An enhancement to the FLC-based baby incubator system using genetic algorithm

Abstract

This research problem focuses on treating premature babies due to hypothermia so that the baby must be put in an incubator for several days. Conventional intensive care method in premature babies, namely skin-to-skin care method between mother and child. Meanwhile, the latest technological developments, the method is already based on electrical-Internet of Things (IoT) engineering. This research proposes the design of an IoT-based prototype known as a smart incubator. This prototype has been equipped with a real-time monitoring system and system settings using the mamdani fuzzy inference system control method and combined using the Genetic Algorithm (GA) method. The results showed that the ideal temperature range in the smart incubator was 33° C with an accuracy of 99.97% and was in accordance with the fuzzy membership degree in the range of 29° C ≤x≤ 37° C. Furthermore, the ideal relative humidity range in the smart incubator was 60% with an accuracy of 98.60% and was in accordance with the fuzzy membership degree in the range of 59 ≤x≤ 65. Then, the noise range in the smart incubator is 37.9dB to 56.8dB with an accuracy of 96.44% and has been appropriate at the fuzzy membership degree. At a maximum distance of 50cm, it takes 8 seconds for the prototype to detect movement as a safety measure.