Towards Enhanced AI-Driven Security in Monitoring Systems with Low-Cost IoT Devices

As the Internet of Things (IoT) continues to expand, the need for robust security measures to protect against an increasing range of threats has grown. However, the computational limitations of low-cost IoT devices, commonly used in monitoring applications, hinder the implementation of advanced security protocols. In this preliminary work, we evaluate the feasibility of deploying complex security methods, such as real-time encryption and intrusion detection, on low-cost devices like the Raspberry Pi 5. By integrating hardware accelerators, such as the Google Coral, we propose optimizations aimed at overcoming these devices’ inherent processing constraints. Initial findings demonstrate the potential for these optimizations to enhance the security capabilities of IoT systems in resource-constrained environments. Further work will explore the scalability and real-world applicability of this approach.