Paper Title
Design and Development of an Automated Hand Sanitizer Spraying Machine with Compliance Verification Using IoT

Abstract
This paper presents the design and development of an automated hand sanitizer spraying machine with compliance verification. The system utilizes a pump to propel the sanitizer through a tubing system equipped with four nozzles for effective spraying. The operation of the machine involves multiple stages, starting with the detection of a hand using an ultrasonic sensor. Subsequently, a facial recognition software, powered by a Raspberry Pi board, identifies the user through a camera positioned atop the machine. Upon successful recognition, the machine initiates the spraying of sanitizer onto the user's hand. To ensure accountability and record-keeping, the machine transmits data regarding user identity and usage time to a server via a Wi-Fi module, where it is stored for future reference. The implementation of this automated hand sanitizer spraying machine offers significant benefits in the healthcare industry. In various areas within hospitals, such as mortuaries, infirmaries, patient rooms, operation rooms, ICUs, and PICUs, maintaining proper hand hygiene is critical to prevent the spread of infections. This system ensures that healthcare workers, patients, and visitors comply with hand sanitization protocols by providing a seamless and efficient sanitization process. By incorporating facial recognition technology, the machine also contributes to the overall security and identification processes within healthcare facilities. Key features of this project include its automated operation, integration of ultrasonic and facial recognition sensors, efficient sanitizer distribution through multiple nozzles, and real-time data transmission and storage. These features combine to create a reliable and user-friendly system that enhances hygiene practices and reduces the risk of infections in healthcare settings. Keywords - Automated hand sanitizer spraying machine, compliance verification, ultrasonic sensor, facial recognition software, Raspberry Pi board, hand hygiene, healthcare industry, infection control, sanitization process, data transmission, real-time monitoring.