Evidence map›Paper›PMID 32456219›Full record

ArticleSensors (Basel, Switzerland)2020

BLESeis: Low-Cost IoT Sensor for Smart Earthquake Detection and Notification.

Jongbin Won, Junyoung Park, Jong-Woong Park, Inho Kim

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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.

Jongbin WonDepartment of Civil and Environmental Engineering, Chung-Ang University, Dongjak, Seoul 06974, Korea.
Junyoung ParkDepartment of Civil and Environmental Engineering, Chung-Ang University, Dongjak, Seoul 06974, Korea.
Jong-Woong ParkDepartment of Civil and Environmental Engineering, Chung-Ang University, Dongjak, Seoul 06974, Korea.
Inho KimDepartment of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea.ORCID 0000-0001-5665-9902

Funding

National Research Foundation of Korea 2017M3C1B6069981
6 · The paper itself

Abstract

The Internet of Things (IoT) has been implemented to provide solutions for certain event detection because of ease of installation, computing and communication capability, and cost-effectiveness. Seismic event detection, however, is still a challenge due to a lack of high-fidelity sensing and classification efficiency. This study proposes BLESeis, an IoT sensor for smart earthquake detection. BLESeis comprises three main parts: (1) high-fidelity vibration sensing using a MEMS accelerometer and digital filtering; (2) an embedded earthquake detection algorithm; (3) BLE (Bluetooth low energy) beacon for earthquake notification. For high-fidelity vibration sensing, a triggering algorithm and embedded finite impulse response (FIR) low-pass filter are developed. The acquired vibration is then classified by the earthquake detection algorithm developed to identify the earthquake signal from other vibration sources using time and frequency domain analysis. Upon detection of an earthquake, the BLE beacon broadcasts using the proposed data packet for efficient notification and visualization. The performance of the proposed system is evaluated through numerical simulations and a set of experiments using shaking table tests. The experiments show the feasibility of the low-cost earthquake detection and notification system.

Indexed as

BLEhigh fidelity sensingiBeaconIoT sensorseismic event detectionwireless sensor

Identifiers

PMID32456219
PMCPMC7294427

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.