Abstract
The aim of this chapter is to propose the use of process monitoring on buildings to gain continuous feedback from the use, for both monitoring risks and learning by use. During this phase the actual performance of what has been predicted is measured in order to check the quality of forecasts. Eventual differences between performance expected and these measured would call either for a review on previsions, or for an intervention on the object measured. For monitoring of building performance data and the possibility for more data abounds but currently only few are the organizations prepared to actually gather the available information and use it for building management. Moreover monitoring techniques on building are often techniques to punctually check the level of performances and not actual continuous monitoring of them. To establish a system of building continuous monitoring that allows ready response, the systems of monitoring of processes can be adopted. Three examples of real-time monitoring and responding system, based on a monitoring of process, are reported from projects of the MIT | Senseable City Laboratory.
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Notes
- 1.
Mathematical methods: mathematical models are, in general theoretical models that simulate the performance object for verification. For example models to test behavior under load of structures.
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Verification methods: are methods to verify the presence of provisions in respect to precise requirements.
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Subjective methods for test statistics: they are “investigations Doxa” verification methods. Evaluate, with appropriate techniques, the degree of satisfaction of a sample of users with regard to determining performance of the building product.
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Source: http://senseable.mit.edu/enel/.
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Websites and documents available online
MIT | Senseable City Laboratory. Future ENEL project [Online]. Available at: http://senseable.mit.edu/enel/
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Martani, C. (2015). Risk Management Through Process Monitoring: Reducing Uncertainty and Improving Risk Assessment Effectiveness Through Knowledge Gathering Over Time. In: Risk Management in Architectural Design. SpringerBriefs in Applied Sciences and Technology(). Springer, Cham. https://doi.org/10.1007/978-3-319-07449-8_3
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DOI: https://doi.org/10.1007/978-3-319-07449-8_3
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