Edge Intelligence Enabled Secured Digital Transformation in Internet of Autonomous Vehicles
Shagun Singh Dasawat, Sachin Sharma · 2024
As the Internet of Things (IoT) scene advances, autonomous vehicles (AVs) are rising as a significant application space with transformative potential. In any case, the integration of AVs into existing advanced biological systems postures special challenges, especially with respect to information security, security, and real-time decision-making. This paper presents a comprehensive system for leveraging edge insights to address these challenges and encourage the secure digital transformation of AV networks. Our system consolidates progressed edge computing capabilities to empower real-time handling and examination of sensor information created by AVs, minimizing idleness and improving decision-making productivity. Moreover, we propose novel security instruments custom fitted to the particular prerequisites of AV environments, counting confirmation, encryption, and irregularity location conventions. Through an arrangement of recreations and tests, we illustrate the adequacy of our approach in defending AV systems against different cyber threats whereas optimizing execution and asset utilization. Moreover, we talk about potential applications and suggestions of our system in progressing the broader field of independent frameworks and IoT advances.