Evidence map›Paper›PMID 39686020›Full record

ArticleSensors (Basel, Switzerland)2024

On Construction of Real-Time Monitoring System for Sport Cruiser Motorcycles Using NB-IoT and Multi-Sensors.

Endah Kristiani, Tzu-Hao Yu, Chao-Tung Yang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. 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

3 authors.

Endah KristianiDepartment of Computer Science, Tunghai University, Taichung City 407224, Taiwan.ORCID 0000-0003-2925-2992
Tzu-Hao YuDepartment of Computer Science, Tunghai University, Taichung City 407224, Taiwan.
Chao-Tung YangDepartment of Computer Science, Tunghai University, Taichung City 407224, Taiwan.ORCID 0000-0002-9579-4426

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study leverages IoT technology to develop a real-time monitoring system for large motorcycles. We collaborated with professional mechanics to define the required data types and system architecture, ensuring practicality and efficiency. The system integrates the NB-IoT for efficient remote data transmission and uses MQTT for optimized messaging. It also includes advanced database management and intuitive data visualization for enhancing the user experience. For hardware installation, the system follows strict guidelines to avoid damaging the motorcycle's original structure, comply with Taiwan's legal standards, and prevent unauthorized modifications. The implementation of this real-time monitoring system is anticipated to significantly reduce safety risks associated with mechanical failures as it continuously monitors inappropriate driving behaviors and detects mechanical abnormalities in real time. The study indicates that the integration of advanced technologies, such as the NB-IoT and multi-sensor systems, can lead to improved driving safety and operational efficiency. Furthermore, the research suggests that the system's ability to provide instant notifications and alerts through the platforms' instant messaging can enhance user responsiveness to potential hazards, thereby contributing to a safer riding experience.

Indexed as

IoTMQTTmulti sensorNB-IoTreal-time monitoring

Identifiers

PMID39686020
PMCPMC11644252

What OpenQuestion holds

Textmetadata
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.