Sensor data fusion for the industrial artificial intelligence of things

The emergence of smart sensors, artificial intelligence, and deep learning technologies yield intelligence things, also known as the AIoT. Sophisticated cooperation these is vital for effective processing industrial sensor data. This paper introduces a new framework addressing different challenges AIoT applications. proposed an intelligent combination multi-agent systems, knowledge graphs learning. Deep architectures are used to create models from sensor-based Multi-agent systems can be simulating collective behaviours sensors using IoT settings. communication among agents realized by integrating graphs. Different optimizations based on constraint satisfaction well evolutionary computation investigated. Experimental analysis undertaken compare methodology presented state-of-the-art technologies. We show through experimentation that our designed achieves good performance compared baseline solutions.