In the contemporary context, a growing population of elderly individuals, often living alone with chronic illnesses, necessitates effective health monitoringHealth monitoring without the inconvenience of wearable sensors. This paper proposes a novel solution leveraging ubiquitous smart devices like smartphones and smartwatches. These devices, equipped with a variety of built-in sensors, including accelerometersAccelerometer, gyroscopesGyroscope, and more, serve as unobtrusive tools to collect data on users’ activities. The collected information, encompassing heart rate, movement patterns, and environmental factors, is wirelessly transmitted to a central server. This real-time monitoring system aids caregivers and healthcare professionals in comprehensively understanding the daily activities and health status of the elderly, facilitating early problem detection and appropriate intervention. Furthermore, the paper critically examines existing literature, highlighting a gap in combining body vital monitoring with human activity recognitionHuman Activity Recognition (HAR). Most prior studies focused on a limited set of activities and did not consider the transitions between two consecutive activities, e.g., sit-transition-stand, stand-transition-sit, sit-transition-laying, etc. The integration of sensors, such as accelerometersAccelerometer, gyroscopesGyroscope, and magnetometers, for both activity monitoring and body vital parameter tracking, is found to be lacking in current research. In response, our project proposes a sensor fusionSensor fusion approach, incorporating data from smartphones, smartwatches, oximeters, and blood pressure machinesBlood pressure machine. This comprehensive strategy evaluates health parametersHealth parameters, diverse daily activities, and employs advanced algorithms to predict the individual’s fitness level, categorizing them for tailored healthcare management. This innovative combination of sensor fusionSensor fusion and diverse activity monitoring offers a promising avenue for improving elderly care, disease predictionDisease prediction, and overall well-being.