The article discusses the emergence of Spatial Digital Twins (SDTs), which leverage vast amounts of spatio-temporal data produced by mobile apps, IoT devices, and autonomous vehicles. With billions of data points generated daily, advanced big data analytics systems like Hadoop and Spark are being extended to process this data efficiently. The focus on scalable solutions highlights the overlap between spatial data and big data analytics, illustrating the importance of evolving technology to handle complex datasets and support analytical operations in SDTs.
The rise of mobile location-based apps and numerous IoT devices has led to an explosion of spatio-temporal data generation, necessitating advanced analytical systems for management.
Recent research emphasizes the use of spatial extensions to big data analytics platforms like Hadoop and Spark, enabling the management of vast amounts of spatio-temporal data.
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