Title | The "Smart Ring" Experience in l'Aquila (Italy): Integrating Smart Mobility Public Services with Air Quality Indexes |
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Publication Type | Presentazione a Congresso |
Year of Publication | 2015 |
Authors | Villani, Maria Gabriella, Cignini F., Ortenzi F., Suriano Domenico, and Prato Mario |
Conference Name | Proceedings of of the 2nd Int. Electron. Conf. Sens. Appl. |
Publisher | Sciforum Electronic Conference Series, %issn=19300395 |
Keywords | Air Quality Index, City 2.0, L'Aquila, low-cost Electrochemical Gas Sensors, Mobility on Demand, Smart Ring, Smartbus, Urban Environment |
Abstract | A collaborative agreement between ENEA and the l'Aquila local government was established in 2010 to support the l'Aquila city centre rebuilding, severely damaged by the April 2009 earthquakes. The collaborative agreement produced the “Smart Ring” project, which, on the bases of a Smart City Paradigm, supported the integration of mobility urban services, environmental monitoring and smart lighting along a 4-5 km circular path, the “Smart Ring”, around the historical centre of l'Aquila. This work presents the activities of the “City Dynamics and Smart Environment” work package of the Smart Ring project. It focuses on the integration of the mobility urban public service “Smartbus”, an experimental on-demand public service electric bus based, with the multiparametric air quality low-cost electrochemical sensors NASUS IV, deployed to sample ambient air gas components (NO2, CO, SO2, H2S). For five days (28-29 August 2014 and 1-3 September 2014), the multiparametric air quality sensor was installed inside the Smartbus, and measured air quality parameters during the Smartbus service. The air quality data for NO2, CO, SO2, H2S , were collected, visualised and statistically analysed also on the base of an Air Quality Index. The results provide an insightful view of the status of the air potentially experienced by the Smartbus users, and indirectly, on the air quality along the Smart Ring track. © 2015 ECSA2, %author_keywords=Air quality; Gas sensors; Measurement uncertainty; Multivariate linear regression; Neural network; Nitrogen dioxide; Ozone |
URL | https://https://sciforum.net/conference/ecsa-2/paper/3229 |
DOI | 10.3390/ecsa-2-E015 |
Citation Key | Villani_ecsa2 |