Result: "2026-04-28 11:45:41.000" ✅

    # Read result fields from MQTT Engine tags
    description = system.tag.readBlocking([
        "[MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/zero/result/content/description"
    ])[0].value

    code = system.tag.readBlocking([
        "[MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/zero/result/code"
    ])[0].value

    correlation = system.tag.readBlocking([
        "[MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/zero/result/_correlation"
    ])[0].value

    # Log to database with cleaned SQLite compatible timestamp
    system.db.runPrepUpdate(
        "INSERT INTO ind360_command_log (command, result, timestamp) VALUES (?, ?, ?)",
        ["zero", description, clean_timestamp],
        database="Sample_SQLite_Database"
    )

preset_tare

Watch tag: [MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/tare-preset/result/_timestamp

def onTagChange(initialChange, newValue, previousValue, event, executionCount):
	
    # Get raw IND360 timestamp e.g. "2026-04-28T11:45:41.000Z"
    raw_timestamp = str(newValue.value)

    # Convert ISO 8601 format to SQLite compatible format
    # Replace the T separator with a space and remove the Z suffix
    clean_timestamp = raw_timestamp.replace("T", " ").replace("Z", "")
    # Result: "2026-04-28 11:45:41.000" ✅

    # Read result fields from MQTT Engine tags
    description = system.tag.readBlocking([
        "[MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/tare-preset/result/content/description"
    ])[0].value

    code = system.tag.readBlocking([
        "[MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/tare-preset/result/code"
    ])[0].value

    correlation = system.tag.readBlocking([
        "[MQTT Engine]IND360_folder/ind360/devices/C249346600/commands/tare-preset/result/_correlation"
    ])[0].value

    # Log to database with cleaned SQLite compatible timestamp
    system.db.runPrepUpdate(
        "INSERT INTO ind360_command_log (command, result, timestamp) VALUES (?, ?, ?)",
        ["tare", description, clean_timestamp],
        database="Sample_SQLite_Database"
    )

Table SQL Query Binding

To visualize the feedback in the table. Add a table to your screen and bind the data with the following script

SELECT
    command   AS Command,
    result    AS Result,
    timestamp AS Timestamp
FROM ind360_command_log
ORDER BY datetime(timestamp) DESC
LIMIT 50

Clear button

To clear the values in the table, you can use the following script

# Show confirmation dialog before clearing
# Prevents accidental deletion of command history
result = system.gui.confirm(
    "Are you sure you want to clear all feedback records?",
    "Clear Feedback Table"
)

# Only delete if operator clicked Yes
if result:
    system.db.runUpdateQuery(
        "DELETE FROM ind360_command_log",
        database="Sample_SQLite_Database"
    )

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Topic Structure Reference

ind360/
├── devices/C249346600/
│ ├── scales/_/measurements #subscribe
│ ├── scales/_ #subscribe
│ ├── alarms #subscribe
│ └── commands/
│ ├── tare/invoke #publish
│ ├── tare/result #subscribe
│ ├── tare-clear/invoke #publish
│ ├── tare-clear/result #subscribe
│ ├── zero/invoke #publish
│ ├── zero/result #subscribe
│ ├── tare-preset/invoke #publish
│ └── tare-preset/result #subscribe

Command Payload Reference

Command	content field	Notes
tare	null	No content needed
tare-clear	null	No content needed
zero	null	No content needed
tare-preset	{"value": "2.0", "unit": "Kg"}	Value and unit required

Ignition Project

You can import this project in your Ignition designer to use it as a prototype:

48KB

IND360_2026-04-30_1650.zip

archive

Open

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Key notes:

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♥️ Work With Me

I regularly test industrial automation and IIoT devices. If you’d like me to review your product or showcase it in my courses and YouTube channel:

📧 Email: [email protected] or drop me a message on LinkedIn