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Rust-Driven Real-Time Sensor Aggregation for Industrial IoT: Zero-Loss Data and Web Visibility
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Author(s): Chenyu Liu (The Hong Kong Polytechnic University, Hong Kong), Yaxin Luo (The Hong Kong Polytechnic University, Hong Kong), Jingyan Zeng (The Hong Kong Polytechnic University, Hong Kong), Liyuan Fan (The Hong Kong Polytechnic University, Hong Kong), Mingyuan Tang (The Hong Kong Polytechnic University, Hong Kong)and Cong Wu (Liaoning Technical University, China)
Copyright: 2026
Pages: 28
Source title:
Advanced Concurrency, Buffering, and Web-Sync in Sensor Platforms: Zero-Loss Streams
Source Author(s)/Editor(s): Aquil Mirza Mohammed (The Hong Kong Polytechnic University, Hong Kong)
DOI: 10.4018/979-8-2600-1101-0.ch003
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Abstract
The ever-increasing volume of data and the need for real-time data processing make preventing data loss a major challenge. This chapter aims to solve this problem. A distributed sensor data aggregation platform based on Rust was designed and implemented. This aggregation platform enables the entire process of efficiently acquiring real-time data from multiple sensors, processing the data, storing it, and accessing it via the web. Its main supporting technology is a one-thread reading strategy for each sensor, a shared queue to absorb the problem of mismatched producer and consumer rates, and finally, multi-threaded aggregation for calculation within a fixed window. Through stress testing, data loss verification, and bench marking, this platform achieved zero data loss, correct and stable aggregation, and safe web access. Overall, this platform provides a scalable foundation for future deployment in industrial IoT environments, which require continuous and low-latency data access, reliable buffering, and strong fault tolerance.
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