Fog computing-enabled smart seating systems: optimizing latency and network bandwidth efficiency in classrooms - Evans Obu; Michael Asante; Eric Opoku Osei (Advances in Computing and Engineering)
In modern educational settings, overcrowded classrooms challenge student engagement and learning efficiency. To address these issues, we propose a novel smart seating system powered by Fog Computing that leverages Wireless Sensor Networks (WSN), Internet of Things (IoT), Fog Computing (FC) and Cloud Computing (CC) technologies. Our work introduces the first fog computing-driven smart seating system for classroom settings. It demonstrates significant improvements in latency (3.29 ms in Fog-based vs. 108.69 ms in cloud-based systems), while maintaining comparable network efficiency. Our findings highlight fog computing’s potential to transform real-time classroom management. Using iFogSim, we conducted a comparative study between traditional cloud-centric architectures and our fog-based system across various classroom scenarios. Results demonstrate that the fog-based architecture delivers superior real-time responsiveness, making it particularly suitable for dynamic educational environments. This research provides both technical insights into performance improvements and practical implementation guidelines for educational institutions seeking to optimize classroom management systems.   Received on, 06 May 2025 Accepted on, 03 June 2025 Published on, 19 June 2025