This chapter explores how the Internet of Medical Things (IoMT), combined with artificial intelligence (AI) and big data, is changing ophthalmology and healthcare delivery. It emphasizes the merging of AI, deep learning (DL), telemedicine, and connected digital systems to improve diagnosis, disease monitoring, and patient access to care. AI algorithms, especially those based on deep learning, can now identify ophthalmic diseases like diabetic retinopathy, glaucoma, and macular degeneration with expert-level accuracy using imaging tools such as fundus photography and optical coherence tomography (OCT). The integration of IoMT allows seamless connectivity among medical devices, imaging systems, and electronic health records (EHRs), enabling real-time communication and data sharing across healthcare networks. Applications such as AI-assisted virtual clinics and cloud-based teleophthalmology platforms demonstrate how connected systems can reduce wait times, improve care efficiency, and expand access to specialists in remote areas. Despite these advances, successful implementation depends on interoperability standards, secure data management, clinical validation, and a trained workforce. When combined with AI-driven analytics, IoMT signifies a major shift toward intelligent, interconnected, and patient-focused ophthalmic care.