ThingsDriver: A Unified Interoperable Driver for IoT Nodes
Bibliographic record
Abstract
The Internet of Things (IoT) is one of the fastest-growing technologies in recent years. However, many IoT service providers design their IoT solutions with non-interoperable hard-ware, scenario-specific features, and unique architectures that make these deployments fragmented rather than collaborative. Collaborative IoT (C-IoT) systems are considered the natural evolution of the traditional IoT. Sharing the infrastructure is one of the main concepts that C-IoT depends on to create a collaborative environment between different applications. With the current fragmented IoT, these applications cannot share their infrastructure and data due to the lack of standards to organize the C-IoT space. In this paper, we introduced Unified Interoperable Driver for IoT (UIDI) nodes. UIDI uses a novel programming methodology that enables node interpreters to provide general-purpose firmware for IoT nodes. UIDI allows the users to configure IoT nodes according to their usage, preferences, and needs through the cloud. We developed a proof-of-concept prototype to demonstrate the feasibility and usability of the proposed UIDI using NodeMCU and Arduino-Uno. The performance of UIDI outperforms Firmata by 27%. In addition to that, the UIDI platform is a standalone node that connects directly to the cloud, whereas the Firmata node requires a host to be accessible from the cloud.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".