Due to the rapid technical development of computer and internet technologies, more and more new applications are becoming possible. Virtual Reality (VR), Augmented Reality (AR) is very often realized with technologies from the field of visual effects, for example, through real-time rendering, artificial intelligence, and high-quality 3D assets. As part of the digital transformation, VR and AR have also been developed for the event industry in recent years, especially for mega-events. As a result, the technologies are increasingly being used. However, processing on mobile devices in these qualities, like smartphones, can still be a challenge, but more and more solutions are being described and developed. On the occasion of the planned 300th anniversary of Immanuel Kant's birth in 2024, there are excellent visualization possibilities for AR applications, for example, the creation of 3D models.

360-degree image and movie content has gained popularity over the media and the MICE (Meeting, Incentive, Conventions, and Exhibitions) industry in the last few years. There are three main reasons for this development. First, on the one hand, it is the immersive character of this media form, and, on the other hand, the development of recording and presentation technology has made significant progress in terms of resolution and quality. Third, after a decade of dynamic rising, the MICE Industry focuses on a disruptive change for more digital-based solutions. 360-degree panoramas are particularly widespread in VR and AR technology. However, despite the high immersive potential, these forms of presentation have the disadvantage that the users are isolated and have no social contact during the performance. Therefore, efforts have been made to project 360-degree content in specially equipped rooms or planetariums to enable a shared experience for the audience.

Autonomous vehicles design and development can move safely on roads while sensing the environment to focus on pedestrian detection systems so that people can be detected as quickly and accurately as possible. First, however, it is critical to examine the pedestrians themselves and their color, which benefits from being insensitive to changes in scale and partial occlusion. Moreover, human skin detection has proven to be a tough challenge since skin color can vary considerably in appearance due to various factors such as lighting, race, and imaging circumstances. Unfortunately, human skin detection has not been thoroughly investigated in this circumstance, and it appears that many studies do not address this systematically when it comes to pedestrian detection systems for autonomous cars. To overcome this issue, we are using a Radar-Camera fusion technique to predict obstacles in various daylight situations.