Internet of Smart Things - IoST: Using Blockchain and CLIPS to Make Things Autonomous
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Current networking integrates common "Things" to the Web, creating the Internet of Things (IoT). The considerable number of heterogeneous Things that can be part of an IoT network demands an efficient management of resources. With the advent of Fog computing, some IoT management tasks can be distributed toward the edge of the constrained networks, closer to physical devices. Blockchain protocols hosted on Fog networks can handle IoT management tasks such as communication, storage, and authentication. This research goes beyond the current definition of Things and presents the Internet of "Smart Things." Smart Things are provisioned with Artificial Intelligence (AI) features based on CLIPS programming language to become self-inferenceable and self-monitorable. This work uses the permission-based blockchain protocol Multichain to communicate many Smart Things by reading and writing blocks of information. This paper evaluates Smart Things deployed on Edison Arduino boards. Also, this work evaluates Multichain hosted on a Fog network.
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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 | 0.001 | 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 | 0.001 | 0.002 |
| 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