M2M Node Playlist Curation via Song Occurrence Analysis
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Solution Overview
Problem
In environments with diverse music preferences, such as bars and nightclubs, traditional collaborative music playlists become impractical due to long playlists and varied listener tastes, making it difficult to provide an appealing music offering.
Innovation Solution
A method and system that utilizes an M2M network node connected to a music player unit and speaker unit to receive and analyze music playlists from mobile devices, determining song popularity based on occurrence across multiple playlists and sending this information to the music player unit to prioritize playing popular songs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If collaborative music playlists are shared among many participants, then more people can contribute their music preferences, but the playlist becomes unpractical due to long duration and diverse tastes
Solution Approach 1:
The patent extracts only the most popular songs from the collaborative playlist based on occurrence frequency analysis. By taking out and prioritizing songs that appear multiple times across different user playlists, the system eliminates less popular tracks, thereby reducing overall playlist duration while maintaining broad appeal to diverse audiences.
Solution Approach 2:
The system changes the parameter of song selection from equal weighting of all user contributions to frequency-based weighting. By analyzing how often each song appears across multiple playlists and using this occurrence data to determine popularity, the system transforms the playlist composition strategy to balance diversity of input with conciseness of output.
2Adaptability or versatility
If all user-contributed songs are included in the playlist, then every participant's taste is represented, but the music offering becomes unappealing due to lack of curation
Solution Approach 1:
The system implements feedback by analyzing playlist occurrence data to determine song popularity. Songs that appear frequently across multiple user playlists receive positive feedback in the form of higher play priority, while less frequent songs are deprioritized or excluded. This automated feedback mechanism enables intelligent curation that maintains quality while representing diverse tastes.
Solution Approach 2:
The system performs self-service curation by automatically analyzing the collaborative playlist data, determining song popularity based on occurrence frequency, and prioritizing songs without requiring manual intervention. The music player unit autonomously makes playback decisions based on the analyzed popularity metrics, eliminating the need for manual playlist management.
3Ease of operation
If manual playlist management is used in diverse environments, then curators can select songs, but it becomes impractical due to the large number of participants and varied tastes
Solution Approach 1:
The system replaces manual curation with automated self-service playlist management. The music player unit automatically receives collaborative playlists from multiple users, analyzes song occurrence frequencies, determines popularity metrics, and prioritizes playback accordingly. This eliminates the need for manual playlist management while simultaneously improving adaptability to diverse audience preferences through data-driven song selection.
Data Source
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AI summary
A method for an Application in a M2M Network Node, a M2M Network Node, an Application, and a method for a Music Player Unit and Music Player Unit are presented. A Music Playlist is received from a mobile device and is sent to Application in the M2M Network Node. The Application determines the popularity of the songs, which are included in the received Music Playlist. Determining the popularity is based on determining the occurrence of the songs in a M2M Music Playlist and the Music Playlist received from the Music Player Unit. Information about popularity of at least one song included in the received Music Playlist is then sent back to the Music Player Unit. Finally, the Music Player Unit plays-out the at least one song using a Speaker Unit.