Top 5 Things Industrial IoT Differs From IoT

City connected line, internet of things concept.
Image: stnazkul/Adobe Stock

The concept of the Internet of Things is the origin of industrial IoT. However, the operation of devices in a smart home or office is very different from the way they operate in an industrial plant such as a smart car assembly plant.

The number of connected IoT devices worldwide was 11.3 billion by 2021. by 2030 An extra there will be an estimated 29.4 billion IoT devices. This means that there are more than three devices for every person in the world today.

In terms of proportions, consumers are not the most significant users of IoT devices. Major industries in energy, water, manufacturing, government, transportation, and natural resources use billions of devices together.

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What is IIoT?

IIoT is defined by the SAP as an AI-driven “system of systems” capable of end-to-end curation, management and analysis of data in industrial operations. The system includes machines, sensors and other connected devices and systems that work together in real time.

When the data generated by the connected components of the IIoT infrastructure can be leveraged using machine learning and artificial intelligence applications, industries can increase efficiency, learn from mistakes, increase productivity, visibility and more.

IIoT networks use machine-to-machine communication to “talk” between devices. These devices regularly transmit and receive data to a central system that integrates and manages all IIoT devices. The central system can operate in the cloud, at the edge or in data center locations. IIoT devices typically connect via 5G, Bluetooth Low Energy BLE, Wi-Fi, and near-field communication (NFC).

The benefits of IIoT include more efficient machines, smarter management and increased worker safety. Automating industrial operations protects workers from performing hazardous tasks and helps companies reduce human labor costs and increase speed and agility.

What is IoT?

IoT is a term used to describe a network of physical objects embedded with sensors, software, and other technologies. The primary purpose of this network is to connect and exchange data with other devices and systems used online. IoT devices are diverse: they can be household devices or sophisticated industrial devices.

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IoT is on common ground with IIoT. Systems and devices are connected and communicate, and users control them on a central platform. In addition, IoT uses edge and cloud computing in addition to analytics functions. The main difference between them is determined by the end use. In IoT, end users are consumers, offices and other work environments such as healthcare.

The idea behind IoT is to automate many previously manual tasks and integrate systems for better accessibility. For example, in homes, users can manage all their smart devices using a central hub or smartphone, which is usually equipped with voice control. IoT environments aim to make life and work easier, smarter and more accessible.

Differences between IoT and IIoT

IIoT can be considered IoT with super-enhanced capabilities. Understanding the differences between one and the other is essential, especially if you work in industries or environments that require intensive machine collaboration, collaboration, and connectivity.

The end use

The main difference, as mentioned above, is the end user. In both cases, the end user determines what the devices and the network can do and what features they have. IoT is designed and works in homes, offices, buildings and professional workspaces. Although healthcare IoT may be very advanced, they are still closely related to consumer devices rather than industrial devices. In contrast, the IIoT end user is at a larger scale. Work in the industrial sector requires different devices and connected systems and networks.

Machine learning and artificial intelligence: Optimizing operations

Another major difference is how both groups use machine learning and AI. IoT devices in the home and office will use analytics and AI-powered applications. However, they do not use data as widely as IIoT.

For example, factories using IIoT can run AI algorithms that analyze the data generated by each device and adjust the unique actions of each device to increase production. Therefore, IIoT systems can “learn” and become more efficient. This advanced analytics does not occur in consumer IoT systems. IIoT AI systems can automate operations from security to redundancy or maintenance.

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Strength, performance and durability

While not all IIoT devices and systems are of significant size, they are all built to withstand extreme conditions. Industrial sectors require high and low temperatures, weather, water, dust, friction and extended life cycles. Compared to IoT devices and networks, IIoT is durable and flexible. It is also designed for repair and maintenance. Also, IIoT is performance intensive, so both software and hardware must be built accordingly.

IIoT systems are designed for mission-critical processes and durability is essential. Industries cannot afford downtime or disruption to their systems. Backup systems are usually implemented as a contingency plan in case a component of the IIoT infrastructure fails or requires maintenance.

Precision, scalability, data flow and connectivity

Industries that use robotics, sensors and systems require accuracy that exceeds the standards of domestic IoT systems. IIoT must also be scalable. While a workplace or home environment may connect a few dozen devices, industries may have hundreds or thousands of devices connected to a network and need to scale their IIoT systems as demand increases.

Also, the amount of data generated in IIoT infrastructures is exponentially higher than the amount of data generated in other IoT areas. The challenge of transferring data in real time while keeping the information secure is unique to the IIoT. Likewise, industries typically use private networks to handle their data streams, and private 5G networks have become the new norm.

All IIoT big data needs to be integrated and analyzed to leverage operations optimization. The central software and platforms used in IIoT are designed specifically for industrial purposes by leading manufacturers. They can manage big data from assets, employees, communications and external factors such as supply chains, partners or market changes. After these systems calculate and analyze the factors, they use artificial intelligence to automatically adjust operations without human intervention.

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Technical complexity: Security, skills and talent

The final difference between IIoT and IoT is complexity, which presents many security challenges. Complexity also increases the skills required to design, install and operate such systems. Talent is in critical demand in IIoT. Every element of IIoT requires skilled professionals. This is a significant difference, since domestic IoT does not usually require users to have technical knowledge. Workers in the industry must be trained and educated. While new technologies such as augmented reality streamline these processes, these positions are still highly technical.

Security is another differentiating factor. In IIoT, the security consequences can affect the company, its suppliers, partners, all its customers, and even the population. For example, the security of energy or water IIoT systems can be a matter of national security. Companies using IIoT must secure networks, software, systems and platforms, as well as all other assets, ensuring that they cannot be digitally or physically tampered with. IIoT solutions include secure and flexible system architectures, specialized chipsets and hardware, encryption and authentication, threat detection and risk management frameworks.

The world is deeply immersed in a journey of transformation and modernization. In this era, IoT unites the digital and real worlds. Connected devices, machines, robotics, systems and data centers are at the forefront of development. Understanding the key differences between IoT and IIoT is the first step in designing, implementing or building innovative architectures that can drive results and efficiencies in your industry.

Further literature

If you are working on implementing IIoT in your enterprise, choosing the right software is critical. There are hundreds of IIoT platforms out there, and each one is slightly different, so how do you choose? This article, including links to TechRepublic Premium resources, may help.