Secure and Low-Power Embedded System Architecture for IoT-Enabled Smart Infrastructure Applications

Abstract

The development of the Internet of things (IoT) technologies has fundamentally transformed the contemporary systems of smart infrastructure, such as the smart cities, smart transportation, smart energy, and smart automation in industry. Embedded systems are notably important in these applications in the real-time data acquisition and processing as well as communication. Nonetheless, the massive scale implementation of these systems presents immense challenges especially with regard to energy efficiency, security as well as scalability, which is because of the resource limited character of embedded devices. The present paper outlines a low-power and safe embedded system layout specifically aimed at lessening the use of IoT-powered internet-based smart infrastructure. To strike the best balance between performance and resources usage, the proposed architecture incorporates energy-saving hardware, lightweight cryptography algorithms, and the proposal to adapt power management. The multi-layer design methodology that involves sensing, edge processing and integration with the cloud is used to increase system performance and minimal communication overhead. The lightweight encryption constructions and secure authentication schemes are used to guarantee the integrity of data, confidentiality, and vulnerability to major cyber-attacks, with a low computational cost. Along with these there is also the deployment of dynamic power optimization such as sleep scheduling and scaling based on workloads which helps to increase the life time of the devices. As experimentally shown, the prototype system results in a substantial power use reduction, lesser latency, and security performance in comparison to the conventional IoT embedded architectures. The results show that the framework suggested is useful in overcoming severe constraints inherent in current systems and can be rolled out in a scalable manner in different smart infrastructure settings. Therefore, the present study will help in the construction of stable, safe, and non-energy-hogging embedded solutions in next-generation IoT features.