This study aims to develop a human-centric, intelligent lighting control system using adaptive LED lights in roadway lighting, integrated with an imaging luminance meter that uses an IoT sensor driver to detect the brightness of road surfaces. AI image data are collected for luminance and vehicle conditions analyses to adjust the output of the photometric curve. Type-A lenses are designed for R3 dry roads, while Type-B lenses are designed for W1 wet roads, to solve hazards caused by slippery roads, for optimizing safety and for visual clarity for road users. Data are collected for establishing formulae to optimize road lighting. First, the research uses zonal flux analysis to design secondary optical components of LED roadway lighting. Based on the distribution of LED lights and the target photometric curve, the freeform surface calculation model and formula are established, and control points of each curved surface are calculated using an iterative method. The reflection coefficient of a roadway is used to design optical lenses that take into account the illuminance and luminance uniformity to produce photometric curves accordingly. This system monitors roadway luminance in real time, which simulates drivers’ visual experiences and uses the ZigBee protocol to transmit control commands. This optimizes the output of light according to weather and produces quality roadway lighting, providing a safer driving environment.

The paper aims to explore the relationship between the vertical plane luminance on projection screens and human visual clarity in the classroom or meeting room. While controlling the lighting environment conditions of the classroom to create different luminous distributions and luminance on the projection screen, a survey is conducted to understand students’ visual experience about screen clarity during the field experiment. The luminance of each picture on the projection screen is measured under the specified lighting conditions of luminaires in the classroom, and the relationship is formulated between the average luminance on the projection screen and the visual satisfaction based on clarity of experience. This will be useful for further studying the acceptable threshold of luminance distribution in the classroom to provide a better visual clarity and lighting quality of projection screens while teaching. In this study, the measurement and performance evaluation on a projection screen were carried out at a classroom in the National Taiwan University of Science and Technology (NTUST). By using an image luminance meter and analyzing the research results, we propose an improvement strategy for asymmetric luminous distribution design of LED light tube and light switch control mechanism of luminaires to resolve the inadequate luminance of the vertical projection screen area to improve the lighting quality and visual clarity of the projection screen while teaching with the least cost.