The concepts of IoT, Industrial IoT, and Industry 4.0 share common ground yet exhibit distinct differences. IoT emphasizes connecting all hardware devices in daily life and production; Industrial IoT refers to connecting production equipment and products within industrial environments; Industry 4.0 encompasses the entire manufacturing ecosystem.
As industrialization and informatization deepen their integration, the demand for interconnecting production control systems and management systems within and between enterprises has grown. The need to enhance product quality and operational efficiency through network connectivity has become increasingly urgent, giving rise to the Industrial Internet of Things.
The Industrial Internet of Things transforms every stage and piece of equipment in the production process into data terminals. It comprehensively collects foundational data from the ground up and performs deeper-level data analysis and mining to boost efficiency and optimize operations.
Unlike IoT applications in consumer industries, the industrial IoT foundation has existed for decades. Systems like process control and automation, industrial Ethernet connectivity, and wireless local area networks (WLAN) have operated in factories for years, alongside programmable logic controllers (PLCs), wireless sensors, and RFID tags. However, within traditional industrial automation environments, everything remained confined to the factory's own systems, never connecting to the outside world.
Compared to traditional industrial automation, the Industrial Internet of Things (IIoT) exhibits four key characteristics:
1. Data Collection Scope: The IIoT utilizes RFID, sensors, QR codes, and other means to continuously capture information data throughout a product's lifecycle-from production and sales to end-user application. Traditional industrial automation data collection is often confined to production and quality inspection stages.
2. Interconnected Transmission: The IIoT employs a combination of dedicated networks and the internet to transmit object information accurately and in real time. It relies more heavily on networks and emphasizes data interaction.
3. Intelligent Processing: The IIoT comprehensively utilizes intelligent computing technologies such as cloud computing, cloud storage, fuzzy recognition, and neural networks to analyze and process massive amounts of data and information. Combined with big data technology, it deeply mines the value of data.
4. Self-organization and Self-maintenance: Each node in the IIoT contributes processed information or decision data to the entire system. When a node fails or data changes occur, the system automatically adjusts based on logical relationships.