An ICN-based publish-subscribe platform to deliver UAV service in smart cities
Why this work is in the frame
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Bibliographic record
Abstract
Intelligent Transportation Systems (ITS) play significant role in the management of traffic congestion in large cities. However, current ITS platforms are not suitable for real-time traffic control mainly due to the facts that 1) the contents are not rich enough to provide detailed information of current transportation network state, 2) there is no sophisticated notification system to alert the ITS platform about major issues in real-time. Unmanned Autonomous Vehicles (UAV) are promising candidates to provide rich content for traffic control systems in large cities and enable real-time notifications, especially when deployed on a platform that is content-oriented. This paper presents a sensor as a service platform to host live content streams (video, data) from a diverse set of input streams including UAVs, city cameras, loop detectors, etc., and to make the data available to a broad range of customers using a novel data dissemination layer. The data-dissemination layer is a content-oriented system based on information-centric networking, a new paradigm that puts content first, and which inherently enables content mobility and content security (through encryption on demand). To support real-time notification, we have implemented publish/subscribe overlay system based on the ICN paradigm. have also conducted live demos with UAVs providing live transportation video data in the system.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it