Neural Network-Based Serum Flow Rate Control

Autor: Gokhan Cetin, Sule Senyigit, Emrah Benli
Rok vydání: 2021
Předmět:
Zdroj: 2021 Innovations in Intelligent Systems and Applications Conference (ASYU).
Popis: While intelligent systems continue to take more place in our lives, it is critical that biomedical instruments, which are of vital importance, also benefit from this technology. When a serum is inserted into patients in hospitals, patients or their relatives may change the serum flow rate by interfering with the reel on the serum set, which adjusts the flow rate of the serum. As a result, it can cause undesirable consequences for patients. In order to eliminate such negativity and make the job of health workers easier, it was intended to create a system where serum flow rate can be controlled from the computer. Neural Network is preferred because there are many factors that affect the flow rate of the serum. A model has been created with Neural Network. In this model, the input parameters of patients and the desired condition for the output, i.e the degree of the servo motor that controls the flow rate of the serum, are defined. Thus, the coefficients “weights” and “bias” were obtained with this model. These coefficients were also processed into Arduino and the control of the servo motor was carried out.
Databáze: OpenAIRE