A Big Data Platform for Smart and Sustainable Cities: Environmental Monitoring Case Studies in Europe

Abstract

One of the most challenging aspects of the actual smart city trend is to keep under control the environmental parameters with the aim of general sustainability. The impact of daily activities of humans in the city is presently very evident. The geographical and social characteristics of the cities may react and facilitate the sustainability as well as may really influence how the city may be more or less resilient to certain pollution production. After investigating the theoretical concept of Smart Sustainable City (SSC), this paper reported the work performed in supporting the aforementioned trend and analysis in three European cities (Florence, Helsinki and Cagliari) that despite having different characteristics for population and density, have some similarities, such as geomorphic aspects. In addition, two of them present a relevant port (Helsinki and Cagliari), two of them have similar urban complexity, such as traffic (Florence and Helsinki). The work presented has exploited Snap4City big data for smart city infrastructure and has been developed in the context of Snap4City, Trafair, and GHOST projects. The results have shown that critical aspects have been identified over time for pollution issues, in particular with PM10 and NOX.

Research trends in the application of big data in smart cities—A literature review

“…One of the most demanding issues in the current trend of smart cities is keeping environmental aspects under control with the ultimate goal of sustainability. Therefore, the concept of smart sustainable cities was introduced (Huovila et al., 2019), and big data technologies have been exploited in smart city infrastructures to support environmental monitoring (Garau et al., 2020). In addition, predictive models can be used to control pollution levels to protect citizens from the damage caused by pollution (Honarvar & Sami, 2019).…”

“…G‐IoT can use data to help monitor pollution levels, resource consumption, and share resources, with better insight enabling citizens and government authorities to make better environmental decisions. The identified articles in this dimension mainly present analytical networks for IoT‐based big data applications (Bibri, 2018; Garau et al., 2020; Navarro et al., 2017).…”

Data Sources and Models for Integrated Mobility and Transport Solutions

“…On the other hand, the activity of finding correct data providers and studying their distribution modalities is time consuming and prone to risks of missing some needed information for the purpose planned. In the last years, national and international public organizations have been trying to design and implement data hubs or dataspaces [ 74 , 75 ] capable of integrating the different data providers by defining interoperability standards to realize unique access points for the distribution of mobility and transport data, as well as data spaces in other domains, which are out of the scope of this paper. In Europe, the first project aimed at the development of a mobility dataspace started in 2019 in a German consortium [ 76 , 77 , 78 ] proposing a decentralized and distributed system with a directory to publish available data sources and services (i.e., a data marketplace) and a vocabulary provider that gives information on standards and APIs (e.g., DATEX-II, NeTEx and SIRI).…”

Sensors on Internet of Things Systems for the Sustainable Development of Smart Cities: A Systematic Literature Review

“…Daepp et al [45] also developed a low-cost IoT system, Eclipse, to monitor Chicago's outdoor air quality and found that the system reliably collected data for more than 90% of the expected hours. Last but not least, Garau et al [46] reported on IoT Environmental Monitoring systems in Florence, Helsinki, and Cagliari.…”