The World Health Organization’s data indicates a consistent increase in the number of people 60 years of age and over worldwide. According to projections, the number of older individuals worldwide will rise from 1.4 billion in 2030 to 2.1 billion in 2050. Changes in perception and cognition brought on by ageing may affect an aged person’s capacity to identify and convey emotions through facial expressions. There is a dearth of research on the identification of emotions in older persons, dementia or not. As a result, there aren’t many databases available to help with research and experimentation in this field. Older adult’s communication skills may be hampered by their incapacity to communicate or identify their emotions, which could endanger their safety. Therefore, the aim for this research was to develop an application for recognizing emotions in elderly individuals based on facial expressions. To realize the objective, there are three main stages to achieve the objectives including, data collection, facial expression recognition algorithm and decision system. Very few of older people presented in common facial expression for emotion recognition datasets. Thus, in this work, facial expression dataset will be collected using high-definition camera for capturing their faces. The camera will be installed in a room where the monitoring system will monitor their emotions in 24 h. Then, the image is input to the emotion recognition algorithm to recognize the emotion for the day. Finally, if the changes of emotion happen in certain frequent of time, the system will recognize there is an issue with mental health. The subsequent stages involve evaluation and testing the model application in real-time implementation. The expected outcome of this research has the potential to markedly improve the quality of life for seniors living alone. Furthermore, it is expected to provide valuable support to caregivers and healthcare professionals through detailed behavior analyses for the development of personalized care plans.