Joseph C. Kenny (PhD Student, Project Lead), Dr. Samuelle Bourgault, Philippe Maman, Soulaf Aburas
Prof. Dr. Daniela Mitterberger
Collaborators:
Populous Applied R&D
Photo & Video:
Samuelle Bourgault, Charlie Burt, & Keith Zhang
Event Information:
Date: April 2nd, 2026
Location: Populous Headquarters, Kansas City, MO
Description: The event included a 1-hour presentation with an overview of the Pixelate project, including its research context, system design, and approach to multi-user interaction on public displays. Further, it was followed by a 2-hour interactive demonstration session, during which attendees from all across North America engaged with the system directly in a hybrid online/in-person session with the system.
Publication (Poster) :
J. C. Kenny, S. Bourgault, P. Maman, S. Aburas, and D. Mitterberger, “Poster: Pixelate: An Event-Driven System for Scalable Distributed Multi-User Interaction on Public Displays,” in Proceedings of the 20th ACM International Conference on Distributed and Event-based Systems, Universidade de Lisboa Lisbon Portugal: ACM, Jun. 2026, pp. 175–177. doi: 10.1145/3809481.3816719.
Pixelate explores scalable multi-user interaction on public displays through a platform-independent collaborative drawing system. Developed as a distributed, event-driven application, the project examines how large numbers of co-located and remote users can interact with a persistent shared canvas across different devices, locations, and display configurations.
The system supports real-time synchronization, persistent shared state, and application-level concurrency control across web, Android, and iOS clients. Users select, modify, or erase pixels within a shared canvas, while transient locking and event-based reconciliation coordinate simultaneous interactions and resolve conflicts between distributed participants.
Pixelate was evaluated through a public deployment spanning at least four cities and three time zones, connecting 75 unique clients through personal devices, tablets, phones, laptops, and mixed-reality headsets. At peak use, the system supported 69 concurrent users and 48 simultaneous selections, demonstrating an approach to persistent, cross-platform collaboration on large-scale public interactive displays.
The system supports real-time synchronization, persistent shared state, and application-level concurrency control across web, Android, and iOS clients. Users select, modify, or erase pixels within a shared canvas, while transient locking and event-based reconciliation coordinate simultaneous interactions and resolve conflicts between distributed participants.
Pixelate was evaluated through a public deployment spanning at least four cities and three time zones, connecting 75 unique clients through personal devices, tablets, phones, laptops, and mixed-reality headsets. At peak use, the system supported 69 concurrent users and 48 simultaneous selections, demonstrating an approach to persistent, cross-platform collaboration on large-scale public interactive displays.
interaction tools, color controls, action history, and interface legend. (B) Randomized interaction, which selects pixels according to a stochastic pattern. (C) Linear incremental selection, which extends selection step-by-step across adjacent pixels. (D) Free-form touch selection, allowing users to directly mark pixels through touch input. (E) Multi-user selection, showing simultaneous local and remote selections within the shared canvas.
the system data model. ScreenData stores persistent session
and pixel-grid state, UserCurrentSelection manages tran-
sient selection locks, and InteractionLog records append-
only interaction events used to synchronize updates across
connected clients.