Industrial IoT and data: The fuel behind the Fourth Industrial Revolution

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Industrial IoT and data: The fuel behind the Fourth Industrial Revolution

Industrial IoT and data: The fuel behind the Fourth Industrial Revolution

Subheading text
Industrial Internet of Things allows industries and companies to complete tasks effectively with less labor and more automation.
    • Author:
    • Author name
      Quantumrun Foresight
    • December 16, 2021

    Insight summary

    The Industrial Internet of Things (IIoT), a key component of the fourth industrial revolution, is transforming industries by enhancing machine-to-machine connectivity, leveraging big data, and utilizing machine learning. By enabling real-time data analysis, IIoT allows companies to streamline operations, improve efficiency, and make informed strategic decisions. However, the widespread adoption of IIoT also brings challenges, such as heightened cybersecurity risks and increased electronic waste, requiring strong security measures and improved recycling methods.

    IIoT context 

    The expansion and usage of the internet of things (IoT) in industrial sectors and applications is called the industrial internet of things (IIoT). The IIoT helps companies and organizations improve their efficiency and dependability by focusing on machine-to-machine (M2M) connectivity, big data, and machine learning. In the context of the fourth industrial revolution, known as Industry 4.0, the IIoT has become essential to cyber-physical networks and manufacturing processes.

    The IIoT’s increasing adoption has been supported by equally widescale adoption of big data and analytics in industry. Industrial infrastructures and appliances rely on real-time data from sensors and other sources to aid in decision-making, allowing networks and factories to formulate ideas and perform specified operations. As a result, machinery can now complete and automate tasks that were previously impossible for prior industrialization. 

    In a broader context, the IIoT is essential in applications involving interconnected habitats or ecosystems. For example, IIoT can help urban areas and corporations become smart cities and industries. Furthermore, the continuous gathering and transfer of data amongst intelligent devices aid developers in tailoring technology specific to various enterprises.

    Disruptive impact

    By harnessing the power of data analytics, companies can gain a more nuanced understanding of their operations, leading to more informed strategic decisions. For instance, a company could use IIoT to track the efficiency of its supply chain, identifying bottlenecks and areas for improvement. This feature could lead to more streamlined operations, reducing costs and increasing profitability in the long run.

    For individuals, the IIoT could lead to a significant shift in the job market. As automation becomes more prevalent, there will be a growing demand for workers skilled in managing and interpreting the data produced by IIoT systems. This trend could lead to new opportunities in data science and analytics. Moreover, the increased efficiency brought about by IIoT could lead to lower prices for consumers as companies pass on the savings from improved operations.

    Governments, too, stand to benefit from the rise of IIoT. By integrating IIoT systems into public infrastructure, governments could improve the efficiency and reliability of services such as public transportation and utilities. For example, IIoT could be used to monitor the condition of roads and bridges, allowing for proactive maintenance that could prevent costly and disruptive failures. Furthermore, the data generated by these systems could help governments make more informed policy decisions, leading to better outcomes for their respective citizens.

    Implications of Industrial Internet of Things

    Wider implications of IIoT may include: 

    • Safety monitoring, where companies can use geo-fencing borders to identify if employees are in an area where they are not supposed to be.
    • Facility management by providing comprehensive data collection and analysis, including ways to improve current management techniques for better efficacy and productivity. 
    • Predictive and automated industrial purchasing of supplies since IIoT systems can track resource use in different manufacturing or construction workplaces and proactively order additional supplies when they are running low.
    • Various optimizations within the B2B logistics sector as the IIoT platforms of separate companies can proactively coordinate/collaborate on various work functions with minimal human oversight.
    • The application of IIoT in healthcare enabling remote patient monitoring, leading to improved patient outcomes and reduced healthcare costs.
    • The adoption of IIoT in waste management could lead to more efficient recycling processes, contributing to a cleaner environment and more sustainable cities.
    • Heightened cybersecurity risks requiring security measures to protect sensitive data and systems.
    • The proliferation of IIoT devices resulting in increased electronic waste, requiring improved recycling and disposal methods.

    Questions to consider

    • How should industries and businesses approach IIoT securely?
    • Does the IIoT improve efficiency in all applications?

    Insight references

    The following popular and institutional links were referenced for this insight: