Research on Real-time Data Transmission between IoT Gateway and Cloud Platform based on Two-way Communication Technology
Bibliographic record
Abstract
To realize the real-time two-way communication between the IoT gateway and the cloud platform and improve the transmission efficiency, this paper adopts the designed open IoT platform, uses the Node.js server as the operating platform, and uses the Redis database fast access technology. The design is based on Modularized processing of real-time two-way communication system of Internet of Things gateway and resource platform based on Socket.IO communication protocol. Compared with the traditional Internet of Things communication protocol, the advantage of Socket.IO is that only a handshake between the client and the server is needed to quickly establish a Socket two-way channel, which can realize the real-time twoway transmission of data and effectively save broadband resources.Thereby improving the system's real-time update efficiency of the data model, and ensuring the stability and reliability of the system.For the system function and performance test, the experimental results show that the use of Socket.IO two-way communication technology can realize the simultaneous update of the physical model of the IoT gateway and the virtual model of the IoT cloud platform, and effectively improve the data transmission efficiency of the system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".