Designing Home Security and Monitoring System Based on Field Programmable Gate Array*
Bibliographic record
Abstract
In the conventional design of home security systems, only the property is typically monitored, without taking into consideration the physical control aspects of the house itself. Besides, the term security is not strictly well defined in view of the fact that there is usually a time delay between the alarm system going on and actual arrival of the security personnel. This paper presents the development of a home security and monitoring system that is suitable where the traditional security systems that are mostly concerned about curbing burglary, gathering evidence against trespassing and so on fail. The design and implementation details of this new home control and security system which is based on field programmable gate array has been discussed in the subject paper. The user here can interact directly with the system through a web-based interface over the Internet, while home appliances like air conditioners, lights, door locks, and gates are controlled remotely through a user-friendly web page. An additional feature that enhances the security aspect of the system is its capability to monitor entry points such as doors and windows so that in the event of any breach, an alerting email message could be sent to the home owner instantly.
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 | 0.000 | 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) | 0.003 | 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 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".