Energy expenditure estimation based on artificial intelligence and microservice architecture

Abstract

Nutritional status plays an important role in not only pregnancy outcomes but also neonatal health. One of efficient techniques to control the nutritional status is to estimate the energy expenditure. There are some approaches for estimating energy expenditure. However, they have limitations including high cost, relative complexity, trained personnel requirements, or locality. This study investigates in a system for data collection and analysis (IoH-Internet of Health) developing based on microservice architecture, and its application for energy expenditure estimation. The proposed system has a good ability to scale and integrate with other systems; the energy expenditure estimation is performed by using artificial intelligence. The experimental results have shown the promising results of the proposed system.