PRAHAR is an interactive, web-based experience dedicated to exploring the relationship between the time of day and Indian classical ragas. It invites participants to discover how specific ragas are traditionally associated with different phases of the day, reflecting changing moods, energies, and atmospheres through sound and interaction.
In Indian classical music, ragas are traditionally linked to specific times of day and night, known as prahars. Derived from an ancient Indian system of timekeeping, prahars divide the 24-hour day into eight segments, each lasting approximately three hours.
Each prahar is associated with particular emotional qualities and moods, which align with the ragas performed during that time. Morning ragas often evoke calmness and introspection, while evening and night ragas tend to express depth, longing, or serenity.
Prahar draws from this system to create an interactive way of experiencing these time-based associations, allowing users to move through the day and observe how music and emotion shift along with it.
After granting permission, Prahar activates the device’s webcam and uses real-time hand tracking to detect horizontal hand movement. This interaction is powered by TensorFlow.js with MediaPipe Hands.
As participants move their hand from left to right, the system maps this movement to a progression of time, from morning to evening, divided into distinct zones. Each zone triggers a specific Indian classical raga, alongside corresponding visual overlays and contextual information.
A frame-by-frame animation rendered on an HTML canvas responds continuously to the hand position, while sound transitions are handled through looped audio playback, creating a fluid, intuitive exploration of time, movement, and music.
When no hand is detected by the webcam, the experience automatically shifts to the current time of day. In this state, the animation scrubs to the corresponding prahar based on real-world time, and the associated raga and information are played accordingly.
ChatGPT was used as a coding assistant during the development of the HTML and interaction logic for the experience.
Anoop Saxena
Tejaswi Meshram
Advait Chebbi
Amruta Shandilya
Ananya Singh
Arjun Kumar Das
MS Athulkrishna
Avinash P Soman
Ayush Pratap
Bedangshu Saloi
Dev Manoj
Jaysi Nigam
Kaustav Purkayastha
Kusumita Asawa
Malavika KK