Smart home technologies offer promising solutions for managing dietary-related conditions like coronary heart disease, hypertension, and diabetes. However, adoption among older adults remains low due to concerns over functionality, reliability, privacy, and security. This study shifts the focus of human-computer interaction (HCI) research from usability to behavior design as a strategy for trust-building, a critical factor influencing older users’ engagement with health technologies. We introduce SeniorCare, a smart home-based food intake monitoring system tailored for older adults. Guided by behavior design principles, the system aligns timing, ability, and trustworthiness to enhance user acceptance. Additionally, we propose the Time, Ease of Use, and Ability (TEA) Model to assess the impact of interaction time and usability on trust. Using a mixed-methods approach, including surveys and interviews, this study examines key trust factors in smart home adoption. Findings demonstrate how behavior design and the Tiny Habits method can foster sustained engagement, ultimately enhancing the accessibility and acceptance of AI-driven healthcare solutions for older adults.