Litmus: Foundation (Device Data Collection & Analytics)IOT System
DescriptionLitmus is the Edge Data Platform purpose-built for Industry 4.0. With instant connectivity to hundreds of OT assets, Litmus Edge makes it easy to harness the OT data needed to power insights at the edge and across the enterprise. From data collection and machine analytics to application enablement and data integration, Litmus is a complete Edge Data Platform platform that is rapid-to-deploy and easy-to-use, offering everything you need to improve operations at scale.
- One Platform: Everything you need for Industry 4.0 including complete OT connectivity, machine analytics, data integration and application enablement.
Device Connectivity: Rapidly collect and normalize data from any modern or legacy OT asset into a standard format ready for use by edge and enterprise applications.
Machine Analytics: Access pre-built or custom data visualizations, KPI dashboards, and analytics at the edge to improve OEE, reduce downtime and optimize throughput.
Application Enablement: Host applications in a public or private marketplace, rapidly deploy them using containers at the edge, and run them with complete OT data.
Data Integration: Easily and securely integrate data between OT and IT using pre-built integrations to dozens of cloud and enterprise systems.
Flexible Deployments: Deploy easily into any OT or IT infrastructure – run on any edge gateway, virtual machine or container (Docker, Kubernetes, etc).
IoT Solution Application
Ships with hundreds of OT device drivers
With 250+ pre-built drivers, Litmus can connect to any machine or industrial system out-of-the-box. Collected data is structured and stored, and ready for use by edge and enterprise applications.
- Connect any asset – PLC, CNC, SCADA, MES, Historian
- Pre-loaded drivers, no programming required
- Normalize hundreds of custom data points
Pre-build machine analytics and visualizations
With pre-built KPIs and an easy-to-use dashboard builder, customers can quickly create data visualizations and analytics for machine downtime, condition monitoring, OEE and more.
- Analyze data at the edge for instant value
- Pre-built analytics dramatically reduce setup time
- Drag and drop KPIs to build custom dashboards
Integration with cloud and enterprise systems
Immediately feed ready-to-use machine data to any cloud or enterprise system to achieve a complete edge-to-cloud data picture for OT, IT and Data Science teams.
- Normalized data can be used by any application
- Simple drag-and-drop editor to send data anywhere
- 20+ pre-built connectors to cloud and enterprise systems
Containerized application deployment
Host and access public or private applications in a centralized repository, with the ability to deploy and run applications and machine learning models at the edge.
- Access a default set of 45+ pre-loaded applications
- Host any type of custom application or model
- Use containers to deploy applications and models rapidly
Scalable and repeatable IIoT deployments
Achieve a single point of control to view and manage a complete picture of edge devices, data and applications at scale.
- Remotely configure, update and monitor all IIoT devices
- Visualize data from all devices and factories
- Create an ideal configuration template for repeatable deployment
Simplify the management of Industrial IoT deployments
Litmus Edge Manager is a centralized edge management platform purpose-built to give edge and enterprise teams visibility, access and control over the orchestration of all edge devices, data, applications and machine learning models at scale. Visualizing data from all sites and centrally deploying applications leads to exponential opportunities to drive efficiency and operational improvement. Litmus Edge Manager makes it easy to create deployment templates and send over-the-air-updates for fast, easy and secure IIoT at scale.
- Single Point of Control: Simplify the management of IIoT deployments at scale with centralized visibility and control of devices, data, applications and machine learning models.
- Device Management: Control, configure, update and monitor IIoT devices across all sites remotely to remove the need for on-site management.
- Data Management: Visualize OT data from any site and integrate data to any enterprise system to power advanced analytics and applications.
- Application Orchestration: Run containerized applications on any Litmus Edge device with centralized control over how they are hosted, deployed and updated.
- ML Model Orchestration: Host and manage machine learning models in a central repository. Deploy models to Litmus Edge devices at any number of sites, and run them using Docker containers.
- Flexible Deployment: Install Litmus Edge Manager in the data center, cloud (Google Cloud, Azure, AWS, etc) or on-premise next to IIoT devices.
IoT Solution Specification
Litmus Platform Capabilities
Under the hood, Litmus is the most complete Industrial IoT Edge platform on the market – providing everything industrial companies need to collect and put data to work at the edge and across the enterprise. First, Litmus Edge collects and unifies all OT data – from vision systems to flat files to PLCs and DCS – and normalizes and stores the ready-to-use-data. Customers can engineer the data with common KPIs and visualization for valuable machine analytics and immediate value or send data anywhere for advanced analytics. Applications and machine learning models are fed with complete OT data and deployed at the edge with container technology. Litmus Edge Manager adds a management and orchestration layer for device, data, application and ML model management at any scale.
Litmus Edge Platform Features
- Native Device Drivers: Access 250+ pre-built device drivers – the most in the industry. Our patented technology enables the rapid development of new drivers.
- Data Normalization: Collect and structure various OT data types and formats into a standard JSON file ready to be used for analytics and applications.
- Data Storage: Store normalized data in a scalable and secure time-series database with the option to integrate with any enterprise storage platform.
- Data Engineering: Create data workflows, define data actions, debug data, set up alerts and visualize metadata with a drag-and-drop data processing engine.
- Pre-Built KPIs: Improve OEE, machine uptime and production quality using pre-built or custom KPIs to track production time, change of value, anomaly detection, signal loss, and more.
- Data Visualization: Quickly set up data visualizations and dashboards for OT teams to monitor production. The platform uses Grafana or works with any other data visualization tool.
- Application Marketplace: Access a library of pre-populated applications or add custom applications to a private marketplace to quickly run them at the edge using containers inside the platform.
- Solution Marketplace: Utilize vertical-specific applications for automotive, food & beverage, and more – designed and validated to accelerate deployment times and reduce complexity.
- Application Runtime: Run any number of applications in a controlled and secure runtime environment using Docker container technology embedded inside the platform.
- OT/IT Connectors: Integrate data rapidly with 20+ pre-built OT-IT connectors to Microsoft, AWS, Google, Cloudera and other systems via MQTT, REST API and Kafka.
- Data Streaming: Stream complete or select OT data in any format to data teams and systems to support machine learning and other IT initiatives.
- ML Runtime: Run any machine learning model trained by any machine learning system at the edge using container technology embedded inside the platform.
Litmus Edge Manager Platform Features
- Device Configuration: Set up and configure IIoT devices remotely and create templates for rapid deployment to tens or hundreds of sites.
- Device Support: Streamline IIoT device support with the ability to remotely manage, change configurations, troubleshoot, and send over-the-air updates.
- Data Storage: Aggregate data from multiple Litmus Edge deployments in one place and allow other applications to access the data
- Data Visualization: Quickly visualize real-time data across all devices and factories with configurable dashboards and KPI reports
- Application Library: Create a global application library, decide which applications should be deployed at which sites, and control who has access.
- Application Deployment: Create a containerized application and deploy, manage, and update it to any number of Litmus Edge deployments.
- ML Model Repo: Create a centralized repository of machine learning models accessible to any production line or site.
- ML Model Deployment: Containerize machine learning models, deploy them to any number of sites, and make updates for continuous learnings.
The following table lists the recommended hardware requirements for a client connecting to the Litmus Edge appliance:
For this hardware
Use this requirement
Quadcore Intel Gen7 or better
8 GB RAM minimum
128 GB for local storage
Ideal to set to UTC time to prevent any time synchronization issues
2 dedicated to separate IT and OT network
2 or more