Methodological Proposal for the Analysis of Urban Mobility Using Wi-Fi Data and Artificial Intelligence Techniques: The Case of Palma
Knowing and modeling mobility in smart city spaces is important for both planning and managing city resources. The optimization of public resources and the improvement of their management are some of the main concerns in the development of sustainable urban development policies. This study proposes...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
|
| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/12/3/504 |
| _version_ | 1797624852286275584 |
|---|---|
| author | Pau Salas Vicente Ramos Maurici Ruiz-Pérez Bartomeu Alorda-Ladaria |
| author_facet | Pau Salas Vicente Ramos Maurici Ruiz-Pérez Bartomeu Alorda-Ladaria |
| author_sort | Pau Salas |
| collection | DOAJ |
| description | Knowing and modeling mobility in smart city spaces is important for both planning and managing city resources. The optimization of public resources and the improvement of their management are some of the main concerns in the development of sustainable urban development policies. This study proposes the application of several artificial intelligence methodologies to support mobility planning based on data provided by public Wi-Fi infrastructures in the city. Considering that Wi-Fi networks provide high-frequency data about the devices under their coverage radius, three classification techniques are proposed: by frequency of occurrence of the devices, by estimation of the mode of transport, and by estimation of the most common travel routes. As a case study, the city of Palma (Mallorca, Spain), an international tourist destination where mobility is of singular importance, is selected. This study shows the results obtained from a Wi-Fi network with wide coverage that is integrated into the urban space. It provides novel and updatable information on the mobility model of the city by taking advantage of public high-frequency monitoring resources. |
| first_indexed | 2024-03-11T09:48:33Z |
| format | Article |
| id | doaj.art-e14c6771d88c483ba62d4c0a7c80318e |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T09:48:33Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-e14c6771d88c483ba62d4c0a7c80318e2023-11-16T16:27:22ZengMDPI AGElectronics2079-92922023-01-0112350410.3390/electronics12030504Methodological Proposal for the Analysis of Urban Mobility Using Wi-Fi Data and Artificial Intelligence Techniques: The Case of PalmaPau Salas0Vicente Ramos1Maurici Ruiz-Pérez2Bartomeu Alorda-Ladaria3SmartDestination Research Group, Industrial Engineering and Construction Department, University of the Balearic Islands, 07122 Palma de Mallorca, SpainSmartDestination Research Group, Applied Economics Department, University of the Balearic Islands, 07122 Palma de Mallorca, SpainSmartDestination Research Group, Geography Department, University of the Balearic Islands, 07122 Palma de Mallorca, SpainSmartDestination Research Group, Industrial Engineering and Construction Department, University of the Balearic Islands, 07122 Palma de Mallorca, SpainKnowing and modeling mobility in smart city spaces is important for both planning and managing city resources. The optimization of public resources and the improvement of their management are some of the main concerns in the development of sustainable urban development policies. This study proposes the application of several artificial intelligence methodologies to support mobility planning based on data provided by public Wi-Fi infrastructures in the city. Considering that Wi-Fi networks provide high-frequency data about the devices under their coverage radius, three classification techniques are proposed: by frequency of occurrence of the devices, by estimation of the mode of transport, and by estimation of the most common travel routes. As a case study, the city of Palma (Mallorca, Spain), an international tourist destination where mobility is of singular importance, is selected. This study shows the results obtained from a Wi-Fi network with wide coverage that is integrated into the urban space. It provides novel and updatable information on the mobility model of the city by taking advantage of public high-frequency monitoring resources.https://www.mdpi.com/2079-9292/12/3/504artificial intelligencereal-time urban monitoringWi-Fi network datatravel routes estimationurban modal mobility estimation |
| spellingShingle | Pau Salas Vicente Ramos Maurici Ruiz-Pérez Bartomeu Alorda-Ladaria Methodological Proposal for the Analysis of Urban Mobility Using Wi-Fi Data and Artificial Intelligence Techniques: The Case of Palma Electronics artificial intelligence real-time urban monitoring Wi-Fi network data travel routes estimation urban modal mobility estimation |
| title | Methodological Proposal for the Analysis of Urban Mobility Using Wi-Fi Data and Artificial Intelligence Techniques: The Case of Palma |
| title_full | Methodological Proposal for the Analysis of Urban Mobility Using Wi-Fi Data and Artificial Intelligence Techniques: The Case of Palma |
| title_fullStr | Methodological Proposal for the Analysis of Urban Mobility Using Wi-Fi Data and Artificial Intelligence Techniques: The Case of Palma |
| title_full_unstemmed | Methodological Proposal for the Analysis of Urban Mobility Using Wi-Fi Data and Artificial Intelligence Techniques: The Case of Palma |
| title_short | Methodological Proposal for the Analysis of Urban Mobility Using Wi-Fi Data and Artificial Intelligence Techniques: The Case of Palma |
| title_sort | methodological proposal for the analysis of urban mobility using wi fi data and artificial intelligence techniques the case of palma |
| topic | artificial intelligence real-time urban monitoring Wi-Fi network data travel routes estimation urban modal mobility estimation |
| url | https://www.mdpi.com/2079-9292/12/3/504 |
| work_keys_str_mv | AT pausalas methodologicalproposalfortheanalysisofurbanmobilityusingwifidataandartificialintelligencetechniquesthecaseofpalma AT vicenteramos methodologicalproposalfortheanalysisofurbanmobilityusingwifidataandartificialintelligencetechniquesthecaseofpalma AT mauriciruizperez methodologicalproposalfortheanalysisofurbanmobilityusingwifidataandartificialintelligencetechniquesthecaseofpalma AT bartomeualordaladaria methodologicalproposalfortheanalysisofurbanmobilityusingwifidataandartificialintelligencetechniquesthecaseofpalma |