Publicação
AI on the management of existing bridges
| Resumo: | The present paper presents a brief discussion on the current practice regarding bridge management. The main goal of this discussion is the attempt of finding some trends in the research and development of existing bridge management systems (BMS). To achieve this, it is firstly important to analyse the entire process of bridge management, understand which parts of the process are being properly addressed by current BMS and which parts are not account for nowadays. The next step consists in providing some guidance on how to improve BMS considering the parts not being well covered. Likewise, some orientation is required to deal with the parts not yet being accounted for in existing BMS. To this end, insights and tools already used in other fields of knowledge can be considered, adapted and adopted in future BMS. In this regard, artificial intelligence algorithms appear as a sound candidate. |
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| Autores principais: | Matos, José C. |
| Outros Autores: | Santos, Carlos; Coelho, Mário Rui Freitas |
| Assunto: | BMS Asset Management AI BrIM Engenharia e Tecnologia::Engenharia Civil Indústria, inovação e infraestruturas |
| Ano: | 2020 |
| País: | Portugal |
| Tipo de documento: | comunicação em conferência |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | The present paper presents a brief discussion on the current practice regarding bridge management. The main goal of this discussion is the attempt of finding some trends in the research and development of existing bridge management systems (BMS). To achieve this, it is firstly important to analyse the entire process of bridge management, understand which parts of the process are being properly addressed by current BMS and which parts are not account for nowadays. The next step consists in providing some guidance on how to improve BMS considering the parts not being well covered. Likewise, some orientation is required to deal with the parts not yet being accounted for in existing BMS. To this end, insights and tools already used in other fields of knowledge can be considered, adapted and adopted in future BMS. In this regard, artificial intelligence algorithms appear as a sound candidate. |
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