PERFORMANCE COMPARISON OF SPATIAL SEARCH ALGORTIHMS FOR SPECIFIC DATASETS IN SMART CITIES

The concept of smart city has emerged in the digital age. One of the main purposes of smart cities is to provide components that will provide time efficiency. Smart transportation and parking services are included in this concept. The basis of these services is based on real-time spatial search algorithms. We need to use performance spatial search algorithms for real-time spatial searches. Popular spatial search algorithms; k nearest neighbor, rectangle queries, r-tree and kd-tree. In the query made from a point in the spatial plane, the selection of the correct algorithm is important in terms of performance. The purpose of this study; to determine the algorithm that determines the nearest neighbor in a given dataset in the fastest way for the selected center point. The 4 spatial search algorithms written in Python language were compared with the tests and the most suitable algorithm was determined for the data set. The algorithm can be used in the city component model similar to the data set, so efficient time management is provided in the city life where time is valuable.