IIoT: Industrial Internet of Things
An Industry Brief
What is IIoT?
What is the Purpose of IIoT?
IIoT focuses on machine-to-machine communications, enabling processes to be optimized and automated. These connected devices communicate through gateways, which are physical servers that filter data, and transmit it to other devices and software applications.
IIoT permits Information Technology (IT)/Operational Technology (OT) convergence; enabling more direct control and more complete monitoring, with easier analysis of data from these complex systems, from anywhere in the world. This allows users to do their jobs more efficiently and improves decision-making, as they have access to real-time insights that the data provides.
It is great to have all these devices connected, communicating and transferring data, but understanding the efficiency and effectiveness of these devices and their data in transient requires a comprehensive, top-of-the-line, AI-powered data monitoring and analytics solution. Those manufacturers taking advantage of the advanced analytics and connectivity are gaining a competitive edge. They are leveraging data and analytics from advanced hardware combined with advanced software and data from sensors results in smarter products and processes and an opportunity to increase profitability.
Enter Sightline EDM.
Sightline EDM™ for IIoT & Utilities is used for industrial and manufacturing data collection & intelligence that is unified in one easy to use IIoT 4.0 platform.
Highlights of Sightline EDM include:
Real-Time Predictive Analytics
Live data collection, visualization, monitoring & advanced analytics tools give you live visibility across facilities & production, improving profitability across operations.
Advanced Anomaly Detection
Using historical baselines for production and customized alerting algorithms, the system flags potential issues as they happen & helps determine statistical significance, potentially saving production downtime and labor.
Root Cause Analysis
With live data from production across different facilities, the context of past performance & issues, and drill-down details, resolve issues within minutes and decrease time to fix the problem.
Capacity Planning & Forecasting
Automate the capacity planning process for customized reports & alerts, identify resource bottlenecks, forecast labor or production capacity constraints, and prevent downtime across facilities & systems.
SIAS End-to-End Data Security
Industry 4.0 & smart factories are facing unprecedented security threats; protect against cyber risks and respond faster to threats using a “zero trust” policy with end point device cloaking, cryptographic zoning, data encryption, and dynamic isolation to secure, detect, and respond in real-time.
For more on Sightline visit us at www.sightline.com
MQTT (Message Queueing Telemetry Transport) is a simple, lightweight message publishing and subscribing network protocol. It is the standard protocol for Internet of Things (IoT) and Industry 4.0 messaging.
It is lightweight, low bandwidth, and functions well in high latency and unreliable environments, making it ideal in production environments. Devices send data (publish) to an MQTT Broker with a topic and a data payload, and devices can subscribe to that topic and subtopics and receive updates containing that data from the broker when the data changes. Topics can be defined to use several levels of depth and devices can subscribe to topics using wildcards allowing for dynamic changes when required. Continue Reading MQTT Protocol
Zero-Trust is a security concept and cybersecurity framework allowing an organization to aggressively defend itself, its data, and user permissions using an advanced system of automated security protocols. Zero-Trust is centered on the belief that organizations should not automatically trust anything inside or outside their perimeters and instead must verify anything and everything trying to connect to their systems before granting access. Continue Reading Zero-Trust Data Security
The EDM Correlation data analysis tool is designed to help users perform root cause analysis across multiple devices or systems. It compares the activity of one system over a given period with the activity of multiple other systems and identifies the most highly related data points. This allows EDM to create an intuitive visualization of related events across an entire network of mixed technology enabling root cause analysis to be performed more efficiently than ever before. Continue Reading Data Correlation
Forecasting uses historical data as inputs to make informed estimates that are predictive in determining the direction of future trends. Choosing appropriate forecasting techniques depends on the type of data being used and behavior of the data. For example, forecasting techniques used for “financial data” may not be appropriate for time series data like “computer server data” or “data center network activity data” (though underlying forecasting principles stay the same). Continue Reading Data Forecasting