Interactive Synthesis: Immersive Public Space Murals Using Generative AI and Real-Time Audience Interaction

Project Abstract

This study investigates the design, deployment, and impact of immersive public space murals created through Generative AI technologies and real-time audience interaction, aiming to redefine communal experiences, democratize visual storytelling, and expand the capabilities of artists working at the intersection of design, computation, and social engagement. By synthesizing advances in neural networks, procedural generation, computer vision, and interactive media, the research develops a scalable framework for generating large-scale mural visuals that respond to environmental context, cultural narratives, and live audience inputs. The project encompasses a multidisciplinary methodology that combines design research, computational prototyping, field deployments, and evaluative studies, ensuring both aesthetic quality and social relevance in diverse urban settings. A core objective is to establish interpolation between algorithmic outputs and human agency, enabling participants to influence color schemes, form evolution, motion patterns, and narrative arcs in real time through accessible interfaces and sensor-driven cues. The work investigates how generative systems can maintain cohesion with architectural scale, mural longevity, and maintenance practices while still offering dynamic variability that invites ongoing public dialogue. It also interrogates ethical considerations, including inclusivity, representation, consent, and the mitigation of algorithmic bias, ensuring that generated imagery reflects community values and avoids perpetuating stereotypes. The research design includes a literature-informed analysis of mural traditions, AI-assisted art practice, and participatory design methodologies, followed by iterative design-build cycles in which artists collaborate with technologists to test prototypes on both small-scale models and public facades. Data collection methods span observational field notes, user experience surveys, interviews with participants, and telemetry from interaction interfaces, complemented by computational metrics for image coherence, stylistic diversity, and temporal responsiveness. A mixed-methods evaluation examines perceptual effectiveness, emotional engagement, place attachment, and social interactions catalyzed by the murals, while considering durability, weather resistance, and maintenance workflows in outdoor environments. The expected outcomes include a validated design protocol for responsibly integrating generative models with human-centered curation, a toolkit for artists to customize generative parameters without deep programming expertise, and an impact assessment framework capable of informing urban cultural policy and public art commissioning. Additionally, the work contributes to theoretical discourse on authorship in AI-augmented art, proposing models of co-creation that balance algorithmic novelty with deliberate, community-informed direction. By demonstrating scalable deployment strategies, robust interaction modalities, and ethical guardrails, this research aspires to empower cities to cultivate meaningful, participatory, and evolving mural ecosystems that reflect collective memory and contemporary urban identity.

Project Overview

What This Project Is About

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A straightforward look at how public murals can be created with AI that learns from crowds and reacts in real time, blending art and technology in shared urban spaces.

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The Problem It Addresses

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Public murals are often static and limited by a single artist’s vision. This project explores whether generative AI and interactive systems can expand creative possibilities while encouraging community participation and accessibility.

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Objectives of the Project

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1. Demonstrate a system that generates mural designs using AI with inputs from passersby.
2. Evaluate how real-time audience feedback changes the artwork over time.
3. Develop a simple workflow that artists can use to deploy interactive murals in public spaces.
4. Assess social and cultural impacts of interactive murals on communities.

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What You Will Do Step by Step

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1) Review existing public art projects and basic AI tools for image generation. 2) Design a crowd-interaction method (e.g., simple prompts or gestures). 3) Build a lightweight prototype that can run in a public area. 4) Collect feedback from observers and record changes in the mural design. 5) Analyze which interactions influence the artwork most. 6) Document the process and prepare a display-ready version of the mural.

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Expected Outcome

A functioning interactive mural prototype with a clear method for crowd input, plus a concise report on how audience interaction shaped the artwork and its potential for broader use in cities and communities.