The architectural concept of a monitoring system based on the neural module of IoT data analytics

Abstract

The object of research is the processes of collecting and analyzing data in intelligent systems, which determine the problem of improving the efficiency of data processing in real-time. The subject of the study is intelligent IoT systems developed with edge computing technologies and with ways for improving the efficiency of IoT systems using neural networks and machine learning. The aim of the work is to develop an architectural concept of software and hardware using an intelligent IoT module for data analytics at the edge of computing. The proposed architectural concept of a human sleep monitoring system through the use of a trained neural network for IoT data analytics makes it possible to overcome the limitation of data processing efficiency and the security of personal information, and the combination of inexpensive hardware and affordable wearable electronics is aimed at reducing the cost of system availability for a wide range of users. Ref. 9, pic. 9.

Keywords

• IoT
• intelligent IoT system
• edge computing
• microclimate control
• neural network
• machine learning