# A Distributed Sensor System Based on Cloud-Edge-End Network for Industrial Internet of Things +
###### Abstract  
The Industrial Internet of Things (IIoT) refers to the application of the IoT in the industrial field. The development of fifth-generation (5G) communication technology has accelerated the world's entry into the era of the industrial revolution and has also promoted the overall optimization of the IIoT. In the IIoT environment, challenges such as complex operating conditions and diverse data transmission have become increasingly prominent. Therefore, studying how to collect and process a large amount of real-time data from various devices in a timely, efficient, and reasonable manner is a significant problem. To address these issues, we propose a three-level networking model based on distributed sensor self-networking and cloud server platforms for networking. This model can collect monitoring data for a variety of industrial scenarios that require data collection. It enables the processing and storage of key information in a timely manner, reduces data transmission and storage costs, and improves data transmission reliability and efficiency. Additionally, we have designed a feature fusion network to further enhance the amount of feature information and improve the accuracy of industrial data recognition. The system also includes data preprocessing and data visualization capabilities. Finally, we discuss how to further preprocess and visualize the collected dataset and provide a specific algorithm analysis process using a large manipulator dataset as an example.  
data generation; Industrial Internet of Things (IIoT); data acquisition; distributed sensors; feature fusion +
Footnote †: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/py/4.0/](https://creativecommons.org/licenses/py/4.0/)]([https://creativecommons.org/licenses/py/4.0/](https://creativecommons.org/licenses/py/4.0/))).  
Footnote †: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/py/4.0/0/](https://creativecommons.org/licenses/py/4.0/0/)]([https://creativecommons.org/licenses/py/4.0/0/](https://creativecommons.org/licenses/py/4.0/0/))).  
Footnote †: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.  
These technologies encompass industrial data collection and storage, data conversion and transmission, data preprocessing, data visualization, and data analysis [2; 3; 4].  
The IIoT is driving the trend of processing data at the network edges to reduce latency and improve efficiency. However, this also requires careful data management outside the core data center to avoid data corruption and adverse effects. The continuous innovation of distributed sensor network (DSN) technology further advances the development of the IIoT. DSN technology overcomes many challenges posed by traditional on-site embedded industrial gateways connecting to industrial sites. Moreover, DSNs are widely used due to their significant advantages, such as flexible nodes, reliable transmission, multiple data transmission paths, and simple network layout [5]. In multisensor information fusion systems, both centralized and distributed architectures are commonly employed [6; 7; 8; 9]. In a centralized data fusion structure, sensor data are sent directly to the data fusion center for processing, which minimizes information loss. However, it also has drawbacks, such as complex data interconnection, poor reliability, and high computing and communication resource requirements. In a distributed fusion architecture, each sensor has its own processor to process its own information and sends the processed data to the data fusion center for fusion [10].