Optimizing Resource Utilization in IoT based Smart Home Automation: A Hybrid Crow Search and Border Collie Optimization Approach

Smart home automation systems are now essential parts of contemporary living, providing convenience, energy efficiency, and improved security. Efficient compute offloading solutions are crucial for achieving optimal performance and resource utilisation in these systems. This research presents a new method for improving the efficiency of resource usage in smart home automation. The method utilises a hybrid algorithm that combines the Crow Search Algorithm (CSA) with the Border Collie Optimisation Algorithm (BCOA). The hybrid method is designed to tackle the difficulties of computing offloading by combining the advantageous aspects of the collective foraging behaviour of crows and the intellect of border collies. We introduce the hybrid algorithm and describe its design, implementation, and assessment through simulation-based experiments. The results indicate that the proposed approach effectively optimises resource utilisation, enhances system efficiency, and improves overall performance in smart home automation scenarios. This research enhances the field of smart home automation by proposing a new optimisation technique specifically designed to meet the specific needs and limitations of these systems.