IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 15, No 4: August 2026

A holistic energy expenditure tracking framework: fuelling wellness with holistic energy tracking

Prachi Kadam (AI Consultant of Sahyasakha)
Gagandeep Kaur (Mukesh Patel School of Technology Management and Engineering)
Leena Manojkumar Panchal (Symbiosis International (Deemed University))
Smita Nirkhi (Symbiosis International (Deemed University))



Article Info

Publish Date
01 Aug 2026

Abstract

Effective public health management is essential for a country’s social and economic development. A strong public health system reduces the strain on healthcare infrastructure by encouraging preventive measures. With significant lifestyle changes in recent years, monitoring both energy intake (EI) (diet) and energy expenditure (EE) (physical activity (PA)) has become crucial to maintaining public health. Existing methods primarily track exercise-related EE using self-assessment tools or wearable devices, often neglecting occupation-related activities. This results in an underestimation of total EE. To address this limitation, we propose the holistic energy expenditure tracking (HEET) framework, which aims to provide a comprehensive estimate of daily EE by including occupational activities. The framework was applied to data from a dietitian who collected 180 data points from working professionals across three different occupations. Exploratory data analysis revealed a 41% increase in metabolic equivalent of task (MET) values and a 27% rise in calorific values when occupational EE was considered. A categorical scoring system was developed based on the new calorific values, enabling dietitians to offer more personalized dietary recommendations. The study highlights the need for a standardized framework that captures all daily activities, offering a more accurate and holistic approach to public health monitoring and intervention.

Copyrights © 2026






Journal Info

Abbrev

IJAI

Publisher

Subject

Computer Science & IT Engineering

Description

IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like ...