A smart fog-to-cloud system in airport: challenges and lessons learnt

被引:3
|
作者
Salis, Antonio [1 ]
Jensen, Jens [2 ]
机构
[1] Engn Sardegna Srl, Telco & Media Div, Cagliari, Italy
[2] UK Res & Innovat, STFC RAL, Didcot OX11 0QX, Oxon, England
来源
2020 21ST IEEE INTERNATIONAL CONFERENCE ON MOBILE DATA MANAGEMENT (MDM 2020) | 2020年
基金
欧盟地平线“2020”;
关键词
Cloud computing; fog computing; fog-to-cloud; distributed systems; IoT; machine learning; proximity marketing;
D O I
10.1109/MDM48529.2020.00078
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Airports are one relevant environment in the smart cities implementation. Recent progresses in IoT have made it possible to develop advanced real-time services and assistance tools for travelers, making use of fog computing as an architectural model that places itself between the Cloud and the IoT, in the Cloud-to-Things Continuum, fulfilling requirements for strict real-time responses. The main tool exploits the concept of proximity marketing and covers the essential experience through the airport onto the flight, but also allows travelers to spend their waiting time by discovering the facilities of the airport, supported by a recommendation system using machine learning. The system provides also the airport planners an aggregated and anonymized view, like heat maps, of travelers behavior that highlight bottlenecks in the infrastructure, or highlight situations that require intervention, such as emergencies. The app in based on Android and makes use of the fog-to-cloud platform developed by the Horizon2020-funded mF2C project, giving evidence that the adoption of the fog-to-cloud approach brings significant benefits in terms of performance and optimization of resource usage, giving an objective evidence of the impact of the mF2C framework.
引用
收藏
页码:359 / 364
页数:6
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