Abstract
With reference to the MeSmart project, the Municipality of Messina is making a great investments to deploy several types of cameras and digital devices across the city for carrying out different tasks related to mobility management, such as traffic flow monitoring, number plate recognition, video surveillance etc. To this aim, exploiting specific devices for each task increases infrastructure and management costs, reducing flexibility. On the contrary, using general-purpose devices customized to accomplish multiple tasks at the same time can be a more efficient solution. Another important approach that can improve the efficiency of mobility services is moving computation tasks at the Edge of the managed system instead of in remote centralized serves, so reducing delays in event detection and processing and making the system more scalable. In this paper, we investigate the adoption of Edge devices connected to high-resolution cameras to create a general-purpose solution for performing different tasks. In particular, we use the Function as a Service (FaaS) paradigm to easily configure the Edge device and set up new services. The key results of our work is deploying versatile, scalable and adaptable systems able to respond to smart city’s needs, even if such needs change over time. We tested the proposed solution setting up a vehicle counting solution based on OpenCV, and automatically deploying necessary functions into an Edge device. From experimental results, it results that computing performance at the Edge overtakes the performance of a device specifically designed for vehicle counting under certain conditions and thanks to our reconfigurable functions.
Highlights
Smart Cities represent a new way to live the urban environment, involving social and technological aspects
We present a vehicle counting system we developed to be run on a Raspberry Pi mod 4 equipped with a USB webcam with 1920 × 1080 resolution, and we compare the performance of the proposed approach with the performance of a Traficam device
In this paper, starting from the requirements of the Italian project Mesmart, we investigated the use of a single edge device for accomplishing multiple tasks in the domain of video processing instead of buying a specific camera per each task
Summary
Smart Cities represent a new way to live the urban environment, involving social and technological aspects In this context, systems based on IoT (Internet of Things) play an important role to allows citizens to interact with the environment and to benefit of advanced services, such as video surveillance, intelligent traffic lightning, air quality sensing and noise estimation, to obtain intelligent means of transport and autonomous vehicles management [1]. The benefit of decomposing an application into different smaller services is that it improves modularity, making applications more straightforward and more resilient This architectural style simplifies the deployment of microservices within a flexible and dynamic Cloud/Edge environment that meets their needs. With the aim of simplifying the management of distributed microservices among several devices, the function as a service model has been proposed
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