Fuzzy Techniques in Visual Performance and Illumination Applications

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The British University in Dubai (BUiD)
The lighting design calculation has many variables that do not realistically have crisp values and therefore can be considered fuzzy. By fuzzy we mean that a particular variable does not have an exact value. The vagueness of such variables will certainly lead to imprecise outcomes. In fact, many visual performance and luminous variables and metrics are- either by nature or by virtue of their inherent complexity- not precise. To come up with an exact output from input that is, by its very nature, uncertain and imprecise is virtually impossible. We believe that the uncertainty that is inherent in many lighting design variables leads to imprecise lighting design outcomes. Hence, Fuzzy logic technique is suitable for implementation in visual performance and illumination applications. Moreover, Fuzzy logic can solve the problem of complex mathematical formulas and a large number of correction factors currently used in visibility models. This work is exploring the possibility of applying the fuzzy techniques in both indoor lighting and road lighting by demonstrating how lighting variables can be represented in fuzzy sets rather than crisp sets. The first part of this study is related to indoor illuminance selection, three variables (Age, Task characteristics, and task importance) have been considered as an input for the fuzzy model with the target Illuminance as the output. This model allows for the lighting designer to select the precise target illuminance based on the actual conditions and avoid underlit or overlit situations. Moreover, a digital tool has been developed based on the membership functions established in this study that allows the lighting designer to check the state of the uniformity and compare the target illuminance (based on his choice or based on the application) with the achieved illuminance from lighting calculations. The second part of this study (road lighting) models the visual performance based on fuzzy techniques. This allows the proposed visual performance model to include more input variables compared to the current visibility models. The input variables are luminance contrast (positive and negative), age, visual size, retinal illuminance, eccentricity, background complexity, and disability glare, while the output variable is the Fuzzy relative visual performance (FRVP). The results of these models have been compared to the current visual performance model and it was found to be in good conformance. Moreover, the term ‘critical contrast’ is introduced, defined as the minimum contrast required to produce a change in the rating of the visual performance for a particular values of visual age, visual size, retinal illuminance, eccentricity, and background complexity. A digital tool has been developed to calculate the fuzzy relative performance and is available to be used
A thesis submitted in fulfilment of the requirements for the degree of DOCTOR OF PHILOSOPHY in Architecture and Sustainable Built environment (ASBE) At The British University in Dubai Supervisor: Prof. Riad Saraiji August 2020
Lighting, Architectural and decorative., Visual performance, fuzzy logic