This review systematically examines research on indoor thermal comfort for older adults conducted in China since 2010. It highlights several existing research gaps, including the lack of a systematic understanding of environmental and individual influences, limitations of thermal comfort models, challenges in their optimization, and inadequate integration of intelligent technologies. Results indicate that environmental factors usually exert a greater impact on the elderly’s neutral temperature than individual factors. Thermal comfort models differ in predictive accuracy, data requirements, and applicability. The adaptive predicted mean vote (aPMV) model is better suited for group-level assessments. Machine learning (ML) models, featuring high flexibility and accuracy, are more appropriate for personalized predictions. In addition, physiological parameters could play a critical role in thermal assessments. When integrated with ML models, physiological parameters could further improve predictive accuracy. When integrated into artificial intelligence (AI) and Internet of Things (IoT) systems, forehead and back skin temperatures could act as early-warning indicators during heat exposure, while lower-limb temperatures are more indicative of thermal discomfort during cold exposure. Overall, this review summarizes current progress and limitations, offering a reference for the development of user-friendly modeling and intelligent temperature-control systems.

Tropical daylight provision is inherently coupled with intensive solar heat gains, particularly in south-facing rooms that experience pronounced seasonal variations in solar altitude and exposure across different times of the year. When appropriately designed, external shading devices can mitigate solar heat gains while maintaining adequate indoor daylight availability. This study investigates the daylighting and thermal performance of a representative south-facing apartment room equipped with combined horizontal and vertical slat-based shading devices using a controlled, comparative simulation framework under tropical climate conditions. Parametric simulations were conducted using IES-VE to evaluate multiple shading configurations with varying slat positions, depths, and combinations under representative sky conditions and seasonal design days. The results demonstrate that mid-height horizontal slat configurations reduced front-zone Estimated Indoor Illuminance (EII) by up to 54.9%, while enhancing daylight penetration into deeper areas under direct sunlight conditions. Bottom horizontal slats further improved daylight distribution by reflecting sunlight into deeper zones, producing peak increases in EII of up to 26.8% in the middle zone and 19.7% in the rear zone under direct solar conditions. The addition of vertical slats further improved thermal performance by limiting lateral solar exposure without significantly diminishing the daylight-redirecting effects of horizontal elements. Selected integrated shading configurations achieved maximum reductions in operative temperature of up to 2.5 °C during peak afternoon periods compared with the base case within the adopted evaluation framework. However, under intermediate sky conditions without direct solar contribution, the daylighting and thermal benefits of slat-based shading were substantially reduced. Based on these findings, the study proposes a movable external shading system with adjustable horizontal and vertical slats for south-facing apartment rooms, intended to respond to changing solar conditions across the evaluated design days. Overall, this study provides mechanism-oriented insights to support the development of climate-responsive façade strategies for tropical high-rise residential buildings, with the aim of improving daylight distribution and reducing cooling demand.