ArticleHeliyon2023
Emergency treatment mechanism of laboratory safety accidents in university based on IoT and context aware computing.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 9 citations in OpenAlex.
- Research and Application of Safety Hazard Perception and Responsibility Traceability System in University Laboratories.Sensors (Basel, Switzerland) · 2026Article
- Emerging technologies transforming the future of global biosecurity.Frontiers in digital health · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, safety accidents in university laboratories have occurred frequently. Not only do the accidents result in property damage, but also in injuries. Real-time environmental monitoring of the laboratory through IoT enables early detection of potential safety risks such as high temperatures, high humidity and gas leaks, and timely action to reduce the likelihood of accidents. To ensure laboratory safety, in the paper, an emergency treatment mechanism for laboratory safety accidents was proposed based on IoT and context perception. The mechanism uses sensors to collect environmental information and fill a feature characterization architecture for unified safety management. Subsequently, the meta-rule algorithm is used to discover services in the prior knowledge model to form a workflow engine, so as to drive the security business management. Additionally, based on the standard measurement model, we normalize the fuzzy uncertainty measurement model with different granularities and define the fuzzy uncertainty of different emergency decision-making knowledge. Based on this, a knowledge fusion method for emergency decision-making under different fuzzy uncertainties is proposed, which improves laboratory safety emergency response performance based on situational awareness. The implementation of the proposed mechanism in a chemical laboratory demonstrates its efficacy in optimizing operational processes and discovering operational flow through multi-dimensional information analysis. This capability significantly aids safety administrators in their daily laboratory safety management.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.