Over the past decade, there has been a dramatic increase in the use of various technologies in the Architecture, Engineering, and Construction sector. Artificial intelligence has played a significant role throughout the different phases of the design and construction process. A growing body of literature recognizes the importance of artificial neural network applications in numerous areas of the construction industry and the built environment, presenting a need to explore the main research themes, attributes, benefits, and challenges. A three-step extensive research method was utilized by conducting a bibliometric search of English language articles and conducting quantitative and qualitative analyses. The bibliometric analysis aimed to identify the current research directions and gaps forming future research areas. The scientometric analysis of keywords revealed diverse areas within the construction industry linked to ANNs. The qualitative analysis of the selected literature revealed that energy management in buildings and construction cost predictions were the leading research topics in the study area. These findings recommend directions for further research in the field, for example, broadening the application ranges of ANNs in the current Construction 4.0 technologies, such as robotics, 3D printing, digital twins, and VR applications.

Purpose: To test whether indoor sound shows a non-monotonic dose-response with occupant health and productivity in mechanically ventilated offices, using formal threshold inference. Design/methodology/approach: A total of 365 sensor-survey observations from 42 occupants across 12 mechanically ventilated office zones in Doha, Qatar; confirmatory analyses pre-specified in an internal pre-analysis plan. Segmented logistic regression with occupant-clustered errors, Davies' supremum-Wald existence test, profile-likelihood intervals and Bayesian random-intercept sensitivity. Findings: A composite of noise-pathway symptoms (headache, anxiety, low energy) inflects in the 44–52 dB(A) band (Davies' p = 0.038; point estimate 47.75 dB(A)), with a corroborating regime change in the acoustic productivity rating at 49 dB(A). It holds under IEQ adjustment, in 4 of 7 alternative composites and under Bayesian sensitivity; negative controls do not. Research limitations/implications: Findings apply to hot-arid mechanically ventilated offices and are cross-sectional. Exposure is hour-averaged A-weighted level only, so the acoustic mechanism is not identified. An underpowered symptom-class interaction leaves the noise-pathway interpretation resting on component-level negative-control behaviour, and significance depends on clustering by occupant or zone. Practical implications: The band offers preliminary evidence relevant to provisions bearing on over-quiet conditions in WELL v2, BREEAM Hea 05 and ISO 22955:2021, which rest on privacy inference, not symptom data. Acoustic operation is better expressed as a target band than a quieter-is-better rule. Originality/value: First application of Davies' supremum-Wald threshold inference to multi-domain indoor environmental quality field data, giving a transferable pattern for dose-response research.