###### Abstract  
During the dynamic development of modern technologies based on advanced algorithmic and instrumental solutions, it is essential to integrate geospatial data efficiently. Such an approach is applied in all geo-information services, especially mobile ones, and is helpful in, for example, precise navigation or effective risk management. One leading application is deformation monitoring (structural monitoring) and displacement control surveying. In addition, spatial data integration methods are used in modern accessibility analysis, Smart City ideas, tracing utility networks, and building information modelling (BIM). The last aforementioned technology plays a crucial role in architectural design and construction. In this context, it is crucial to develop efficient and accurate algorithms supporting data fusion, which do not strain the computing resources and operate efficiently online. This paper proposes an algorithm for real-time adjustment of integrated satellite GNSS (global navigation satellite system), total station, and Earth Gravitational Model (EGM) vertical direction data in a geocentric coordinate system based on a statistical general linear mixed model. A numerical example shows that the proposed algorithm of the online adjustment works correctly. The results of the online adjustment are the same as those of the offline adjustment. It is also shown that the GNSS measurements are necessary only at the total station points in the spatial total station traverse. There is no need to add additional merging points of the total station positions because the differences between the results of the online adjustment, including and excluding the merging points, are very small (around 1-2 mm in standard deviation). algorithms; data adjustment; data integration; integrated geodesy; structural monitoring 2020 July 2  
of spatial data has increasingly been involving mobile technologies. In such cases, the activities of system analysts focus on the operation of smartphone or tablet devices, which requires the optimization of algorithmic solutions, thereby ensuring efficient switching between functions. In the case of structural monitoring systems, notifications of potential threats in the form of predefined alarm thresholds are generated based on previously captured and properly integrated data. The user can receive such alerts in an ongoing form, except for simple visualization on screens, also employing signals, text messages, or sound calls. Reliable generation of the warnings mentioned above is required because property and often human lives depend on the speed of response to appearing circumstances. Moreover, such systems often use artificial intelligence and machine learning to initiate and aid appropriate reactions. The topic currently belongs to the mature systems and is reflected in many publications. For example, articles [1; 2; 3; 4] present an overview of existing solutions in this field, explaining the theoretical basis in detail. The cited works also include an in-depth analysis of the available literature, considering new solutions and presenting them as complementary. In the context of spatial data acquisition, photogrammetric techniques--mainly images taken using UAVs (unmanned aerial vehicles) and close-range photogrammetry [5]--are used to a remarkable extent. Data-driven applications are used in mobile solutions, open visions, or complex services, e.g., Smart City concepts [6]. In this context, it is worth mentioning the so-called Internet of Things (IoT), through which multiple sources, especially mobile data, can be acquired and processed online [7; 8]. However, this article focuses on analytical solutions to present a mechanism for effectively integrating spatial data obtained from different sensors, particularly geodetic observables. Such an approach makes it possible to visualize and interpret the survey results with millimeter accuracy.