Industrial IoT (IIoT) brings together machines, cloud computing, analytics, and people to enhance the productivity and functionality of industrial processes. With IIoT, companies can transform business models and improve performance alongside decreasing industrial waste.

Whether it’s called Industrial Internet of Things (IIoT), Industry 4.0, or Digitalization, companies have started leveraging technologies to completely reimagine their business model. This transformation will be widespread, and everything from Information technology (IT) to engineering technology (ET) to operational technology (OT) services will be impacted.

The most notable benefit of IIoT is that the focus of business owners has started shifting to increased efficiency and lower costs by using edge devices and Big Data analytics. However, massive data transmissions from and to the IIoT devices in remote areas, on diverse network connections on time are some of the challenges to overcome. Another challenge is the need for actionable data to make sense of all the data collected.

The addition of Edge Computing to the Industrial IoT gateway hardware allows the Industrial IoT gateway to perform local storage and data processing. It results in higher reliability, lower latency, and more security.

There are five widely recognized criteria for choosing the Industrial IoT gateway:

  • ​Open standards
  • Flexible architectures
  • Cloud technology
  • Edge Computing
  • Cheaper and more flexible hardware​

Why should I use edge devices in Industrial IoT?

The edge device plays a vital role in collecting data and creating a digital twin of your cloud applications. Simply put, the edge devices connect the data from your network to the cloud solution.

In a manufacturing facility, edge devices have the following benefits:
  • Facilitate condition-based monitoring to keep an eye on the condition of shop-floor machines
  • Monitoring and analyzing data to detect anomalies sooner so that you can improve machine uptime, lower spare parts inventory
  • Adds efficiency and self-monitoring analysis

IIoT systems with edge devices give you the benefits of real-time local analysis and robust cloud-based storage. Compared to cloud computing, which requires network connectivity and reliance upon 3rd party security, Edge computing, on the other hand, offers low-latency, dependable edge computing power that can be deployed in manufacturing facilities with limited network connections and also in places where security is a premium factor.

IoT device management in IoT platforms – Features, deployment, and capabilities

IoT device management platforms provide device lifecycle management functionality connected to the deployment and management of IoT devices. You can choose a device management platform vendor like ARM, Amazon, Bosch or decide to have IoT platform vendors like Utthunga with device management within their features.

The onboarding process, provisioning, authentication, deployment, and encryption of device management consists of secure and rapid deployment keeping in mind security and trust.

Three key capabilities of IoT device management platforms

  1. Deployment and monitoring
  2. Maintenance and management
  3. Software and firmware updates

Edge device management and its challenges:

As per a report by Statista, 75 billion edge devices are predicted to be used in operation across the industries like manufacturing, healthcare, finance, and more to produce, capture or analyze data. In some cases, these edge devices are expected to capture, analyze, store and transfer data to centralized data centers or the cloud.

The significant functionality of these devices goes beyond managing the captured data as per their software specifications. They are expected to be a part of a larger, interconnected ecosystem to provide users with visibility into entire processes.

Take the case of home automation.There are multiple edge devices for monitoring and controlling lighting, window blinds, temperature, etc., qualified for edge computing in home automation systems. These devices handle specific processing tasks as individuals and act as an interconnected system as more computing power is required for managing edge devices.Limited scalable computing power is only one of the significant challenges of managing edge devices.

Apart from this, enterprises or domestic users need to ensure that these edge devices are secure, even for devices that connect to external data centers. For smaller edge devices, users face are unable to access the right data and get an overview of the work they do. Some form of data visibility is essential when their performance is going to affect an entire system.

Meaning, edge device management requires an all–in-one solution that offers scalability, visibility, and flexibility. A 360-degree view into edge device performance is essential to stay updated with real-time insight.

Industrial IoT platforms and edge device management

Industrial IoT platforms integrate artificial intelligence and machine learning algorithms to take edge device management to the next level. With these algorithms, shop floor requirements can be achieved using extensive data analysis and data-driven insights. IoT platforms also facilitate communication workflows for edge device management which provide deeper insight into connected devices. This communication workflow offers alerts and notifications to help organization’ decision-makers optimize edge computing processes. The data visualization by IoT platforms also makes the comparison of shop floor data against benchmark data possible.

This communication workflow process starts from collecting data from different facilities to create an optimal benchmark of data. Data collected from shop floors can then compare their productivity levels to the benchmarked data, and the insight from this comparison is helpful in optimizing asset utilization. These insights can also be used to highlight other issues and failures within production cycles, right from poor material handling systems or even the idle time of the machines leading to underutilization of the shop floor operators.

Industrial IoT platforms often work as Software as a Service platforms (SaaS) platforms and provide the APIs, algorithms, and repositories for enterprises to help them build edge applications. These applications can also be deployed within edge devices or edge networks, depending on what you want to build.

IoT platforms use the scalability and flexibility of cloud and edge computing to help enterprises scale up their edge device management needs only when more devices or data are produced. Using the IoT platform for edge device management can reduce the cost and efforts as well.

Conclusion

Edge device deployment and management are an essential part when you leverage edge computing within shop floors. The choice of an edge device management platform depends upon your industry’s specific needs, whether you want to build industry-specific applications, cybersecurity, scalability, and subscription cost, or something else.


Recent Post