ABSTRACT
Internet of Things (IoT) represents a connected system consisting of different devices and components that interact with each other to serve multiple goals. It has created new avenues for prospective applications in various domains including cloud computing, image processing, smart transportation, agriculture, smart healthcare, and other computationally expensive tasks. IoT is becoming popular in healthcare domain because it improves the automation of many repetitive tasks performed by human agents. One example of such tasks is patient check-in to hospitals and clinics, traditionally using paper-based data entry forms at the front desk. IoT can enable a seamless and more rapid check-in without requiring active front desk personnel and patient interaction, or delays from queues. For example, Radio Frequency Identification (RFID) trackers can be used to identify and register patients at the hospital or clinic upon arrival. Moreover, recent trends show that medical image processing is an effective method to diagnose patients with diseases and inform management decisions. Deep learning (DL) technology is contributing to automated image processing applications and clinical decision support technology. There are multiple specific applications in the ophthalmology domain (the branch of medicine that addresses diagnosis and treatment of eye diseases). In this chapter, we present a framework to demonstrate the benefits that we can obtain from using DL and IoT in the ophthalmology domain. We particularly emphasize the infrastructure that can be built around different geographical locations to enable the people to benefit from eye care in distributed locations.
