Encrypted fully model-free event-triggered HVAC control

This paper addresses the critical issue of privacy and high computational overhead in cloud-based HVAC control systems for building automation. Cloud computing platforms can infer sensitive information , such as occupancy, from sensor data, making privacy a major concern for users of intelligent buildings . Existing model-based control methods ensure privacy by introducing homomorphic encryption but they rely on approximating building dynamics and are resource-intensive, leading to increasing communication and computation costs. To solve this, we propose an encrypted fully model-free event-triggered control framework that guarantees privacy while minimizing both communication and computational costs without the need for approximating building dynamics. Our approach includes a model-free controller that regulates indoor temperature and CO 2 levels, and an event-triggering mechanism that optimizes communication by only transmitting data when necessary. The numerical results from the simulations using the TRNSYS platform show that our method reduces communication between the system and cloud by 64% and decreases computation time by 75% compared to the latest encrypted HVAC control method. The primary contribution of this work is the novel model-free design that simplifies the control process modeling while significantly reducing resource demands, and provides a scalable and cost-effective solution for cloud-based HVAC control, enhancing both privacy and operational efficiency in smart buildings. • An encrypted fully model-free control method is proposed. • Homomorphic encryption ensures secure cloud computations on sensor data. • Event-triggering unit reduces communication by 64%. • Computational costs were cut by 75% compared to the hybrid model-free control method. • Enhanced privacy without sacrificing control performance.