Indoor navigation is necessary for the new era of Internet of things (IoT) applications. Tracking objects in outdoor environments has been successfully implemented for many years using advanced tracking technologies, such as GPS. However, in indoor environments, GPS cannot work well due to the complexity of those environments that contain furniture and other objects and also the limitations of the line-of-sight (LoS) path from the satellite. Therefore, other alternative techniques have been adopted, such as infrared, radio wave, sound, visible light, and magnetic field technologies. The recent applications of AI, especially deep learning methods have significant impacts on different areas of indoor mapping and navigation, such as image and signal processing, information fusion, photogrammetry, geographical information systems (GIS), human-computer interaction (HCI), and others. Most recently, nature-inspired computational algorithms, including, evolutionary-based algorithms, swarm intelligence-based algorithms, and physical-based algorithms, have attracted researchers to be employed for different applications, such as feature selection, image processing, and optimization problems.

This Special Issue focuses on the applications of different AI and nature-inspired algorithms for indoor mapping, navigation, and related applications. The main goal of this Special Issue is to attract recent contributions of high-quality papers focusing on the recent advances of AI applications for indoor environment applications, such as mapping, navigation, modeling, 3D visualization, object tracking, human motion and activity recognition, location-based commerce services, and other related services. We welcome both original research and review papers.

Potential topics include but are not limited to the following:

• Indoor navigation systems
• Smartphone based localization
• Wi-Fi based localization
• Indoor hybrid positioning methods
• Indoor 3D mapping Indoor localization Indoor human motion tracking Indoor and outdoor navigation connection
• Indoor object motion detection Indoor location-based services
• Deep learning-based navigation Indoor navigation security and privacy 3D simulation and visualization
• Indoor human activity recognition Optimization for application of navigation