Randomized trial evaluates algorithm effectiveness in geo-data processing, suggesting enhancements in analytics for various applications.
Geo-data is a specialized type of data that requires specific rules and algorithms for processing to yield reliable results. Efficient software solutions for geo-data processing require a structured and optimized data pipeline to ensure reliable data handling and computational performance. In the paper, an algorithm for effective geo-data processing is proposed. The algorithm represents the data processing workflow as a hierarchical structure comprising basic (primary), multisensor, trajectory, storage, and visualization levels. Basic data processing considers sensor level, which deals with data transformation and accuracy evaluation. Multisensor provides data fusion of the same parameters but measured from different sensors. Trajectory data processing considers data analysis, which provides calculation of secondary parameters like angles, velocities, accelerations, and timestemps. The relative location algorithm used in TopoJSON data format is considered an efficient trajectory coding for data storage based on minimization of required space. Proposed approach is unified and could be useful for various applications. Developed algorithm has been used in specific software for airplane trajectory data processing. Keywords Data analytics, sustainability performance, intelligent transport system, collaborative decision-makingThis is an archival copy of the original publication in CEUR Workshop Proceedings, Vol. 4155 (in-person Event, Kyiv, Ukraine, January 26, 2026), pp. 117-127. Available online at https://ceur-ws.org/Vol-3422/Paper13.pdf. Published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).
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Ostroumov et al. (2026) studied this question.
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