The Wise Eye Elderly Monitoring System, a comprehensive solution for the monitoring and care of elderly people in Sri Lanka, was developed and put into use as part of this study. This system includes monitoring devices and mobile application to reduce the burden on caregivers. The system uses machine learning techniques to enable automatic system activation and deactivation through image classification, assuring user-friendliness and individualized monitoring for each senior. The device also has an automatic accident detection module that uses machine learning techniques to find accidents in real time and identify them, alerting carers who are away from home right immediately by mobile app. Additionally, the system incorporates voice and sound recognition algorithms to improve communication and enable voice-based commands. This functionality will enhance the system’s ability to seamlessly identify and classify an incident of emergency based on the voice inputs received. At the very least, the Wise Eye system uses behavioral pattern analysis and machine learning to forecast how active an older person will be, providing details on their daily routines and probable behavioral aberrations. A dataset of real-world scenarios is used to evaluate the system, showing how well it can recognize the elderly, detect accidents, hear spoken commands, and gauge activity levels. The suggested Wise Eye Older Monitoring System offers a clever and thorough solution that increases the older population's safety and well-being while simultaneously lightening the load on caregivers and raising the standard of care delivered.