Drug Storage System based on Fuzzy Logic and the Internet of Things

Abstract

Health-related issues are a top priority for anyone in the world, and if there is any issue related to health, then solutions should be found as soon as possible. Medicine is one of the most important causes of recovery, so storing medicines of the highest possible quality is necessary. Storing medicines is very important for the hospital because they are used for hormones, viruses, and ointments, which are of great value to the hospital's sustainability and must always be preserved. This study designed and implemented a system to continuously control and monitor sensitive atmospheric information for drug storage, such as temperature, humidity, and light exposure. The system starts by reading the environment sensors around the drug store by the microcontroller. Then the microcontroller passes the data to the fuzzy logic. Mamdani-type fuzzy control is implemented to control and monitor devices that are used on fuzzy rules. The system has the ability to send an alarm when any of the temperature and humidity-related parameters are higher or lower than normal. The data collected using this system is sent via two methods: the first is the website platform, and the second is GSM notification. Drug storage is designed and implemented using a microcontroller and IoT sensors. During the system analysis phase, the SWOT method was utilized to obtain user perspectives and preferences, which were then incorporated into the system output specifications for the development phase. This approach helped to identify the necessary system requirements. During the implementation phase of the system and to measure the capabilities of the system, the technique of measuring the system usability scale was used, with the contribution of 22 users of the system, and the percentage recorded as general satisfaction with the system was 91%. The new system improves the overall quality of drug storage, reduces the risk of drug deterioration to patients' health, and reduces the incidence of adverse events associated with drug mismanagement.