Francisco Troncoso-Pastoriza 
- (2020): Model Calibration Methodology to Assess the Actual Lighting Conditions of a Road Infrastructure. In: Infrastructures, v. 5, n. 1 (January 2020).
- (2022): IoT-based platform for automated IEQ spatio-temporal analysis in buildings using machine learning techniques. In: Automation in Construction, v. 139 (July 2022).
- (2021): Use of optimised MLP neural networks for spatiotemporal estimation of indoor environmental conditions of existing buildings. In: Building and Environment, v. 205 (November 2021).
- (2020): Ellipsoid-based approximation method for the estimation of the actual reduced luminance coefficients of road surfaces for accurate lighting simulations. In: Sustainable Cities and Society, v. 63 (December 2020).
- (2018): Generation of BIM data based on the automatic detection, identification and localization of lamps in buildings. In: Sustainable Cities and Society, v. 36 (January 2018).
- (2019): Use of BIM data as input and output for improved detection of lighting elements in buildings. In: Automation in Construction, v. 106 (October 2019).
Structurae cooperates with
