A New Architecture for the Internet of Things (IoT) to Analyze Pattern Recognition using Big Data

The Internet of Things is a new paradigm of verbal exchange. The Internet extends from the digital world to interact and interact with things in the international physical world. The Internet of Things contains a large variety of heterogeneous interconnected devices, which generate large volume statistics. The ultimate challenge for the Internet of Things is to purchase and process this large volume of information. This study addresses this issue by quoting patterns in the lower layers of the IoT reference model stack and reducing processing in the top layers. The study analyses the IoT reference version and middleware architectures for software expansion in this context. The new framework implementation extends Link-Smart by introducing a popular manager model that includes algorithms for parameter estimation, outlier detection, and aggregation of raw records from IoT sources. The new module will be embedded in the Big Data Hadoop platform and the Mahout algorithm implementation. These panels highlight the interlayer connectivity built into the new IoT fabric. Experiments that can complete in these studies will use the actual Smart Santander Framework database to validate the new IoT architecture with displays of pattern popularity and verbal exchange of the layer.