Evidence map›Paper›PMID 42451229›Full record

ArticleSensors (Basel, Switzerland)2026

Child Presence Detection Algorithm in School Buses Based on Infrared Array.

Yongjun Liu, Gaosong Li, Xuepeng Yuan, Shuai Zhang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yongjun LiuSchool of Intelligent Manufacturing, Huanghuai University, Zhumadian 463000, China.ORCID 0000-0002-5132-8175
Gaosong LiSchool of Intelligent Manufacturing, Huanghuai University, Zhumadian 463000, China.
Xuepeng YuanSchool of Intelligent Manufacturing, Huanghuai University, Zhumadian 463000, China.
Shuai ZhangSchool of Intelligent Manufacturing, Huanghuai University, Zhumadian 463000, China.

Funding

the Natural Science Foundation of Henan Province, China 262300421369the Science and Technology Research Project of Henan Province, China 262102220039
6 · The paper itself

Abstract

School buses serve as the primary mode of transportation for children traveling to and from school, and their safety measures represent a critical safeguard for children's lives. Nevertheless, incidents in which children are left unattended on school buses-due to inadequate supervision or the children's own actions-occur with notable frequency and can lead to fatal outcomes. To mitigate or prevent such tragedies, this paper proposes an in-vehicle thermal imaging solution based on infrared array sensors, integrated with a dedicated algorithm to detect whether a child has been left behind in the school bus. The system collects background temperature, presence temperature, and real-time temperature data inside the bus using infrared array sensors. By comparing the real-time temperature difference against a predefined presence temperature difference threshold, the algorithm determines whether a child is present under the current thermal conditions. It then verifies whether the number of positive detections within a specified temperature range meets a preset presence count threshold, thereby reaching a final decision regarding child presence. Experiments identified optimal parameters: a temperature range of 26-33 °C, a double-difference threshold (ε = 1), and a presence count threshold (

Indexed as

AlgorithmsInfrared RaysMotor VehiclesSchoolsChildDetection AlgorithmsHumansTemperaturechild presence detectiondifferential algorithminfrared array sensorschool bus safety

Identifiers

PMID42451229
PMCPMC13364463

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.