EA-SARSA-Based Recommendation Framework in SIoT for Smart Meeting Scheduling Using Smart Assistance

In a smart workplace, the integration of intelligent assistance systems for meeting scheduling presents significant benefits. However, the reliance on specific commands often hampers user experience. To address this challenge, we introduce the Exponential Adaptation-based State-Action-Reward-State-Action (EA-SARSA) system. This sophisticated solution accommodates both text and voice inputs, enhancing user interaction. Furthermore, to ensure robust data security, inputs are encrypted using the Sieve of Atkin Lenstra-based Elliptic Curve Cryptography (SAL- ECC) technique. Following input processing and encryption, the system dynamically analyzes schedules by cross-referencing encrypted data with personalized database records. This enables seamless identification of available time slots or notification of scheduling conflicts. The system then optimizes schedules on a daily basis for enhanced efficiency. During meeting execution, decrypted schedule details are retrieved and leveraged to determine the optimal travel route using smart devices in the Internet of Things (SIoT) environment. Empirical validation underscores the efficacy and productivity gains afforded by the EA-SARSA system, making it a compelling solution for modern workplace productivity enhancement.