머신러닝 기반의 IoB 리소스 분석 모델 설계

With the recent development of IoT technology, IoT technology is being used in a cloud environment that can continuously process data in real time through various intelligent devices. In particular, IoT technology has recently attracted attention in the field of IoB using information collected from AI, distributed computing, and simple/complex Internet activities of users. However, measures to improve the accuracy and efficiency of IoB information in various fields using IoB information are currently lacking. In this paper, we propose an analysis model that can effectively analyze machine learning-based IoB resources. The proposed model creates an IoB dataset to allow machine learning to analyze IoB resources and extract specific information when transferring IoB resources to servers in a cloud environment. The proposed model combines and processes IoB resources hierarchically in a blockchain so that IoB resources can be continuously exchanged in a cloud environment. The proposed model configures the network as a mesh network to enable stable interconnections to devices connected to the network by adding IoB resources to the blockchain. Such a network configuration allows IoB distributed access, effectively prevents a single point of failure, and operates flexibly. In addition, the proposed model minimizes bottlenecks in IoB information, delays in IoB processing resources, and network overhead because it performs efficient IoB continuous learning at low cost.