Web services for indoor energy management in a smart grid environment
Bibliographic record
Abstract
Smart grid aims to empower the current power grid with the capability of supporting two-way energy and information flow; and facilitating the integration of advanced computer technology and renewable energy sources into the grid. We assume a smart home with a wireless sensor network based on Zigbee. The smart home contains elements like light or temperature sensors at every room, HVAC (heating, ventilation, and air conditioning), smart appliances, thermostat and smart meter. Furthermore, there is a central computer that can communicate with all these elements. Web service is implemented on central computer and it can be accessed over the internet. The paper proposes an approach that makes use of the web services technologies to remotely interact with smart home elements in a smart grid environment. These interactions include adjusting the temperature according to personal preference or reading energy consumption. Furthermore, utility provider can interact with the smart home via web services and can facilitate demand response or selling energy back to the grid. Some scenarios are shown to describe the interactions in more detail. The performance, advantage and limitations of the radio communications between user (e.g., utility provider) and elements via web services are demonstrated in this paper.
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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".