Intelligent Medication Management System: Enhancing Patient-Centric Care with Machine Learning and IoT Integration

Machine learning (ML) and Internet of Things (IoT) technologies have revolutionized the healthcare industry, particularly in the field of medication administration. The system leverages machine learning algorithms for personalized medical scheduling and Internet of Things (IoT) connectivity for remote monitoring and intervention. Through continuous monitoring and analysis of patient-specific parameters, such as vital signs, medication history, and lifestyle factors, the system dynamically adjusts medication schedules and dosages to optimize therapeutic efficacy while minimizing adverse effects. Key components include a medication dispenser equipped with sensors for inventory tracking and patient interaction detection, a Raspberry Pi microcontroller for data processing, and cloud-based machine learning models for personalized scheduling. Machine learning models are trained on patient-specific data to generate personalized medication schedules considering dosage requirements, timing preferences, and potential interactions. Additionally, the integration of IoT-enabled smart sensors and connectivity allows for smooth communication between patients, healthcare professionals, and medicine dispensers, permitting prompt interventions, prescription reminders, and remote monitoring. Integrated with IoT devices, such as Raspberry Pi-based sensors and actuators, the system enables seamless communication between patients, caregivers, and healthcare providers, facilitating remote monitoring, medication adherence reminders, and timely interventions. Overall, ML and IoT-driven medication dispensing systems offer promising avenues for enhancing medication adherence, reducing errors, and improving patient outcomes in healthcare delivery.