Towards Intelligent Control Architectures: A Systematic Review of Internet of Things Applications in Control Systems

Abstract

The rapid proliferation of the Internet of Things (IoT) has significantly transformed modern control systems by enabling real-time data acquisition, intelligent decision-making, and seamless connectivity across distributed environments. This paper presents a systematic review of IoT-based control systems, covering studies published between 2015 and 2025, with emphasis on architectural foundations, enabling technologies, control strategies, and major application domains. The review paper analyses five key domains, namely industrial automation, smart manufacturing, healthcare, smart homes and buildings, transportation, and energy and smart grids, while examining major control and optimization approaches integrated with IoT, including data-driven, adaptive, intelligent, and distributed control methods. It also identifies four major cross-cutting challenge categories, namely security and privacy, interoperability and standardization, latency and reliability, and energy efficiency and sustainability, which continue to limit large-scale deployment. In addition, the study highlights eight emerging research directions, including edge-fog-cloud co-design, federated learning, TinyML, digital twins, zero-trust security, and safe learning- based control. The novelty of this review lies in its unified perspective that connects IoT architecture, embedded intelligence, control and optimization frameworks, and cross-domain applications within a single analytical structure. By synthesizing existing literature and revealing key research gaps, this work provides a clearer foundation for developing secure, scalable, and resilient next-generation IoT-driven control systems