Introduction
Indonesia faces a severe residential energy crisis, with household usage accounting for around 42% of national electricity use, and energy literacy levels remain low. It costs Indonesia an estimated 15-20 trillion rupiah annually in lost economic activity due to electrical waste, such as vampire power problems, commonly considered standby and energy waste. Current traditional energy audits, which are very costly, require trained auditors and cannot be scaled to a million homes in Indonesia, making it harder for citizens to be aware of energy-saving issues. As a result, there exists a significant intention-action gap for the average citizen to understand abstract concepts such as saving energy because they cannot easily get energy-saving education and apply their understanding to sustainable action. In this paper, we present IuditAR as a solution to the residential energy crisis in Indonesia, part of the Game-As-Reality (GAR) verse in sustainability, which employs a novel GAMERS protocol (Geste, Ambience, Mechanics, Engine, Reality, Sustainability). In contrast to passive education methods or pure gamification/game-based learning, the GAR-verse paradigm turns the home itself into a playable audit environment where the user can interact with real appliances as virtual game objects using AI-powered markerless augmented reality and obtain progress within the game upon completing verified actions. It can be a game-changer for energy-saving actions to make them more engaging and effective.
Methods
We conduct a quasi-experiment as a pilot study to evaluate the feasibility and initial user engagement of the IuditAR system using 32 participants over a one-week period. Our IuditAR utilizes AI for device detection with around 95% accuracy, markerless augmented reality for generating context-aware energy-saving missions, and giving personalized advice. It is operationalized in GAMERS protocols as follows: G (Geste), a narrative story to frame users as “Energy Guardians” on a hero’s journey; A (Ambience), a hybrid physical and digital environment to support AR panels attached to detected appliances; M (Mechanics), a mechanism to award users XP/badges only upon successful completion of actions that were verified; E (Engine), supporting technology and tools to educate; R (Reality), a connection from the program to real impact conducted by users in real life; and S (Sustainability), features to support streak mechanisms and cumulative savings dashboards for users to sustain behavior change and retention. We measure the outcomes via several indicators using KAB (knowledge, attitudes, behavior) toward energy-saving and the GAMERS framework experience scale.
Results and Conclusion
Based on our study, we found significant results in several parameters. Participants engaged with a mean of 36.5 AI scans/user across >50 household objects to identify potential savings. In the KAB (knowledge, attitude, and behavior) parameter, participants’ knowledge scores and attitudes towards energy behaviors changed significantly (p<0.0001) from the baseline, indicating that they would take action to save energy. They also demonstrated high compliance with the behavioral checklist, with more than 90% of users reporting sustaining energy-saving actions such as unplugging gadgets after charging and turning them off. Our system validates their energy-saving actions by verifying their uploaded photos. In the GAMERS experience scale, the Reality and Geste components received the highest ratings and predict participants' behavior significantly. It indicates that digital progression in a game to physical actions that have been verified by AI can be a powerful mechanism for locking in behavior changes that are not available in conventional apps or usual games/simulations.
This pilot study demonstrates the feasibility and user acceptance of the GAMERS protocol as a scalable framework for energy education. While the current results rely on self-reported data with verification in the app to verify their results and limited participants, they provide a strong foundation for future research. The next phase of development will focus on validating these behavioral changes through integration with PLN (state utility) smart meter data and conducting longitudinal Randomized Controlled Trials (RCTs) to objectively measure kilowatt-hour reduction. IuditAR represents a promising step toward scalable, AI-driven sustainability tools for the Global South, aligning with SDG 7 and Indonesia’s 2060 net-zero goals.
