Much research has been conducted to improve users’ experience with LCSs by improving the graphic design and content of user interfaces, as well as creating more tangible interactive media. Researchers have found that users’ awareness of their everyday lighting conditions to be low, although most participants considered lighting to be important. A traditional LCS was only used when (a) the lighting was undesirable, (b) the improvement, after using the LCS, was significant or (c) the effort required to use the LCS was relatively low. Interactive and
tangible interfaces could improve the sense of playfulness that users experience when operating LCSs (Offermans, van Essen, & Eggen, 2014).
Dugar and Donn (2011) attempted to establish a framework for future studies on tangible lighting control systems. They proposed that information processing within the human brain can be classified in three systems: the perceptual system, the cognitive system and the motor system. According to them, the two processes of perception are the physical reception of the stimuli and the processing and interpretation of that reception. Cognition is the process of presenting, sequencing, pacing and delegating information on lighting control interfaces appropriately. The motor system includes the output as the human behavioural response mainly involving bodily movement. They summarised three views of tangible interaction in lighting environments, “a data-centred view, an expressive-centred view and a space-centred view.” The data-centred view is from the HCI researchers’ perspective. For them, the design of tangible user interfaces mainly focuses on collecting and utilizing digital data and clearly representing the information. The expressive-centred view, which largely applies to industrial designers, emphasises bodily interaction with objects, rather than the form and appearance of products. The space-centred view focuses on creating interactions between spaces and people by sensing users’ activities in the spaces (Dugar & Donn, 2011).
Chien and Mahdavi’s research explored the requirements of a user-interface system to facilitate effective communication and interaction between building occupants and
environmental systems. Twelve products were compared across three categories (information types, control options, hardware) with seven criteria: functional coverage, environmental information feedback, intuitiveness, mobility, network, input, and output. They suggested that high-tech interface products that offer “high functional coverage” (i.e. offers many different functions) “imposes a large cognitive load on (new) users.” They suggest that control commands should be intuitive and not overly complicated (Chien & Mahdavi, 2008).
Dugar et al. identified the characteristics of an ideal lighting control system by re-examining real-life scenarios using the principles of interaction design. They studied users’ interaction with four types of lighting control interfaces (pushbutton, rotary, slide dimmers, and screen-based virtual interfaces) across six dimensions: appearance, grab-ability, accuracy,
responsiveness, learning speed and ease-of-use (Dugar, Donn, & Osterhaus, 2011). They concluded that end-users preferred remote interfaces that provided the option of controlling
touch-screen-based iconographic representations of light intensities, light colours and lighting scenes. Additionally, end-users desired rich interactive experiences with control interfaces.
High resolution interactive LCSs give users more options, but may lead to user dissatisfaction due to complexity or extra effort required. This could reduce the frequency that users interact with the system, minimizing the potential to save energy (Dugar & Donn, 2011).
After surveying 410 people in 14 office buildings in the United Kingdom, Moore et al. (2002) concluded that occupants recognised the importance of personalised lighting control.
However, some occupants commented that the lighting control systems that they used
“lacked user friendliness.” In a recent study, Yılmaz et al. found that small increments (high resolution) in a dimming system confused users (Yılmaz, Ticleanu, Howlett, King, &
Littlefair, 2016). Although researchers suggested that colour-tunable controls could enhance occupants’ mood, performance etc., they also believe that occupants need to understand better how to use a colour changing control system to achieve their desired effects (Yılmaz et al., 2016).
A control interface for colour-tunable systems could be designed based on a dRGB system, such that each dimension controls a channel of a primary colour. In an LED system, the three control dimensions would control the luminous output of red, green and blue light
respectively. RGB interfaces are the simplest device-specific signals interfaces, with only three channels, but some colour-tunable LED systems have seven or eight channels and can provide an enormous number of colour options, such as ETC (ETC, 2016) and Telelumen products (Telelumen, 2016). The simplest three-channel 8-bit systems can produce 16 million different colours, while a more advanced system can offer up to 3 × 1038 options. These products are usually controlled by computer software. They can mix colours using a variety of models including, but not limited to, CIE chromaticity systems, HSB models and device-specific models that directly control the signals sent to devices, such as DMX, to change the intensity of each single colour channel. Although this type of control software can,
theoretically, provide any colour precisely, they are complicated for untrained, general users.
Dugar and Donn suggested that numerous switching or dimming options (high LCS resolution) could lead to the selection of the wrong light level or create an undesirable atmosphere, making the lighting “annoying and tedious” (Dugar & Donn, 2011).
Some colour control interfaces of commercial products, such as the To Be Touched® from Philips lighting, are based on a design modified from the HSB system and are similar to a conventional artistic colour wheel. A typical design of this type control interface is shown in Figure 6. These interface designs are assumed to be better understood by the general public than RGB interfaces. However, there is little publically available empirical evidence on the usability of the different colour specification interfaces.
Figure 6. A typical control interface design based on a colour wheel, modified from the HSB system.
Another common design is a combination of a colour wheel based on HSB and additional sliders, as shown in Figure 7. For instance, the colour-tunable product, LIFX, uses this type of design (LIFX, 2017). Manufacturers usually select the labels and resolutions of the control dimensions. For instance, “colour”, shown in Figure 7, refers to the control of saturation. The smallest magnitude of change is 1 %. However, there is no available empirical data to suggest that 1 % is an optimal resolution for either saturation or brightness. Although some large companies may conduct research on the usability of LCSs, the research results are usually confidential and not disseminated.
Figure 7. A typical control interface combining sliders with a colour wheel based on the HSB system.
Although the comparison of colour mixing systems for a colour specification interface is a relatively new topic in the lighting industry, it has been studied systematically for televisions and computer displays, which require accurate colour specification.
Schwarz, Cowan and Beatty found that it is difficult for users to specify their desired colours when displays provide 16 million colour options. In an experiment, they compared the usability of RGB, luma, in-phase, quadrature (YIQ), CIELAB, hue, saturation, value (HSV) and opponent colour models for displays (Schwarz, Cowan, & Beatty, 1987). For
inexperienced users, the RGB control interface allowed the fastest completion of colour-matching tasks, but the colour-matching results were not very accurate. The HSV interface was the slowest, but the most accurate (Schwarz et al., 1987).
A conflicting result was reported earlier (Murch, 1984), which found that a hue, saturation, lightness (HSL) interface was the most efficient one for inexperienced users (as cited in Douglas & Kirkpatrick, 1996). However, detailed data was not published. Douglas and Kirkpatrick conducted a colour-matching experiment and reported that no significant
difference in colour matching accuracy was observed between RGB and HSV colour models when the position of current colour in the colour space was shown to the subjects (Douglas &
Kirkpatrick, 1996).
Hughes and Foley claimed that an interface based on the RGB system is not ideal as a colour-selection tool for a computer. This is partly because it is better suited to “material colours but not coloured lights, where the intensity can be arbitrarily large.” The authors further
suggested two alternative interfaces: the HSV interface and the HLS interface. The RGB model is described as a hardware-oriented model, while the HSV model is user-oriented (Hughes & Foley, 2014). Fairchild suggested that, for image editing, three control
dimensions - hue, chroma and lightness - is more intuitive for untrained users to manipulate the image colours than device dependent colour spaces, such as dRGB and CMYK (Fairchild, 2013). However, it is not clear whether the results for displays and image editing are also applicable to lighting.
Beigpour and Pedersen (2015) compared RGB and HSV interfaces in a recent experiment.
The researchers instructed participants to match the colour of a Philips Hue lamp with a colour displayed on a computer screen. When using the HSV interface, participants matched colours more rapidly, but less accurately. It is worth noting that in this experiment, instead of matching the colours displayed on two identical devices, participants matched the colours between a lamp and a computer screen.
Research on colour selection models in the display industries started much earlier than in the lighting industry. There are still some ongoing debates, and no well-accepted result has been forthcoming. Even if their results were consistent, they might not be suitable to apply to lighting products. Computer displays, which are defined as self-luminous objects in colorimetry, are different from light sources for colorimetry purposes. The colorimetric formulae used for displays (self-luminous objects) differ from those for the chromaticity of light (Schanda, 2007).