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In recent years, green energy has undergone a lot of development and has been the subject of many applications. Many research studies have focused on illumination with sunlight as a means of saving energy and creating healthy lighting. Natural light illumination systems have collecting, transmitting, and lighting elements. Today, most daylight collectors use dynamic concentrators; these include Sun tracking systems. However, this design is too expensive to be cost effective. To create a low-cost collector that can be easily installed on a large building, we have designed a static concentrator, which is prismatic and cascadable, to collect sunlight for indoor illumination. The transmission component uses a large number of optical fibers. Because optical fibers are expensive, this means that most of the cost for the system will be related to transmission. In this paper, we also use a prismatic structure to design an optical coupler for coupling n to 1. With the n-to-1 coupler, the number of optical fibers necessary can be greatly reduced. Although this new natural light illumination system can effectively guide collected sunlight and send it to the basement or to other indoor places for healthy lighting, previously there has been no way to manage the collected sunlight when lighting was not desired. To solve this problem, we have designed an optical switch and a beam splitter to control and separate the transmitted light. When replacing traditional sources, the lighting should have similar characteristics, such as intensity distribution and geometric parameters, to those of traditional artificial sources. We have designed, simulated, and optimized an illumination lightpipe with a dot pattern to redistribute the collected sunlight from the natural light illumination system such that it equals the qualities of a traditional lighting system. We also provide an active lighting module that provides lighting from the natural light illumination system or LED auxiliary sources, depending on circumstances. The system is controlled by a light detector. We used optical simulation tools to design and simulate the efficiency of the active module. Finally, we used the natural light illumination system to provide natural illumination for a traffic tunnel. This system will provide a great number of benefits for the people who use it.

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Highlights We developed a deep learning system for automatic ICH detection and subtype classification. Our method produced AUCs around 0.99 for each ICH subtype and won 1st place in the RSNA challenge. Our method generalizes across two independent external validation datasets. Visualization technique makes the system more easily acceptable for clinicians.