The research aims to explore a solution in addressing the lack of unified gestural systems in smart home environments. However, in the context of cultural differences, the hand gesture can create uncomfortable feelings for specific users who might read a negative expression from the movement. Therefore, this study attempts to explore the possibility of establishing a simple set of hand gestures, controlling mechanisms for smart home devices that can be widely understood by people of various cultural backgrounds.
According to Statista, a consumer needs for IoT (Internet of Things) has been growing exponentially since the year 2014 and projects an additional revenue growth rate of 14.9 % up to the year 2022. With the growth of home automation technology, an increasing need for users to engage and control smart devices has been rising.
The hand gestures in a current smart home system are limited by the context of a user’s geographical location and its cultural influences on the user. The problem of introducing a set of hand signals in a smart home environment is that each culture often interprets the gestures differently from one another.
This research investigated gestural systems available in the current market to develop a set of universal hand gestures, in an attempt to improve interactions with smart home devices, regardless of the user’s geographical location. The empirical research method was chosen to derive measurable data from participants in different countries from finding a “Universal hand gestural system.” The collected data was divided into three groups. The percentile ranking measurement was used as the perimeter to define tested hand gestures into three categories: Universal, limited, and non-universal.
This research first gathered hand gestures from current smart home automation companies such as Bixi, Fibaro, and Singlecue. The hand gestures were also collected from automotive and computer manufacturers like BMW, Byton, Gest, Gestoos, Google, Leap Motion and Microsoft. The table chart provided an overview of all of the collected hand gestural systems. The chart was composed of industry categories, company names, types of commands and images of hand gestures.
In search of finding a simple set of “Universal” hand gestures for human-machine interactions in a smart home environment, 10 gestures were assembled from the pool of various gestural systems collected in the table chart. The newly assembled hand gestures and triggers from the chart were chosen based on their number of appearances and cultural influences.
The set of basic hand gestures was converted into a survey questionnaire. All 10 components in the basic set became 10 independent questions each contained with a hand image and assigned triggers. The multiple question format was chosen to list all the triggers. The survey participants were then asked to select a single trigger which they associated the most with the hand image given in each question. In the United States alone, the raw head counts of the respondents were over 420. The actual number of survey participants was condensed to 35 people who represented a statistical demographic sample of the country.
The first round of the survey results provided this study with directions to modify hand gestures. The modifications on the first set of hand gestures were performed to enhance their communication to broader ethnic groups. This newly modified set of hand gestures were converted to 10 multiple questions each with 3-4 assigned trigger options. The second survey process was exactly repeated to match the first round of surveys.
The percentile ranking system was chosen to process the findings in this study. This process provided an opportunity for this study to rank each trigger from different countries altogether.
The percentile ranking system was chosen to process the findings in this study. This process provided an opportunity for this study to rank each trigger from different countries altogether. Also, the ranking system allowed this research to categorize the data set into the three sections created by the median, and 75th percentile breaking points.
There were 30 triggers tested in the first round of the survey. The percentile ranking number was rounded up from 0.5.
For example,this study used the following formula to find 75th percentile rank. was rounded to 8. The same percentile ranking process applied to the second round of the surveys from each country. The findings were combined into a visualized ranking chart which included the rankings of all hand gestures and their assigned triggers. Any triggers that were ranked equal to or greater than the 75th percentile from all three countries were defined as a universal set of hand gestures in this research. Out of 10 universal hand gestures defined, “Mute” ranked at the highest in the chart from both rounds of the tests in all three countries.
The findings were combined into a visualized ranking chart which included the rankings of all hand gestures and their assigned triggers. Any triggers that were ranked equal to or greater than the 75th percentile from all three countries were defined as a universal set of hand gestures in this research. Out of 10 universal hand gestures defined, “Mute” ranked at the highest in the chart from both rounds of the tests in all three countries.