Evidence map›Paper›PMID 35676960›Full record

ArticleComputational intelligence and neuroscience2022

Design and Implementation of Multiple Music System Based on Internet of Things.

Mengchen Xu

Open access · hybridAbstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. 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
0.4field-weighted citation impact, top 35% 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, 1 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

1 author at 1 institution in 1 country.

Mengchen XuXi'an Conservatory of Music, Music Education Department, Xi'an 710061, Shaanxi, China.ORCID https://orcid.org/0000-0002-1155-0636
Xi'an Conservatory of Music · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapid development of social economy and Internet of Things, the society has entered the era of networking, digitalization, and intelligence, bringing great convenience to people's life; Internet of Things music system also has begun to get people's extensive attention. Due to the influence of such factors as strong music professionalism, complex music theory knowledge, and diverse changes, it is difficult to identify music features. In order to strengthen the user's personal experience of the music system, the multimusic systems are interconnected through information technology to realize the connection between objects and people. The system uses an embedded processor to realize the central control module and then according to network standard the sensor network is built, through radio frequency identification (RFID) technology for light, sound, infrared sensor, temperature, and other sensors for information reading. Music selection logic is designed based on the theory of music psychology and user behavior log, so as to select the best music for users to improve their mood and improve their life quality and work and study efficiency. At the same time, the system uses voice recognition technology to enhance user interaction, through the system, to provide the website to share their own music data and comments on songs and view song information, and the system runs stably and can collect high quality music signals and correctly identify the characteristics of music form and emotional characteristics.

Indexed as

Internet of ThingsMusicHumansInternetRecognition, PsychologyTechnology

Identifiers

PMID35676960
PMCPMC9170442
OpenAlexW4281623110

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.