Occupancy information is a key element for improving building energy performance and occupant comfort through occupancy-centric control strategies. However, the rapid development of occupancy-related research over the past years has led to fragmented terminology and heterogeneous analytical perspectives, which complicate consistent comparison and interpretation of results. To address this issue, this paper proposes an analytical occupancy information framework that structures the literature according to complementary dimensions: occupancy scale, information level, acquisition strategy, modeling approach, temporal dimension, and system constraints. Based on this framework, a systematic review of the literature is conducted under a novel analysis axis based on occupancy scale. The analysis highlights trade-offs between information richness, deployability, privacy constraints, and control relevance across scales. Occupancy presence and estimation appear as the most widely investigated and practically exploitable information levels for energy-oriented applications, particularly at zone and multi-zones scales, where they are more directly integrated into HVAC control strategies. More detailed information levels, such as localization, tracking, activity, comfort, and behavior, provide complementary insights but remain constrained by sensing complexity, privacy considerations, and challenges in generalization. Across occupancy scales, black-box modeling approaches are the most frequently adopted in the literature, while gray-box and knowledge-based approaches offer potential advantages in terms of interpretability and adaptability. Overall, the proposed framework provides a unified perspective on occupancy information modeling, clarifies the respective contributions and limitations associated with each occupancy scale, and identifies key challenges and research directions toward scalable, privacy-aware, and energy-efficient building control systems.
BOURGOIN et al. (2026) studied this question.