Combining FM broadcast, accelerometers, IEEE 892.15.4 wireless and GPS to secure maritime containers worldwide
Bibliographic record
Abstract
There are approximately 50 million maritime style containers entering and leaving ports in North America every year and 500 millions worldwide [8]. The interiors of such containers are rarely inspected. With market globalization, a large amount of these containers enter North America on a daily basis. Such containers may include contraband or dangerous items that present an economic or security risk. Despite significant security improvements, only 3 to 5% of the maritime containers, that arrive in or transition through North America, go through physical inspection. Current container tracking technologies solely based on GPS consume high DC power, are costly, require line-of-sight with satellites and they are often too large to be covert. It is possible to overcome some of these limitations by combining GPS with a tracking system based on the FM broadcast signal. Digital FM broadcast is an alternative man-made signal that is ubiquitous, provides a geographically unique frequency spectrum and is about 100,000 as strong as a GPS satellite signal. The combination of GPS and FM, called "Broadcast Assisted GPS™" allows the development of a low-cost, low-power and miniature FM-GPS receiver that can trace the path that a container has taken for less than 25$ per container. This paper presents the first results of highway trials (train and sea trials are to be conducted in 2010-2011) of such a low cost, covert, "Broadcast Assisted GPS"based technology, called "FM-RFID Tag™" that records the worldwide displacement of containers and displays the path undertaken by the container while in transit. As an added security benefit, the tag is also capable of detecting container intrusion, either door or side panel intrusion.
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 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 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".