Exploring Integration of IoT Data in Urban Information Management Systems
Abstract
is becoming more and more prominent. However, the inconsistency of multi-source heterogeneous IoT data in terms of format, semantics and
standards seriously restricts its efficient integration and application. This paper proposes an urban Internet of Things data integration method
based on unified semantic model and multi-source data integration. By building an architecture composed of a data acquisition layer, a fusion
processing layer and an application service layer, this method realizes the standardized processing and semantic association of sensor data of
different protocols, and uses the graph database for unified storage and query. The experiment was verified based on the UCI air quality data
set. The results showed that this method could significantly improve the accuracy and consistency of environmental monitoring data under
multi-sensor fusion, and the system showed low transmission delay and good stability in multi-protocol environments such as ZigBee, WiFi and MQTT. Research shows that the proposed integrated framework can effectively support the real-time monitoring and decision-making
support of urban information management systems, and provide a feasible path for the digital governance of smart cities in the future.
Keywords
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DOI: http://dx.doi.org/10.70711/aitr.v3i4.8204
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