Spatial Digital Twins (SDTs) integrate complex spatial and geolocation data from various sources like IoT sensors and drones, which elevates their complexity compared to traditional Digital Twins. This paper highlights four key building blocks crucial for developing SDTs, including data acquisition and processing, data modeling and management, Big Data analytics, and middleware systems. The study discusses both modern technologies like AI and Blockchain that bolster SDT functionality and the challenges faced in multi-modal data acquisition and security concerns, outlining future work directions to advance the field.
To accurately represent a large physical environment, Spatial Digital Twins (SDTs) integrate diverse spatial and geolocation data through various technologies such as IoT sensors and drones.
The complexity of SDTs surpasses traditional Digital Twins, necessitating multi-faceted approaches for data acquisition and processing, which drive their efficacy in real-world applications.
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