Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/50851
Título: | Anomaly detection in roads with a data mining approach |
Autor(es): | Silva, Nuno Alberto Ribeiro Soares, João Paulo Conceição Shah, Vaibhav Santos, Maribel Yasmina Rodrigues, Helena |
Palavras-chave: | Road anomalies Data mining Data analytics Data Analitics |
Data: | 2017 |
Editora: | Elsevier |
Revista: | Procedia Computer Science |
Citação: | Nuno Silva, João Soares, Vaibhav Shah, Maribel Yasmina Santos, Helena Rodrigues, Anomaly Detection in Roads with a Data Mining Approach, Procedia Computer Science, Volume 121, 2017, Pages 415-422, ISSN 1877-0509 |
Resumo(s): | Road condition has an important role in our daily live. Anomalies in road surface can cause accidents, mechanical failure, stress and discomfort in drivers and passengers. Governments spend millions each year in roads maintenance for maintaining roads in good condition. But extensive maintenance work can lead to traffic jams, causing frustration in road users. In way to avoid problems caused by road anomalies, we propose a system that can detect road anomalies using smartphone sensors. The approach is based in data-mining algorithms to mitigate the problem of hardware diversity. In this work we used scikit-learn, a python module, and Weka, as tools for data-mining. All cleaning data process was made using python language. The final results show that it is possible detect road anomalies using only a smartphone. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/50851 |
DOI: | 10.1016/j.procs.2017.11.056 |
ISSN: | 1877-0509 |
Versão da editora: | https://www.sciencedirect.com/science/article/pii/S1877050917322494 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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cs_centeris_silva.pdf | 619,2 kB | Adobe PDF | Ver/Abrir |