Unlocking the Power of IIoT: Transforming Industries with Industrial Internet of Things
In the realm of process control, the Industrial Internet of Things (IIoT) stands as a game-changer, offering unprecedented opportunities for optimizing operations, enhancing productivity, and ensuring robust decision-making. In this blog, we focus on the pivotal role of IIoT in process control, delving into its core principles, real-world applications, and the transformative impact it brings to industries dependent on precise control systems. From manufacturing and chemical processing to utilities and beyond, explore how IIoT is reshaping process control, and gain valuable insights into the future of interconnected industrial systems. Join us in unlocking the immense potential of IIoT for a revolution in process control.
Challenges in Implementing IIoT Systems
1. Communication Bandwidth: One of the primary challenges in IIoT is ensuring reliable and high-speed communication between a multitude of connected devices. Industrial environments often require real-time data transfer for critical processes. Limited bandwidth can lead to data bottlenecks and latency issues, potentially affecting operational efficiency. We must invest in robust communication infrastructure, communication protocols and algorithms to support the growing number of connected devices and the data they generate. 2. Security: Security remains a paramount concern in IIoT implementations. The vast network of interconnected devices creates numerous entry points for cyber threats. Protecting sensitive data, ensuring the integrity of control systems, and preventing unauthorized access are constant challenges. Implementing strong encryption, regular security audits, and best practices for device authentication are crucial steps to mitigate these risks. 3. Interoperability: IIoT ecosystems often involve devices and systems from various manufacturers, each using different communication protocols and data formats. Ensuring seamless interoperability among these heterogeneous components can be challenging. Standardization efforts, such as the adoption of common communication protocols like MQTT and OPC UA, are essential to enable devices to communicate and share data effectively. In addition, the solutions must be able to interface with the existing communication protocols such DNP3.0, Modbus or SNMP. 4. Cloud Resources: Many IIoT applications leverage cloud computing for data storage, analysis, and scalability. While the cloud offers significant benefits, such as flexibility and cost savings, it also introduces challenges related to data privacy, latency, and dependency on external resources. We must carefully assess their cloud requirements and implement strategies to address these challenges, such as edge computing for low-latency processing and data storage.
Industrial Internet of Things (IIoT) stands as a game-changer, offering unprecedented opportunities for optimizing operations, enhancing productivity, and ensuring robust decision-making
Avista rIoT Technology
History and Background
The Avista Realtime Systems team behind the suite of IoT applications brings extensive experience in SCADA and real-time data communication applications spanning several years. One of the team's standout achievements involved spearheading the development of the core infrastructure for a power distribution automation system serving one of the largest electric utilities in the United States. This system efficiently caters to approximately 1.5 million customers and manages communication across nearly 4,000 remote pole-mounted distribution devices. It does so through a sophisticated hybrid network, incorporating radio, mesh, fiber, and cellular technologies.
While this project achieved remarkable success, it's important to note that only a limited number of organizations worldwide possess the financial resources and in-house expertise required to undertake such ambitious initiatives. Recognizing this, Avista adopted a vision to deliver a comparable set of features and functionalities in a manner that is both modular and scalable, catering to the needs of the average customer.
Suite of Solutions
To realize the vision, the team set out to build a suite of solutions to address three important areas as follows:
a. rIoT Engine: Edge data engine
b. SkyTracker: A timeseries data platform to house realtime data
c. SkyView: A visualization and analytics portal
Any of these solutions can work independent of the other and can be hosted in the device, on prem or in the cloud.
rIoT Engine is a data communication and decision engine that can run on Linux or Windows operating systems. By design, it is developed to be open and expandable to allow the user adding new communication protocols. Using the scripting engine embedded in the software you can write your own edge decision algorithms or interface the engine with programs written in other languages such as Python or C++.
The team has built their own timeseries database to save realtime data as a historian. One of the great advantages of this solution over the other existing timeseries solutions is the ease of integrating it with corporate data such maintenance management systems. The data can be served to third party applications via REST API’s. SkyTracker provides data interface to push data by the edge components. The data interface is secured by mutual SSL certificates.
SkyView is the visualization, notification, geo-location, and analytics component of the solutions. SkyView allows the users to locate their distributed assets on map, assign a colored alarming scheme to the maps pin drops, drill down to their assets, and view customized HMI’s, charts, lists and alarm summaries.
Use Case I: Data Centers
The rIoT Engine has been deployed within an aviation data center to oversee and monitor critical assets, including:
Network management system
Environmental parameters such as temperature and humidity
This Engine is integrated into a Windows virtual machine, and the visualization screens, replicating the layout and processes, are displayed on screens within the control room. Moreover, intelligent LED lights, under the control of the Engine, have been strategically placed throughout the facility to enhance situational awareness. The inherent openness of our software architecture facilitated swift integration with third-party components, such as the network management system and smart LEDs, by our engineering team.
Use Case II: Train Monitoring
rIoT Engine is installed an embedded hardware on Metro trains to collect realtime data.
The data includes the following:
- Location data: NMEA GPS data
- Engine data: Custom protocol using UDP/IP
- Alarming data: Custom protocol using JSON
As listed above, each input data set has a different format. Once the data is collected in the Engine, they are wrapped in Modbus/TCP format and reported to the control center via a private data connection between the control center and the train.
Use Case III: Wastewater Pump Station Monitoring
rIoT Engine is installed on a relatively inexpensive cellular embedded hardware in the wastewater pump stations. The Engine is communicating with the station PLC’s to collect data and send via cellular links to SkyTracker. The data, charts, visualization screens and geo-location information can be viewed on smart phones via a secure connection to SkyView. A role-based user hierarchy is established to send system alarms and notifications to the relevant people selectively.
Charting the Path Ahead
The future development of Avista's rIoT technology is focused on several key areas:
Interoperability: rIoT technology aims to seamlessly integrate with a wider range of devices and systems by supporting additional communication protocols and emerging IoT standards.
Edge Computing: Expect advancements in edge computing capabilities, enabling faster decision-making and reduced data transfer for real-time applications.
Security: Enhanced security measures, such as improved encryption and intrusion detection, will be a priority to safeguard data and infrastructure.
Scalability: Future iterations offers improved scalability to accommodate the increasing number of connected devices and growing data volumes.
AI and ML: Integration of AI and machine learning for predictive analytics and anomaly detection to provide intelligent insights and recommendations.
Energy Efficiency: Focus on energy-efficient solutions to optimize power consumption in edge devices and enhance energy monitoring and management.
User Experience: Enhanced user interface and experience to ensure ease of use and accessibility for a broader user base.
Support for Emerging Technologies: Adaptation to emerging technologies like 5G networks and advanced sensors for faster data transmission and more accurate data collection.
Customization and Integration: Providing tools and APIs for customization and seamless integration into existing workflows and systems, catering to specific industry needs.
In summary, rIoT technology is primed for innovation and efficiency across industries, supporting the evolving landscape of IoT and real-time data communication.