Hearing screening and diagnostic systems, once based on biomedical device technologies constrained by analog limitations, low processing power, and strong dependence on clinical environments, have undergone a profound transformation driven by advances in sensor technologies, embedded system design, high-resolution digital signal processing platforms, and artificial intelligence-based analytical methods. Next-generation otoacoustic emission devices, auditory brainstem response measurement systems, and wideband acoustic immittance analyzers have become faster, more accurate, and more portable through the integration of micro-electro-mechanical system (MEMS) microphones, multifunctional probe architectures, low-noise pre-amplifier circuits, and adaptive digital filtering techniques. With the adoption of remote audiology applications, cloud-based data management infrastructures, and Internet-of-Things-enabled connectivity architectures, hearing screening practices are no longer constrained by physical location, evolving instead into continuously monitorable, data-driven, and remotely controllable structures. Artificial intelligence-enhanced Pass/Refer decision models and signal-to-noise ratio estimation algorithms are standardizing measurement and interpretation processes, while frequency-modulated transmission systems and Roger-based auditory support technologies significantly improve the effectiveness of post-screening rehabilitation. This integrated approach transforms hearing healthcare from a purely measurement-oriented practice into an intelligent, connected, and sustainable auditory health ecosystem.