Monitor IoT sustainability compliance and ESG reports with OpenAI, Airtable, Slack and Gmail

Open on n8n.io

$20/month : Unlimited workflows

2500 executions/month

Try free

THE #1 IN WEB SCRAPING

Scrape any website without limits

Try free

HOSTINGER

Early Deal
DISCOUNT 20%

Self-hosted n8n

Unlimited workflows - from $4.99/mo

Try free

#1 hub for scraping, AI & automation

6000+ actors - $5 credits/mo

Try free

Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

How It Works This workflow automates IoT device compliance monitoring and anomaly detection for industrial operations. Designed for facility managers, quality assurance teams, and regulatory compli...

Best for

Engineering automation workflows
AI Summarization automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.scheduletrigger, n8n-nodes-base.set, n8n-nodes-base.code, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.if, n8n-nodes-base.slack

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Cheng Siong Chin.

Original n8n.io source

1.1 Workflow description

Title: Monitor IoT sustainability compliance and ESG reports with OpenAI, Airtable, Slack and Gmail
Workflow name: Monitor IoT sustainability compliance and ESG reports with OpenAI, Airtable, Slack and Gmail

How It Works

This workflow automates IoT device compliance monitoring and anomaly detection for industrial operations. Designed for facility managers, quality assurance teams, and regulatory compliance officers, it solves the challenge of continuously monitoring sensor networks while ensuring regulatory adherence and detecting operational issues in real-time.The system runs every 15 minutes, fetching IoT sensor data and structuring it for analysis. Dual AI agents evaluate compliance against regulatory standards and detect operational anomalies. Issues trigger immediate email and Slack alerts for rapid response. Daily data aggregates into comprehensive ESG reports with AI-generated insights, automatically emailed to stakeholders for transparency and audit trails.

Setup Steps

Configure AirTable credentials and set 15-minute schedule interval
Add OpenAI API keys for compliance and anomaly detection agents, configure regulatory thresholds
Set Gmail/Slack credentials for alerts and ESG report distribution

Prerequisites

IoT sensor platform API access, OpenAI API key, Gmail/Slack accounts

Use Cases

Manufacturing quality control, environmental compliance monitoring

Customization

Modify sensor polling frequency, adjust compliance rules, customize anomaly thresholds

Benefits

Continuous compliance assurance, instant anomaly detection

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Every 15 Minutes

Type / Role: n8n-nodes-base.scheduleTrigger - scheduleTrigger
Config choices: Version 1.3

Block 2 - Workflow Configuration

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 3 - Parse and Structure IoT Data

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 4 - Compliance Monitor Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 3.1

Block 5 - OpenAI Model - Compliance

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.3

Block 6 - Compliance Output Parser

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.3

Block 7 - Anomaly Detection Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 3.1

Block 8 - OpenAI Model - Anomaly

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.3

Block 9 - Anomaly Output Parser

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.3

Block 10 - Check for Issues

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.3

Block 11 - Prepare Alert Data

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 12 - Send Slack Alert

Type / Role: n8n-nodes-base.slack - slack
Config choices: Version 2.4

Block 13 - Aggregate Daily Data

Type / Role: n8n-nodes-base.aggregate - aggregate
Config choices: Version 1

Block 14 - ESG Report Generator

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 3.1

Block 15 - OpenAI Model - ESG Report

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.3

Block 16 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 17 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 18 - Sticky Note2

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 19 - Sticky Note4

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 20 - Sticky Note5

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 21 - Get IoT Data

Type / Role: n8n-nodes-base.airtable - airtable
Config choices: Version 2.1

Block 22 - 📧 Send Email

Type / Role: n8n-nodes-base.gmail - gmail
Config choices: Version 2.1

3. Summary Table

Workflow	Monitor IoT sustainability compliance and ESG reports with OpenAI, Airtable, Slack and Gmail
Complexity	advanced
Nodes	22
Categories	Engineering, AI Summarization
Author	Cheng Siong Chin
Published	27 Dec 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/12198/12198.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Engineering workflows AI Summarization workflows

Frequently asked questions

What does Monitor IoT sustainability compliance and ESG reports with OpenAI, Airtable, Slack and Gmail do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Engineering, AI Summarization use case.

Cheng Siong Chin

203 workflows

Nodes

n8n-nodes-base.scheduletrigger n8n-nodes-base.set n8n-nodes-base.code @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.lmchatopenai @n8n/n8n-nodes-langchain.outputparserstructured n8n-nodes-base.if n8n-nodes-base.slack

Complexity

advanced

Published 27 Dec 2025

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/12198/12198.json

Share Your Workflow

Have a useful automation to share? Publish it and help the community.

Submit Your Template How to Submit

Related Workflows

Build self-improving agent skills with cognee

## Quick overview A self-improving loop for agent skills, powered by the cognee Verified Node. When a skill's review scores below your threshold, it proposes a rewrite, and you approve the before/after diff before it's applied. No code required. ## How it works 1. Execute your workflow. 2. Set the demo inputs (skill name, dataset name, skill procedure markdown, review task text, and the score threshold). 3. Ingest the skill into cognee. 4. Cognee reviews the skill’s performance and returns a JSON with a score and gaps. 5. If the score is below the threshold, the workflow requests a cognee improvement proposal for the skill. 6. The workflow retrieves the full proposal from cognee and builds a human-readable before/after diff. 7. If the proposal is approved, the workflow applies the improvement in cognee, fetches the updated skill, and outputs the updated procedure and diff. ## Setup 1. Create a cognee API credential in n8n and use it in all cognee nodes (Ingest Skill, Review Skill, Propose Improvement, Get Proposal, Apply Improvement, Get Skill). Information for the credential (URL and API key) can be found in your Cognee Cloud account. 2. Update the skill parameters (skill_name, dataset_name, skill_markdown, task_text, score_threshold, and approved) to match your use case. 3. Ensure the referenced cognee dataset name exists so the skill can be stored and retrieved consistently.

View

Orchestrate multi-agent energy optimization with OpenAI GPT and Claude

## Quick Overview This workflow runs manually to orchestrate multi-agent analysis for a thermodynamic system, using OpenAI and Anthropic models to interpret sensor inputs, optimize energy usage, plan and execute tasks, validate results, and send an HTTP alert if validation fails. ## How it works 1. Starts when you manually trigger the workflow with initial system state, temperature, energy budget, and a task queue. 2. Uses OpenAI (GPT-5-mini) to analyze the provided sensor context, detect anomalies, and output structured sensor readings with confidence scores. 3. Uses OpenAI (GPT-5-mini) plus a calculator and custom energy-analysis code tool to compute efficiency/entropy metrics and propose an optimized energy allocation. 4. Uses OpenAI (GPT-5-mini) to build an execution plan and energy estimate for the queued tasks based on the optimized budget and sensor state. 5. Uses Anthropic (Claude Sonnet) to execute the planned task sequence within the estimated energy limit and return structured outcomes and actual energy usage. 6. Uses Anthropic (Claude Sonnet) to validate thermodynamic compliance by comparing planned vs. actual energy and generating recommendations. 7. If validation passes, compiles a final system report and returns the final system state; if validation fails, generates recalibration parameters and posts a JSON alert to an external webhook endpoint. ## Setup 1. Add credentials for OpenAI (Chat) and Anthropic (Chat) so the Perception, Energy Optimization, Planning, Execution, Validation, and Recalibration agents can run. 2. Replace the placeholder alert webhook URL in the HTTP Request step and configure HTTP Header Auth credentials for the target alerting endpoint. 3. Provide the required input fields on trigger (systemState, temperature, energyBudget, and taskQueue) or adjust the prompts to match your data structure. 4. If your execution step needs real environment context, add or connect a node that supplies the referenced environment data (the workflow currently references “Fetch Environment Data” but does not include it).

View

Optimize maritime routes and disruption response with OpenAI and Slack

## Quick Overview This workflow runs every 15 minutes to pull vessel telemetry/AIS data, enrich it with port and weather context, and use OpenAI to detect disruptions, simulate route alternatives, and generate an executive briefing that requires human approval before notifying teams in Slack. ## How it works 1. Runs every 15 minutes on a schedule. 2. Fetches fleet vessel telemetry and AIS data from a configured HTTP API. 3. Retrieves weather forecast and port congestion context for each vessel/route from a second HTTP API. 4. Uses OpenAI to analyze telemetry against historical baselines and classify any operational anomalies with severity and confidence. 5. Uses OpenAI to aggregate anomaly, weather, and port context into risk factors, urgency, and an action category. 6. Uses OpenAI to simulate 2–3 routing and speed options, estimating cost, emissions, fuel, duration, and weather risk, and selects a recommended route. 7. Generates an executive briefing with compliance and master-authority notes, pauses for human approval via an n8n form, and then posts the decision and recommendation to a Slack channel. ## Setup 1. Add OpenAI API credentials for the three OpenAI chat model steps. 2. Configure HTTP Header Auth credentials and replace the placeholder URLs and query parameters for your AIS/telemetry API and your weather/port API. 3. Ensure the upstream APIs return the fields referenced in the prompts (for example position, speed, fuel consumption, historical baselines, forecast, and port congestion). 4. Connect a Slack OAuth2 credential and select the target channel for posting the approved briefing. 5. Test the approval form step in n8n and confirm who will receive and complete approvals before enabling the workflow.

View

Need Custom Automation?

Get help designing a custom n8n workflow that connects your stack and fits your process.

Monitor IoT sustainability compliance and ESG reports with OpenAI, Airtable, Slack and Gmail

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

How It Works

Setup Steps

Prerequisites

Use Cases

Customization

Benefits

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Every 15 Minutes

Block 2 - Workflow Configuration

Block 3 - Parse and Structure IoT Data

Block 4 - Compliance Monitor Agent

Block 5 - OpenAI Model - Compliance

Block 6 - Compliance Output Parser

Block 7 - Anomaly Detection Agent

Block 8 - OpenAI Model - Anomaly

Block 9 - Anomaly Output Parser

Block 10 - Check for Issues

Block 11 - Prepare Alert Data

Block 12 - Send Slack Alert

Block 13 - Aggregate Daily Data

Block 14 - ESG Report Generator

Block 15 - OpenAI Model - ESG Report

Block 16 - Sticky Note

Block 17 - Sticky Note1

Block 18 - Sticky Note2

Block 19 - Sticky Note4

Block 20 - Sticky Note5

Block 21 - Get IoT Data

Block 22 - 📧 Send Email

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions