Global warming, climate change and the energy crisis are trending topics around the world, especially within the energy sector. The rising cost of energy, greenhouse gas (GHG) emissions and global temperatures stem from the over-reliance on fossil fuel as the major energy resource. These challenges have highlighted the need for alternative energy resources and urgent intervention strategies like energy consumption reduction and improving energy efficiency. The heating, ventilation, and air-conditioning (HVAC) system in a building accounts for about 70% of energy consumption, and a decision to reduce energy consumption may impact the indoor environmental quality (IEQ) of the building. It is important to adequately balance the tradeoff between IEQ and energy management. Artificial intelligence (AI)-based solutions are being explored for improving building energy performance without compromising IEQ. This paper systematically reviews recent studies on AI and machine learning (ML) for building energy management and IEQ by exploring common use areas, the methods or algorithms applied and the results obtained. The overall purpose of this research is to add to the existing body of work and to highlight energy-related AI applications in buildings and the related gaps. The result shows five common application areas: thermal comfort and indoor air quality (IAQ) control; energy management and energy consumption prediction; indoor temperature prediction; anomaly detection; and HVAC controls. Gaps involving policy, real-life scenario applications, and insufficient study of the visual and acoustic comfort areas are also identified. Very few studies take into consideration the need to follow IEQ standards in the selection process and positioning of sensors in AI applications for IEQ in buildings. This study reveals a need for more systematically summarized research.

This systematic literature review (SLR) focuses on indoor environmental quality (IEQ) in passenger transport vehicles within tropical and subtropical regions. It specifically examines indoor air quality (IAQ), thermal comfort (TC), acoustic comfort (AC), and visual comfort (VC) of passenger vehicle cabins (PVCs) in auto rickshaws, sedans, trucks, bus rapid transits (BRTs), buses, trains, trams, metro systems, aircraft and ferries of tropical and subtropical regions. The SLR used the PRISMA approach to identify and review scientific studies between 2000 and 2024 on the IEQ of PVCs in the tropics. Studies reviewed were found in SCOPUS, Web of Science, Science Direct, and EBSCO databases including relevant citation references. Findings reveal a significant geographical imbalance in research, with most studies concentrated in tropical Asia (78.2%), while sub-Saharan Africa (8.2%), South America (11.8%), and Oceania (1.8%) are considerably underrepresented. In 113 studies, most addressed IAQ and TC but limited attention to AC and VC. Moreover, fewer studies have jointly addressed all the IEQ parameters, highlighting the need for a more comprehensive approach to IEQ for tropical PVCs. Several studies alluded to in-cabin commuter risk linked to PM_2.5, PM₁₀, carbon monoxide (CO), and volatile organic compounds (VOCs). These risks are exacerbated by traffic hotspots, poor ventilation, ambient pollution, overcrowding, and poor vehicle conditions. Additionally, thermal discomfort is compounded by extreme heat loads, inefficient HVAC systems, and high vehicle occupancy. Common gaps include a paucity of IEQ studies and inadequate IEQ regulations or adapted standards in developing tropics. Infrastructural and regulatory deficiencies have been identified, along with strategies for mitigation. Recommendations are for more holistic IEQ studies in the tropics, including exposure studies for emerging gaps in new indoor pollutants, integration of AI and IoT for sustainable ventilation strategies, and development of effective regulatory frameworks considering region-specific conditions. Finally, Policymakers are encouraged to establish localized IEQ standards, enforce regulations, and prioritize upgrades to transport infrastructure. The SLR findings emphasize the urgent need for targeted interventions in developing tropical regions to address disparities in IEQ, ensuring healthier and more sustainable transport environments that could be replicated across transport systems worldwide.

The indoor climate quality in classrooms at the University of Coimbra, Portugal, was investigated as part of the 3SqAir project, supported by the Interreg SUDOE program. This research focused on two equipped classrooms with different ventilation systems: natural and mechanical ventilation. Both classrooms were continuously monitored for IEQ parameters: thermal comfort, indoor air quality, noise, and lighting during heating and cooling seasons. Air temperature, relative humidity, CO₂ concentration, particulate matter, nitrogen dioxide, volatile organic compounds, formaldehyde, sound pressure level, and illuminance were measured. Outdoor weather conditions were also recorded. The primary focus was on air temperature, CO₂ concentrations, and relative humidity, while air change rates (ACH) were estimated using the Tracer Gas Method. The results showed inadequate thermal conditions in both classrooms, particularly during the heating season. Most weekly mean CO₂ concentrations were within acceptable limits, while ACH were below standard recommendations in four CO₂ decay phases. Simulations of CO₂ decay revealed further air quality gaps in each room. Corrective measures within the 3SqAir project framework were suggested for approval and implementation while monitoring continues. This work represents the first phase in an evolving study towards developing sustainable strategies for improving indoor air quality in classrooms.

The present study proposes a full-scale experimental methodology for testing and quantifying the trajectory deviations induced in road vehicles. A full-scale articulated bus was employed in this work and tested under real operating conditions. In its foreseen exploitation use, the vehicle will, under certain conditions, be automatically guided (to cross bridges and tunnels and to approach and stop at bus stops). A series of tests was conducted on a bridge under different transverse wind conditions. It is important to note that the deviation measured by the laser system includes both the inherent deviations of the optical guidance system (OGS) and those induced by wind. It was observed that, despite trajectory variability, when measured at high spatial resolution (±1 mm) during the approach phase upstream of the test zone, the optical guidance system corrected deviations from the ideal trajectory within a short time interval and over a short distance. The system’s response shows reasonable agreement with the manufacturer’s results reported in the OGS study. The results also show some degree of dispersion, given multiple sources of uncertainty inherent to full-scale testing under real operating conditions. The findings show that the OGS’s dynamic response is adequate to reduce disturbances to the vehicle’s trajectory caused by crosswind.

As part of the EduClimAir project, this study aimed to improve indoor comfort conditions by experimentally evaluating acoustic, thermal, and visual comfort, as well as indoor air quality, in two classrooms with different ventilation types (natural and mechanical) at the Department of Mechanical Engineering, University of Coimbra. Both classrooms are part of a living-lab setup where indoor environmental quality (IEQ) parameters (air temperature Ta, relative humidity RH, carbon dioxide CO₂ and particulate matter PM concentrations, A-weighted equivalent continuous sound pressure level LAeq) are continuously monitored. Representative data across one semester (September through December) is presented in two phases and one day, highlighting the teaching period timeframe, LAeq_Work_P. One phase is a chronological sequence of one week of non-occupancy and one week of occupancy. Results during occupancy showed LAeq_Work_P reached up to 60 dBA (room 3.3) and 65 dBA (room 6.3) in the first phase, and up to 55 dBA (room 3.3) and 57 dBA (room 6.3) in the second phase. Noise was suboptimal, though considered moderate and tolerable in a university setting. During non-occupancy, LAeq_Work_P remained broadly within WHO/ANSI S12.60 limits in the first phase but often exceeded 40 dBA in the second phase due to heating, ventilation, and air conditioning (HVAC) systems operating during unoccupied days, a gap in energy management. An evaluation of noise, Ta, CO₂, and PM interactions in one day suggests IEQ gaps. The study revealed HVAC management and IEQ gaps otherwise be missed outside a continuous monitoring and multidomain assessment approach.