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Go to Editorial ManagerBattery life is the hard constraint for massive Internet-of-Things (IoT) at 6G scale. Wake-up radios (WuRs)—ultra-low-power auxiliary receivers that “listen” for short wake-up signals while the main transceiver sleeps—offer orders-of-magnitude energy savings, but suffer from false wake-ups, long tail latency under bursty traffic, and sensitivity/coverage limits. This paper proposes an end-to-end AI-optimized WuR stack that combines (i) a TinyML classifier embedded in the WuR path to suppress false triggers and adapt detection thresholds, and (ii) a reinforcement-learning (RL) scheduler at the base station or gateway that co-optimizes wake-up signaling with 3GPP NR DRX/C-DRX timers. The proposed method, tested using a trace-driven simulator calibrated with published WuR power/latency figures, the approach reduces node-average energy by 41–72% versus strong baselines, while meeting 99% latency targets and cutting false wake-ups by >80%.
Autonomous vehicles (AVs) rely on continuous vehicle-to-vehicle (V2V) and vehicle-to-everything (V2E) communication to support shared perception, traffic direction, and decision making. Integrating real-time data, connectivity, and precise navigation will revolutionize urban mobility by facilitating sustainable, secure, and highly efficient transportation options. The rapid evolution of AVs within smart cities necessitates robust and secure data transmission methods to ensure efficient and safe operations. This paper proposes a next-generation communication framework that integrates blockchain with artificial intelligence (AI) to enable secure, decentralized, and adaptive AVs network. Blockchain is employed as a distributed trust layer to ensure data immutability, decentralized identity management, and transparent transaction validation among vehicles and roadside infrastructure. AI techniques are incorporated to support intelligent threat detection, dynamic resource allocation, anomaly identification, and context-aware decision making. The integration between blockchain and AI enhances trust establishment while maintaining system scalability and real-time responsiveness. The proposed architecture introduces a layered design that separates communication, consensus, and intelligence components, allowing efficient integration with edge computing and 5G-enabled vehicular environments. This research contributes a unified conceptual framework for secure and intelligent autonomous vehicle communication, highlighting how blockchain and AI can jointly address critical limitations in next-generation vehicular networks and support the evolution of trustworthy, resilient, and scalable smart mobility ecosystems.