23^rd World Dermatology Congress

Biography

Biography: Alimuddin

Abstract

Premature babies and low birth weight babies are not able to adapt to the environment. The incubator has a role to provide the right environmental conditions for premature babies and low birth weight babies. The condition of the baby such as weight and age are parameters that are always changing, which is what determines the temperature conditions in the right incubator. The development of technology for controlling and monitoring environmental conditions including temperature, humidity, oxygen, is important. When the baby is born, if there are abnormalities or abnormalities, including low baby weight, yellow eye color, and most critically, being born prematurely, it is not yet time to give birth. Many control and monitoring systems are used so far there are conventional and modern ones. The control and monitoring system has so far been isolated and not yet integrated and still uses one control system algorithm ON OFF, PID and Fuzzy Logic. There are several research results by the author using the PID Gain Scheduling control system for temperature and humidity in the baby incubator (1) resulting in a model of temperature and humidity in the incubator that can represent the physical characteristics of the temperature and humidity of the incubator has been designed properly, as evidenced by the data validation with an error value 5%. one temperature model and four humidity models have an error value of 2.202% from 438 samples and 2.944% 1.57%, 1.56%, 1.242% from 1038 samples. Adaptive control using Integral-Adaptive Gain Scheduling on temperature and PID-Adaptive Gain Scheduling for humidity in baby incubators can be well designed as evidenced by simulations using simulink on MATLAB software that the system output is able to reach and follow the constantly changing set point and scheduler variables. and the PID and Fuzzy Logic hybrid control system on temperature and humidity in an infant incubator [2] resulted in the temperature control system of the proposed controller being checked at the set point values ​​of 34 °C and 35 °C from the initial room temperature and humidity of 60% and 70%. The results showed that the proposed Fuzzy-PID temperature control has a faster response to reach the set point than using PID alone. However, the proposed controller faces little difficulty in reaching the set point when interference occurs from the output of the moisture mist actuator and due to fluctuations in the outside temperature of the incubator.