Serious Games for Energy Applications in the Built Environment: A Systematic Review

Energy use in buildings is a major global challenge because it depends not only on technologies, but also on how people understand, operate, and respond to building systems. Serious games and gamified applications have been used to improve energy literacy, encourage energy-saving behavior, and support energy-related decision-making. However, evidence remains fragmented across building contexts, user groups, technologies, design approaches, and evaluation methods. It is still unclear how these interventions are designed, who they serve, and whether they produce measurable energy outcomes in real built-environment settings. This systematic literature review examines serious games and gamified applications for energy-related purposes in the built environment. The review analyses 69 empirical studies published between 2008 and 2026. Studies were examined according to application context, target users, learning objectives, game design features, interaction mechanisms, technologies, evaluation approaches, reported outcomes, and limitations across residential, educational, professional, and urban energy contexts. Findings show that most interventions target non-professional users, especially students and household residents, and are mainly evaluated in educational or controlled settings. Game design is dominated by accomplishment- and social-influence-based mechanisms, including challenges, points, feedback, progression, badges, competition, leaderboards, collaboration, and social comparison. More advanced approaches, including real-time building data, adaptive feedback, artificial intelligence, immersive environments, and professional decision-support tools, remain limited. Some studies reported short-term energy reductions, but evidence of sustained and independently verified real-world energy impact remains weak. The review contributes a hierarchical taxonomy linking system purpose, motivational design, user-building interaction, technological integration, and evaluation strategy, supporting future real-world, data-driven, and longitudinally validated interventions.