Early symptoms in Alzheimer’s disease (AD) patients are often subtle, and diagnosis typically occurs in the middle to late stages. Currently, there is a lack of effective targeted therapeutic drugs and treatments to halt the disease’s progression, emphasizing the importance of early detection and intervention over treatment. This paper employs Ambient Intelligence (AMI) to monitor patients’ daily behaviors and identify early symptoms in the home environment. This is achieved through the integration of intelligent sensors, interaction design, and artificial intelligence algorithms, leading to the formulation of personalized solutions based on patients’ behaviors. Furthermore, the paper outlines the future research direction for AD, suggesting the incorporation of VR devices to allow users to experience the behaviors, emotions, and feelings of early-stage patients through visual and auditory immersion. This approach aims to provide a deeper understanding and foster empathy among non-patient individuals.