We present here an IoT-based platform that provides an integrated solution for real-time monitoring and management of educational buildings at a national scale. The proposed system follows the Fog Computing paradigm so that sensor data processing takes place at the edge devices of the network. In this way, the system significantly reduces the network traffic across the network core layers. The architecture and implementation of the system are presented in details in relation to existing use-case scenaria. The performance of the prototype architecture is evaluated in a real-world environment using a range of edge devices available in a pilot deployment spanning across 18 school buildings. The evaluation indicates that existing resources are sufficient to accommodate traffic that can increase up to 5 times higher from the existing one even in sites where low-end devices (e.g., such as Raspberry Pi) are available. The results provide evidence that Fog Computing can address the ever-increasing amount of data that is inherent in an IoT world by effective communication among all elements of the architecture.
2018, 2018 IEEE International Conference on Communications (ICC), Pages 1-6
A fog computing-oriented, highly scalable iot framework for monitoring public educational buildings (04b Atto di convegno in volume)
Akrivopoulos Orestis, Zhu Na, Amaxilatis Dimitrios, Tselios Christos, Anagnostopoulos Aris, Chatzigiannakis Ioannis
Gruppo di ricerca: Algorithms and Data Science