Evidence map›Paper›PMID 37514576›Full record

ArticleSensors (Basel, Switzerland)2023

Indoor Human Detection from a Building's Exterior Using 433 MHz Wireless Transceivers.

Sunghoon Jo, Sehee Park, Gu-In Kwon

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. 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
0.3field-weighted citation impact, top 47% of its field
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, 2 citations in OpenAlex.

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 at 1 institution in 1 country.

Sunghoon JoDepartment of Electrical and Computer Engineering, Inha University, Incheon 22212, Republic of Korea.
Sehee ParkDepartment of Electrical and Computer Engineering, Inha University, Incheon 22212, Republic of Korea.
Gu-In KwonDepartment of Electrical and Computer Engineering, Inha University, Incheon 22212, Republic of Korea.ORCID 0000-0003-0065-4330
Inha University · KR

Funding

National Research Foundation of Korea 2021R1F1A1055052
6 · The paper itself

Abstract

This study introduces a novel system for detecting humans inside a building by utilizing RF signals from the building's exterior. Existing RF communication devices encounter signal attenuation issues when passing through walls, limiting their effectiveness. In contrast, our system employs a low-power, long-distance communication signal operating at 433 MHz to enhance signal permeability, enabling the accurate detection of individuals within the building. The system analyzes received signal strength indicator (RSSI) data using variance and mean analysis algorithms to determine the presence or absence of people. The evaluation results indicate promising average accuracies of 88% for the variance analysis algorithm and 97.7% for the mean analysis algorithm. The proposed system holds potential for real-world deployment, particularly in challenging scenarios such as fire incidents, where pre-installation is challenging. Continued research and development efforts aim to enhance the system's performance and address any limitations, making it more effective and robust in various practical applications.

Indexed as

FiresWireless TechnologyAlgorithmsCommunicationComputer Communication NetworksHumanshuman detectionRSSIthrough-the-wallwireless sensor networks

Identifiers

PMID37514576
PMCPMC10383108
OpenAlexW4383954821

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.