IoT based Vaccine Carrier Monitoring and Self-Learning Algorithm to Optimize Power Consumption in Developing Countries

Abstract

Vaccines are a very effective way of treating preventable diseases in developing countries where it is difficult to supply medical devices and medicines. However, despite the efficiency and benefits of these vaccines, factors such as lack of power supply, geographical ruggedness, and insufficient infrastructure have prevented the spread of vaccine coverage in developing countries. In this paper, based on the Internet of Thing (IoT) monitoring database constructed with a smart phone and the data obtained from sensors in vaccine carrier, it was possible to localize and optimize the vaccine carrier to be used in developing countries by using learning algorithms. The goal was to maximize the use time of the vaccine carrier by learning and predicting optimum power usage that maintaining the optimal vaccine storage temperature of 2℃to 8℃ in a low power supported environment.