# New Approaches in Dynamic Metrics for Lighting Control Systems: A Critical Review
## 5 Discussion of Results
### Complementarity and Utility of Daylighting Metrics  
DA\({}_{300}\) remains the primary reference metric for daylighting due to its ease of interpretation and proven utility in assessing whether a space is adequately lit for a specific task. Its variant, DA\({}_{500}\), introduces a stricter threshold that can better ascertain the luminous quality of spaces where tasks requiring higher visual perception are performed. However, by definition, neither DA300 nor DA500 accounts for potential discomfort caused by glare, making it necessary to rely on complementary metrics. Useful Daylight Illuminance (UDI) might seem an appropriate complement to DA, yet its upper illuminance threshold does not ensure an accurate assessment of glare either. Nevertheless, beyond evaluating whether the analyzed space exhibits illumination deficiencies based on the chosen illuminance threshold, UDI provides insights into zones potentially subject to excessive solar incidence, which could, in turn, affect thermal demand--especially in the case of cooling. This being stated, UDI alone cannot determine excessive solar gain, as there are other more suitable metrics for that purpose. According to the results of this study, it could be argued that UDI proves most effective when used in conjunction with spatial metrics. Both sDA and ASE provide an overall view of the daylighting availability and spatial distribution in a given space. Their simplicity makes them highly attractive for designers with limited experience in daylight simulation tools. However, as demonstrated in previous sections, their unreflective use without the assistance of other metrics can lead to significant errors. Two spaces may present similar sDA and ASE values while displaying very different luminous conditions. Therefore, particular caution is required when comparing spaces with different locations and orientations. In this regard, a metric like UDI serves as a valuable tool to better understand what is truly occurring within that space. Nevertheless, neither UDI nor ASE accurately assesses visual discomfort due to glare, necessitating the use of a specialized metric designed for such concerns. While a combination of UDI, sDA, and ASE--or alternatively DA, sDA, and ASE, if more spatial detail is needed--along with appropriate glare metrics might appear sufficient, it is important to emphasize that none of these are explicitly aimed at promoting healthier spaces beyond fulfilling the minimum illuminance required to avoid vision impairment. In this context, CSA can be useful for estimating the percentage of days on which adequate melatonin suppression is achieved to promote circadian entrainment. Even so, the intrinsic limitations of CSA--already outlined in the introductory review--must not be overlooked. The underlying models of circadian entrainment on which this metric is based are still under active development. Therefore, future revisions to the CSA are expected to change as the model is updated based on new research. Beyond traditional metrics focused on visual comfort and emerging indices related to circadian health, the effective integration of daylight into building operation strategies requires sophisticated tools. In particular, the design of intelligent lighting control systems--particularly those aiming for sensorless operation--demands a nuanced understanding of daylight availability under specific sky conditions. It is precisely to address this need that the Continuous Overcast Daylight Autonomy (DAo.con) metric has been developed. DAo.con is a hybrid dynamic daylighting metric designed to estimate the availability of daylight under overcast-sky conditions. It builds upon DAcon and DAo by combining their respective approaches--temporal continuity and daylight-only analysis--into a unified model that is especially suited to predicting lighting demand in unfavorable daylighting scenarios. Thus, DAo.con integrates core concepts from both DAcon and DAo, combining them for an assessment under overcast-sky conditions with a gradient-based evaluation approach.