Bimodal Insulin Delivery System Using Internet of Things and Machine Learning Approach

Abstract

Internet of things (IOT) and Machine Learning (ML) techniques have achieved quite high standards with the availability of high-speed GPU's and wide range of applications in real world. Both of them are shaping the way we live, travel, work and communicate. Medication in India is the core power of the Economy but, it's quite expensive. This paper aims at an attempt to deploy these IOT and ML techniques for Automating Insulin Drug Delivery (AIDD) for comatose patients. The main focus is to replace the existing Insulin Delivery Systems which are costly and limited to only certain hospitals, with a cost friendly and smart system which incorporates IOT and Machine learning with good accuracy and a very affordable price. In this the rotor system is designed and presented which is employed to deliver the required amount of insulin. The rotation of the designed rotor system is controlled by a motor. In order to make the system more flexible, bimodal operation is developed using IOT which enables either manual or automatic mode. To fix the optimal ML technique, the various machine models such as Linear Regression, Decision Tree and Random Forest is employed to predict insulin dose amount that must be given to the patient by examining his/her condition. This method makes it possible to treat a diabetic patient remotely, without the need of a physical person.