The IIoT industrial industry is growing at an astounding pace, with cutting-edge innovations in IIoT development transforming industries across the globe. The global Industrial IoT industry size as of 2022 is valued at USD 101.45 billion and is expected to experience a compound annual growth rate (CAGR) of 20.5% from 2022 to 2030. Everything from 5G connectivity to automation powered by AI, industries are improving at a rapid pace in terms of efficiency, security, and productivity. Here are some of the newest important trends in IIoT that are redefining how industrial operations will be conducted in the future.
Competitive Landscape of IIoT: Key Growth Strategies
The transformation of edge computing, AI, and IoT-based sensors is making an impact in industrial automation, with engineering companies such as Lemberg Solutions helping implement these technologies in real-world environments. In the context of IIoT, edge computing handles data at the network's periphery, which enables real-time decision-making and significantly reduces latency. In the context of smart manufacturing, for instance, edge-enabled robots in automation can modify the process of production as it is being carried out, which decreases the chances of mistakes while increasing the output.
Challenges of Connectivity: 5G and Edge Computing
The integration of the new 5G technology combined with the IIoT enables the transfer of information at super-fast speeds with very low latency, allowing machines to communicate effectively. In addition, the adoption of edge computing for IIoT systems allows data to be processed at the source, adding greater efficiency compared to cloud computing. For example, 5G-powered automated warehouses are able to capture and quantify inventory in real-time, greatly improving stock levels and streamlining supply chains.
AI and Predictive Analytics Transforming IIoT
Over the last few years, the use of AI in industrial IoT has become much more prominent, and self-learning predictive analytics are being utilized to minimize downtimes while maximizing productivity. AI and machine learning innovations in IIoT can anticipate a machine-related failure and take preemptive measures to avoid it and save money. For instance, oil refineries can use AI-driven predictive maintenance to scan their pipelines for weak spots before they cause a leak, ensuring safe operational conditions.
