A substantial share of the hotel sector's consumption and carbon footprint is in air conditioning (HVAC), lighting, and occupancy-related operational dynamics. In the context of the global energy transition goals, rising energy costs, and increasing pressure to reduce greenhouse gas emissions, improving energy efficiency in hotel rooms has become a strategic priority. In recent years, Internet of Things (IoT) technologies and building automation systems have been increasingly proposed as key enablers for optimizing energy use and mitigating CO₂ emissions in building interiors. Despite the rapid growth of scientific publications in this field, there remains a lack of consolidated evidence on performance indicators, technological architectures, empirical robustness, and real-world applicability, particularly in the hospitality sector. This study aims to systematically analyze international research on IoT-based energy efficiency in hotel rooms by identifying energy and environmental indicators used to evaluate performance, examining the reported benefits and limitations of intelligent systems, and assessing the overall maturity of the research field from a universal implementation perspective. A systematic literature review was conducted in accordance with the PRISMA guidelines. One guiding research question informs the selection criteria: which achievements are associated with the use of IoT tools in the hotel sector? After applying the predefined inclusion and exclusion criteria, a final corpus of 60 peer-reviewed scientific articles has been selected. To ensure a structured and replicable synthesis, a hierarchical analytical framework composed of seven research questions was developed and organized into four analytical levels: (A) What is studied (technologies and system definitions), (B) how it is studied (experimental design and measurement approaches), (C) what is demonstrated (energy and CO₂-related outcomes and limitations), (D) for what purpose it is applied (implementation strategies and decision support). Each article was evaluated using an ordinal scoring scale ranging from 1 (not relevant) to 4 (in-depth analysis with precise empirical results), resulting in a 60 × 7 analytical matrix. Quantitative synthesis was performed using frequency analysis, average depth scores, and consistency measures. Additionally, a research maturity index was developed to assess the developmental stage of IoT-based energy-efficiency research. The results indicate that most studies focus on HVAC and lighting systems, with occupancy smart meters, environmental sensors, smart thermostats, and centralized energy management platforms being the most frequently analyzed technologies. Energy consumption (kWh), HVAC operating time, and indoor temperature are the most reported indicators, while carbon footprint metrics are less consistently quantified. Although a large proportion of studies report energy savings associated with IoT-based control strategies, only a limited subset provides robust empirical evidence derived from experimental or quasi-experimental designs under real operating conditions. Human and operational factors, such as occupant behavior and system overrides, are repeatedly identified as significant constraints on actual energy performance, but there is a lack of empirical evidence. The research maturity index reveals that, while IoT-based energy-efficiency research is generally progressing toward consolidation, its application to hotel rooms remains largely exploratory, with persistent gaps in indicator standardization, scalability, and replicability. Within this investigation, an indicator system has been proposed, built with all the systems that have been mentioned in most articles, to contribute to further implementations of future research. From an operational perspective, these results have direct implications for hotel management. IoT systems not only reduce energy consumption but also enable predictive maintenance strategies, improve the guest experience through automated climate control, and generate valuable data for daily operations, including indoor temperature and humidity, daily guest presence times, and AC activation times, among others. The hotel industry operates with narrow margins and is subject to increasing corporate sustainability goals; therefore, systems capable of dynamically responding to actual occupancy and optimizing HVAC performance represent a competitive advantage. However, the lack of consolidated evidence hinders informed decision-making, making further studies in real-world operating environments essential to transforming these potential benefits into standard industry practices. This study concludes that IoT-based intelligent systems have substantial potential to improve energy efficiency and mitigate CO₂ emissions from the hospitality sector. However, advancing toward scalable and replicable energy solutions requires greater methodological rigor, standardized energy performance indicators, and pilot-scale experimental implementations conducted in real hotel environments. By systematically synthesizing existing evidence and identifying critical technical and methodological gaps, this research provides a robust foundation for future experimental studies. It supports the development of data-driven energy management strategies aligned with the objectives of sustainable, low-carbon building operations.