Energy-Efficient Signal Processing Architectures for IoT Networks Design

The proliferation of Internet of Things (IoT) devices in diverse applications, ranging from smart homes to industrial automation, has significantly increased the demand for energy-efficient signal processing architectures. Given the constrained power resources and real-time requirements of IoT networks, the development of optimized signal processing frameworks is crucial to ensure seamless operation without compromising performance. This paper presents a comprehensive study on energy-efficient signal processing architectures for IoT networks, focusing on low-power design techniques and optimization strategies for various signal processing modules. To validate the proposed approaches, a series of simulations and hardware-based experiments are conducted using benchmark IoT applications, including environmental monitoring and wearable health devices. Our results demonstrate a significant reduction in energy consumption-up to 40% compared to conventional architectures-without compromising data accuracy or system reliability. The proposed solutions also show promise in extending the battery life of IoT devices, thereby supporting sustainable and long-term deployments in remote or inaccessible environments. In conclusion, this paper presents a detailed exploration of energy-efficient signal processing architectures tailored for IoT networks.