Semantic IoT Application Placement for Edge Data Processing

The patent applies local quality by enabling different IoT devices to perform data processing locally based on their semantic models and capabilities. Instead of uniformly uploading all data to the cloud, each device processes and filters data according to its local semantic understanding, transmitting only necessary processed results to the cloud. This resolves the contradiction by maintaining data completeness at the system level while reducing network bandwidth consumption at the transmission level.

The patent segments the data processing function between edge devices and the cloud. IoT devices with semantic models perform preliminary data processing, filtering, and analysis locally, while the cloud receives only the essential processed data. This segmentation allows complete data processing functionality while reducing the volume of data transmitted over the network, thus resolving the bandwidth consumption issue.

The patent implements dynamic application installation where IoT devices can dynamically acquire, install, and update semantic model applications based on their specific needs and capabilities. The system allows devices to selectively install only the applications relevant to their function and data characteristics, rather than pre-installing all possible applications. This dynamic approach enhances data processing capability while controlling device complexity through selective installation.

The patent enables IoT devices to autonomously determine their own data processing needs and selectively install appropriate semantic model applications without requiring manual configuration or installation on every device. Devices self-assess their capabilities and requirements, then automatically acquire and install only the necessary applications, thereby improving overall system processing capability while minimizing individual device complexity and installation overhead.