## 1 Introduction  
The construction and real estate sectors are undergoing a significant transformation due to the implementation of the BIM approach, which is increasingly being required by various global standards. Indeed, BIM technology possesses significant potential to enhance automation within the Architecture, Engineering, and Construction (AEC) sector and is progressively becoming a standard in numerous nations [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]. Based on the assumption that the BIM model is available when working on construction sites and particularly when managing large building assets, a number of technologies have been developed through dedicated software platforms that enable the tracking and asset management phases of even extensive building assets. Specifically, some application platforms allow the recognition of assets in the field while concurrently geo-locating them by using images acquired by mobile cameras. Consequently, appropriate software platforms facilitate centralized asset management through the population of management databases and enable sophisticated functionalities that permit field operators to autonomously find out where they are within the building and identify and \"tag\" objects and elements in the field, thus allowing real time compilation and updating of what is happening in the field, rather than merely managing the collection of such valuable information and data in real time from the operations center. Unfortunately, although it is possible to tag objects in images, in the absence of a three-dimensional model of the surveyed environments, it is not possible to geolocate the detected objects. A possible solution could consist in the use of instruments capable of simultaneously acquiring both the three-dimensionality of the environments and high-quality photographs, such as the latest generation laser scanners such as the Z+F IMAGER(r) 5010C with the HDR I-Cam camera [13], but the timelines and, consequently, the costs of such survey activities are incompatible with the timelines of a rapid acquisition of assets in the field using the previously described systems [14]. An interesting technological innovation has been the introduction of high resolution cameras within iMMS systems. These instruments are highly competitive in terms of accuracy and acquisition speed of the three-dimensional component, allowing for the simultaneous capture of high-quality/high resolution images. This has enabled the use of these devices even for applications within large real estate portfolios, offering sustainable advantages in terms of surveying time and costs compared to the static laser scanning method. Through camera integration, iMMS systems simultaneously provide the recognition and geolocation of assets, the generation of site maps, and the enabling of three-dimensional measurements throughout buildings. Web-based virtual tour navigation within the buildings can also be implemented, and a 3D point cloud of the site can be obtained. The article presents, in Section 2, \"State of the art of systems for Indoor Mobile Mapping (iMMS)\", the evolution over time and the state-of-the-art of indoor mobile mapping (iMMS) technologies and possible future developments, highlighting the characteristics, merits, and limitations of this approach for geospatial applications. Section 3, \"Building Asset Facility Management' introduces the concept of building asset management, explores the technologies currently used for this purpose, and discusses how mobile mapping devices can contribute to the field. Section 4, \"A Case Study in Milan, Italy', describes the successful case study conducted at the Municipality of Milan, where iMMS technologies were used to carry out an asset census of the municipality's entire housing property stock. A major real estate asset management company initiated the project to rapidly perform geometric surveying, inventory, and updating of assets within the housing portfolio.