1.
Use Case: IIoT
Overview
Brian Gilmore
Director of IoT and Emerging Technologies,
InfluxData

2.
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from the InfluxDB Community
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our partners and InfluxDB engineers
Learn best practices that will
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for your projects

3.
This session explores the challenges of modernizing
industrial operations and shares insights into using
modern technologies to monitor, optimize, and predict in
the industrial IoT sector.
Brian Gilmore
Director of IoT and Emerging
Technologies, InfluxData
Brian Gilmore is Director of IoT and Emerging
Technology at InfluxData, the creators of InfluxDB. He
has focused the last decade of his career on working
with organizations around the world to drive the
unification of industrial and enterprise IoT with machine
learning, cloud, and other truly transformational
technology trends.
Use Case: IIoT Overview

4.
Agenda
1. Challenges modernizing industrial operations
2. The diminishing relevance of industrial process
historians
3. Using modern technology stacks to monitor,
optimize, and predict industrial operations

5.
Industrial IoT encompasses industrial
sectors and applications, including
robotics, smart sensors, and
software-defined production processes

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Challenges in Modernizing Industrial Operations
• Security
• Governance
• Expense
• IT/OT Misalignment
• Technology Barriers
• Contextual Enrichment
• Operational Know-how
• Tribal Knowledge
• Real-time
• Systems Integration
• Safety, Availability
Local Awareness
Domain Expertise Remote Visibility

7.
Relevance of Industrial Process Historians
The Good
• Real-time
• OT Integration
• Familiar
The Bad
• Cost
• Complexity
• Siloed
The Ugly
• IT Integration
• Slow Innovation
• Limits:
• Innovation
• Creativity
• Experimentation
• Collaboration

8.
Where we can all make an impact
• Experimentation & innovation
• Observability in IIoT
• The rise of digital natives
• The opportunity with emerging technologies
• The future of industrial operations

9.
A Different Approach to IIoT
Sensors
Metrics
Events
Transactions
Instrumentation
InfluxDB Edge Nodes
(OSS)
Functions*:
Input configuration
Input monitoring
Timestamping
Linebreaking
Whitespace handling
In-stream processing
Line Protocol Conversion
Output configuration
Output routing
InfluxDB Clusters
(Enterprise or
Cloud)
REST API Client Libraries Data Explorer Notebooks Visualizations
Time Series Applications
Monitor, Troubleshoot, Alert, Predict, Automate
Edge Datacenter Cloud
Kafka
Kinesis
CSP Pub/Sub
Cloud Native
Telegraf

10.
Getting There with InfluxDB
Data Sources
InfluxDB
Purpose-Built Time Series Database
Visualization, Query & Task Engine
Collect
Transform
Downsample
Trigger
Integrations Applications & Use Cases
Applications/Services
• SCADA (Supervisory Control and
Data Acquisition)
• MES (Manufacturing Execution
Systems)
• ERP (Enterprise Resource Planning)
• EAM (Enterprise Asset Management)
• CMMS (Computerized
Maintenance Management Systems)
Devices/Infrastructure
• PLCs (Programmable Logic
Controllers)
• HMIs (Human to Machine
Interface)
• Robotics (Assembly, Co-bots,
Logistics)
• Sensors (Legacy OT and Modern
IoT)
• Other Devices (Fab Machines, Lab
& QA)
Telegraf
• MQTT Consumer
• OPC UA
• Modbus
• HTTP
• Kafka
• AWS Kinesis
• Azure Event Hubs
• GCP Pub Sub
Client Libraries
• Python
• Arduino
• Node.js
• JavaScript
• Monitoring and Diagnostics
• Failure Detection and
Forensics
• Supervised/Intelligent
Automation
• Predictive Maintenance
• Process Optimization
• Resource Optimization
• Customer and Client Visibility
• Alerting Frameworks
Partner Solutions
• PTC Kepware
• PTC Thingworx
• Bosch CtrlX
• Siemens WinCC OA
• HighByte
Alert

11.
A Simple Stack with Unlimited Potential
Processes and Assets
Middleware
InfluxDB
Applications
Edge Cloud
Datacenter
ICS/SCADA Plant/Factory
Robotics

12.
What You Can Accomplish
Supply Chain
Optimization
New Lines of
Business
Workforce
Optimization
Cost
Reduction
Improved
Efficiency
InfluxDB

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