Design of expert system to determine the proper diet using harmony search method

Firmansyah, Esa; Rosmawati, R.; Fuadi, R S; Fauzy, D; Ramdhani, Muhammad Ali

doi:10.1088/1742-6596/1402/7/077006

Cited by 3 publications

(2 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2.2 Related Works KALORI HARIANMU (SISTEM PAKAR DIET) by (Firmansyah, et al 2019), this study aim to design an expert system which addresses individual diet based on calorie activities and body needs. This expert system uses a harmony search algorithm to determine the amount of food with Harris-Benedict formula to calculate the body's calorie needs.…”

Section: Literature Reviewmentioning

confidence: 99%

Electronic Human Nutrition Analyzer for Managing Obesity (EHNAMO)

Adepegba¹,

Adepegba²,

Longe³

et al. 2022

AIMS Research Publication

View full text Add to dashboard Cite

The bad eating habits in the Nigeria society is increasing and the Obesity rate is constantly increasing but to monitor the Nutritional status simply means booking an appointment with a nutritionist with long hours of waiting time to get answers. Another important factor is cost of getting an appointment this could be high to an average Nigerian giving the fact that seeing a nutritionist is not one-time bargain as one would continuously need to book an appointment on the long run. The developed is capable of allowing users to enter personal details such as height, weight, age, gender and other factors to efficiently monitor the user nutritional status. By calculating the B.M.I (Body mass index) the system easily identifies the nutrition status of the user and proceeds to recommend appropriate profile for the user such as gaining weight, maintaining weight and losing weight and also likewise calculating B.M.R (Basal Metabolic rate) of the user the system automatically knows the amount of calories needed to be present in the individual nutritional status based on the users profile. The web application was developed using Php7 and Mysql which can be deployed on to any web server for the application to be accessible to users. This web based nutrition analyzer allows users to generate their own diet/Nutritional Food-time table which can be followed to achieve a healthy Nutritional Status. The study gives room for nutritionist to user interaction in order to help boost user satisfaction, the system has the capabilities of generating reminder, alerts, exercise routines and constantly motivates the user to use the application and improve their nutritional habits. Keywords: Obesity, Body Mass Index (BMI), Basal metabolic rate (BMR), Diet, Nutrition Journal Reference Format: Adepegba, O. A., Adepegba S. A., Longe O. B. & Adesiyan A. P. (2022): Electronic Human Nutrition Analyzer for Managing Obesity (EHNAMO). Journal of Behavioural Informatics, Digital Humanities and Development Research. Vol. 8.No. 1, Pp 15-26. Available online at https://www.isteams.net/behavioralinformaticsjournal dx.doi.org/10.22624/AIMS/BHI/V8N21P2

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Electronic Human Nutrition Analyzer for Managing Obesity (EHNAMO)

Adepegba¹,

Adepegba²,

Longe³

et al. 2022

AIMS Research Publication

View full text Add to dashboard Cite

show abstract

“…One area where expert systems have found a wide variety of uses is the medical field [33]. Within the medical field, expert systems have been used and developed for diet planning [34], diabetes therapy [35], heart disease [36], eye disease [37], skin disease [38], COVID-19 [39] and hypertension [40] diagnosis, lower back pain diagnosis and treatment [33], neck pain diagnosis [33] and many more have also been developed [33] relating to medical diagnosis and treatment. Expert systems have also been used to diagnose diseases in fruits [41], plants [42] and animals [43].…”

Section: Expert System Usesmentioning

confidence: 99%

Implementation of Hardware-Based Expert Systems and Comparison of Their Performance to Software-Based Expert Systems

Ritter

Straub

2021

Machines

View full text Add to dashboard Cite

Expert systems are a form of highly understandable artificial intelligence that allow humans to trace the decision-making processes that are used. While they are typically software implemented and use an iterative algorithm for rule-fact network processing, this is not the only possible implementation approach. This paper implements and evaluates the use of hardware-based expert systems. It shows that they work accurately and can be developed to parallel software implementations. It also compares the processing speed of software and hardware-based expert systems, showing that hardware-based systems typically operate two orders of magnitude faster than the software ones. The potential applications that hardware-based expert systems can be used for and the capabilities that they can provide are discussed.

show abstract