Remote monitoring and control (RMC) operations, built upon IoT and IIoT systems, enable real-time supervision and actuation across smart environments such as industrial facilities and other remote engineering applications. These systems leverage interconnected devices and advanced data analytics to enhance operational efficiency, safety, and decision-making processes. However, their reliance on light-weight communication protocols with limited built-in security features, such as MQTT, exposes them to cyberattacks that can compromise reliability and safety. This paper investigates the operational impact of such attacks on an IoT/IIoT-based RMC system and proposes a hybrid Edge–Fog deployment of machine learning (ML)-based intrusion detection systems (IDS) to strengthen resilience and ensure continuous operation.