Abstract
Demographic growth in urban areas means that modern cities face challenges in ensuring a steady supply of water and electricity, smart transport, livable space, better health services, and citizens’ safety. Advances in sensing, communication, and digital technologies promise to mitigate these challenges. Hence, many smart cities have taken a new step in moving away from internal information technology (IT) infrastructure to utility-supplied IT delivered over the Internet. The benefit of this move is to manage the vast amounts of data generated by the various city systems, including water and electricity systems, the waste management system, transportation system, public space management systems, health and education systems, and many more. Furthermore, many smart city applications are time-sensitive and need to quickly analyze data to react promptly to the various events occurring in a city. The new and emerging paradigms of edge and fog computing promise to address big data storage and analysis in the field of smart cities. Here, we review existing service delivery models in smart cities and present our perspective on adopting these two emerging paradigms. We specifically describe the design of a fog-based data pipeline to address the issues of latency and network bandwidth required by time-sensitive smart city applications.
Highlights
Many smart city facilities use advanced Internet of Things (IoT) solutions to implement smart services and applications that use real-time data from various devices such as sensors and meters
Afterwards, we describe some use cases of fog computing in smart cities, mainly intelligent transportation, smart healthcare, and smart grids
Community fog cluster: A community fog cluster is generally designed for exclusive use and exploitation by a specific community of consumers belonging to many organizations that share common concerns
Summary
Many smart city facilities use advanced Internet of Things (IoT) solutions to implement smart services and applications that use real-time data from various devices such as sensors and meters. These initiatives include ways to provide proactive alerts about devices that may fail and prevent threats and unauthorized entry and exit from city facilities using surveillance cameras and electronic identification-enabled security doors These advances are undoubtedly impressive, but managing the massive amounts of data they generate in near real-time is a challenge. Instead of conveying data to cloud servers for processing and storage, sensors and edge devices should transmit their data to edge gateways or servers to be aggregated, processed, or analyzed This operation would allow a reduction in the volume of data to send and store in cloud servers, minimizing costs, reducing latency, and controlling the network bandwidth usage [4].
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