Despite the great need for assistive technology among vulnerable groups (e.g., the elderly, children, and the disabled) in daily tasks, research into advanced AI-driven assistive solutions still remains sparse. Traditional multi-agent interaction tasks often require machines to simply help without nuanced consideration of human feelings (e.g., self-esteem, sense of control, opportunity for practice and learning, sense of self-improvement, etc.), while in real life there are always distinct types of human users with different capabilities, goals, etc. Addressing this mismatch, we define a pivotal and novel challenge ``Smart Help'', i.e., providing both proactive and adaptive support to human agents with diverse disabilities and dynamic goals in different tasks and environments. Leveraging AI2-THOR, an interactive 3D environment tailored for real-world home simulations, we introduce an innovative opponent modeling module, focusing on a nuanced understanding of the main agent's capabilities and goals, and optimize the assisting agent's helping policy. Rigorous experiments validate the efficacy of our model components and show the superiority of our holistic approach against established baselines. Our findings illustrate the potential of AI-imbued assistive robots for enhancing the well-being of vulnerable groups. Our environment, dataset, and codes will be released upon acceptance.