Publicação
An ecosystem approach to the design of sensing systems for bicycles
| Resumo: | Bicycles equipped with sensors, processing capacity and communications can be a promising source of data about the personal and the collective reality of urban cycling. While this concept has been attracting considerable interest, the key assumption is the design of a closed system where a uniform set of sensing bicycles, with a concrete set of sensors, is used to support a specific service. The core challenge, however, is how to generalise sensing approaches so that they can be collectively supported by many heterogeneous bicycles, owned by a multitude of entities, and integrated into a common ecosystem of urban data. In this work, we provide a comprehensive analysis of the design space for onbike sensing. We consider a diverse set of sensing alternatives, the potential value propositions associated with their data, and the collective perspective of how to optimise sensing by exploring the complementarities between heterogeneous bicycles. This broader perspective should inform the design of more effective sensing strategies that can maximise the overall value generated by bicycles in smart cycling ecosystems and enable new cycling services |
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| Autores principais: | Cabral, Ricardo João Santos Pina |
| Outros Autores: | Peixoto, Eduardo Filipe Rodrigues; Carvalho, Carlos Eduardo Tinoco; José, Rui |
| Assunto: | smart mobility cycling data sensing bicycle |
| Ano: | 2021 |
| 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: | Bicycles equipped with sensors, processing capacity and communications can be a promising source of data about the personal and the collective reality of urban cycling. While this concept has been attracting considerable interest, the key assumption is the design of a closed system where a uniform set of sensing bicycles, with a concrete set of sensors, is used to support a specific service. The core challenge, however, is how to generalise sensing approaches so that they can be collectively supported by many heterogeneous bicycles, owned by a multitude of entities, and integrated into a common ecosystem of urban data. In this work, we provide a comprehensive analysis of the design space for onbike sensing. We consider a diverse set of sensing alternatives, the potential value propositions associated with their data, and the collective perspective of how to optimise sensing by exploring the complementarities between heterogeneous bicycles. This broader perspective should inform the design of more effective sensing strategies that can maximise the overall value generated by bicycles in smart cycling ecosystems and enable new cycling services |
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