Hypertension is a significant health concern affecting more than a billion adults worldwide. Early detection is crucial, highlighting the importance of frequent and regular blood pressure monitoring. Conventional cuff-based blood pressure meters can be uncomfortable and cause skin issues due to repetitive cuff inflation and deflation. To address these challenges, previous works have developed cuffless blood pressure monitors based on electrocardiogram (ECG) and photoplethysmography (PPG) sensors and the pulse transit time technique. However, these devices have shown limitations in accurately measuring blood pressure in individuals with hypertension and lack integration with the Internet of Things (IoT). This study aims to enhance the accuracy of cuffless blood pressure monitoring for individuals with hypertension through clinical data collection and integration with mobile and web-based applications, creating a healthcare system for self and remote monitoring, empowering individuals to manage their blood pressure more effectively. To enhance the device’s accuracy for hypertensive individuals, clinical data collection was conducted involving 24 subjects, of which 7 were hypertension patients. The device underwent a calibration process by updating the blood pressure estimation equation using a linear regression technique with the collected data. For clinical validation, 30 subjects, including 5 hypertension patients, were recruited to test the device's performance. The results of this study demonstrate significant improvements, with the device achieving an accuracy of 95.49% for systolic blood pressure and 88.89% for diastolic blood pressure measurements in hypertensive individuals, and 91.91% for systolic blood pressure and 90.64% for diastolic blood pressure in overall measurements.