Exploring the Healthcare Internet of Things (H-IoT), which has a broad range of applications for the health monitoring of patients, has gathered a rapidly increasing amount of attention as a result of the fast improvement of medical sensors in recent years. This project focuses on using advanced technology, specifically the Healthcare Internet of Things (H-IoT), to address the growing concern of diabetes. With the rise in diabetes cases, the need for effective health monitoring is crucial, especially given the current emphasis on healthcare due to the COVID-19 pandemic. The proposed solution is a secure cloud-based platform that remotely monitors and predicts diabetes. The system employs medical sensors to collect patient data, minimizing communication overhead for quick access to information in a cloud environment. To analyze this data effectively, a popular machine learning algorithm called Random Forest is used to predict diabetes in patients. This innovative cloud-based system enhances communication between patients, doctors, and hospital administration. The project was tested using the PIMA Indian Diabetes sample collection, achieving an impressive prediction accuracy of 94.5%. Future improvements could involve combining different machine learning approaches to enhance accuracy further.