 |
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
|
Issue: December 2025
Volume 10 | Issue 12
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19445
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
Total Countries : 144
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | A Survey on Emotion or Weather Based Music Recommendation System |
| Authors Name: | Kavyamol P S , Angel Maria Jose , Aparna Rajesh , Nitika Rose Jacks , Rakhi Ramachandran Nair |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_200288
|
| Published Paper Id: | IJRTI2501085 |
| Published In: | Volume 10 Issue 1, January-2025 |
| DOI: | |
| Abstract: | This paper presents an innovative approach to music recommendations by combining mood and weather to create a more immersive and personalized listening experience. The system is built on two primary components: emotion detection and weather analysis. By analyzing facial expressions, it can accurately gauge the user’s current emotional state and suggest songs that resonate with their mood. Additionally, it incorporates real-time weather up- dates to tailor playlists that suit the ambiance of the day. For instance, on a sunny day, the system might suggest up- beat and energetic tracks, while on a rainy day, it might opt for more mellow and reflective tunes. The inside-outside perspective of music choice, which takes into account the mood of the user and outside weather conditions, is meant to provide music choices that resonate well with the experience of the listener in general. To make music have an emotional effect, the system means to create a relation between the music selected for a particular day with the mood of the user and the weather during that day to make a part of their daily life more engaging and fun. This approach personalizes the selections of music also, and deepens interaction with the environment and the emotions. It regularly updates live data playlists so that the musical items stay relevant and apt at all times of the day. As such, if it suddenly changes from being sunny to stormy, the system would be able to shift organically into another set of tracks better fitting the changed atmosphere. Such a functional ability enables smooth coordination with the user’s inner self and thus with the outer world also. The system gives a mix of mood and weather recommendations, thus augmenting the listener’s sense of intimacy with their environment and with their own emotions, and leads to a richer and more dynamic music experience. It is through this innovative method that music becomes that very much stronger tool for emotion expression and environmental interaction, which surprisingly improves the listener’s daily routine and overall well-being. It promises, therefore, to change the way we relate to music as it will become an integral and responsive part of our lives. |
| Keywords: | Machine Learning,Deep Learning,Music Recommendation System, Emotion-Based Music, Weather Detection, Mood-Based Playlist, Adaptive Recommendations, User-Centered Music, Real-Time Emotion Analysis |
| Cite Article: | "A Survey on Emotion or Weather Based Music Recommendation System", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 1, page no.a703-a712, January-2025, Available :http://www.ijrti.org/papers/IJRTI2501085.pdf |
| Downloads: | 000611 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2501085
Registration ID:200288
Published In: Volume 10 Issue 1, January-2025
DOI (Digital Object Identifier):
Page No: a703-a712 Country: Thiruvankulam, Kerala, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2501085 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2501085 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2025 - All Rights Reserved - IJRTI | |||