Development and Implementation of a Self-Optimizable Smart Lighting System Based on Learning Context in Classroom

Light environment affects the efficiency of surgical suture training

BACKGROUND

Suture knotting is the basis of surgical skills. In the process of surgical skills learning, the surrounding environment, especially the light, will affect the efficiency of learning. This study investigated the effect of optical environment on the learning of stitching and knotting skills.

METHODS

A total of 44 medical students were randomly divided into four groups and participated in the study of suture knotting in four different optical environments. During the process, we assess objective pressure level by testing salivary amylase activity Likert scale and objective structured clinical examination (OSCE) was used to estimate the subjective psychological state and overall skill mastery in surgical suturing respectively.

RESULTS

Under high illumination conditions (700 lx), the salivary amylase activity of the high color temperature group (6000 K) was significantly higher than that of the low color temperature group (4000 K) (p < 0.0001). Similarly, under low illumination (300 lx), the salivary amylase activity of the high color temperature group was also significantly higher than that of the low color temperature group (p < 0.05). The student under high illumination conditions (700 lx) and the low color temperature (6000 K) have an autonomy score between 37-45, which is significantly higher compared to the other three groups (p < 0.0001). Group 2 has an average OSCE score of 95.09, which were significantly higher than those of the other three groups (p < 0.05).

CONCLUSION

High illumination combined with low color temperature is considered as the optimal training conditions, promoting trainees' optimism, reducing stress levels, and enhancing learning efficiency. These results highlight the pivotal role of light environment in improving the quality and efficiency of surgical skills training.

Emotional responses of college students to filtered fluorescent lighting in a classroom (v3)

Background

Classroom lighting, usually bright fluorescent light, can significantly influence the learning environment and emotions of students.

Objective

To assess the emotional impact of classroom lighting on students during an academic year.

Methods

This study used an ABAB withdrawal research design in the following manner: in phase A, the baseline condition, classroom lighting was provided by conventional overhead white fluorescent classroom lights; in phase B, the intervention condition, the conventional overhead white fluorescent classroom lights were covered with fabric filters (thin, translucent, creamy-colored plastic sheets) that were attached to the lighting fixture frame with magnetic discs. The filters produced softer light in the classroom than the fluorescent lights. Each phase lasted for at least 2 weeks. During each phase, students rated 18 pairs of words from the Mehrabian and Russell pleasure, arousal, and dominance semantic differential scale at least four times to assess the emotional impact of the lighting conditions.

Results

For all three emotional behaviors, the mean score of the filtered fluorescent light phase was significantly greater than the mean score of the baseline unfiltered fluorescent lighting phase, indicating more positive emotional responses. Students also noted they experienced fewer headaches and found it easier to see the whiteboard at the front of the classroom when the light filters were in place.

Conclusion

The light filters exerted a positive impact on the students' emotions. Students preferred the filtered lighting to fluorescent lighting. This study supports the installation of filters over fluorescent lights in a college classroom.

Prototyping a Lighting Control System Using LabVIEW with Real-Time High Dynamic Range Images (HDRis) as the Luminance Sensor

Lighting control systems (LCSs) play important roles in maintaining visual comfort and energy savings in buildings. This paper presents a prototype LCS using LabVIEW with real-time high dynamic range images and a digital multiplex controller to brighten lamps sequentially to provide visual comfort. The prototype is applied to a scaled classroom model with three schemes involving different activities and needs: writing and reading, requiring a uniform luminance of approximately 100 cd/m2, teaching using a whiteboard, requiring an illuminance of approximately 120 cd/m2 for the whiteboard and 60 cd/m2 for the desks, and drawing and art activities focused on the center of the room, requiring an illuminance of approximately 100 cd/m2 for the center area and 50 cd/m2 for the background area. For each scheme, two conditions are presented: one in which the room is treated as a closed room without windows, and the one in which the room has a large window on one wall that enables daylight to penetrate the room. The prototype works well with both schemes and provides different combinations of lamp brightness levels, starting from 10% to 60%, based on the activities and required luminance, and can save around 73–82% of electricity. The presence of daylight does not always result in more energy savings, as the brightness contrast for visual comfort needs to be considered.

Design and Implementation of an IoT-Based Smart Classroom Incubator

Ambient conditions influence human health, emotions, and mental power. Therefore, numerous studies have been conducted in different disciplines on the measurement and control of ambient conditions in classrooms. Moreover, a number of studies identify some physical and mental performances of students simultaneously or for informative purposes by utilizing various hardware and software. However, these studies did not consider automatic control processes and individuality in fulfilling classroom ambient conditions, which influence students’ behavior. This study aims to reduce the adverse impacts of environmental factors on learning and control more necessary physical parameters with higher accuracy using the latest technology and methods. Thus, a new smart classroom incubator (SCI) algorithm, including hardware, software, and experimental studies, in which individual differences could be considered even in the same classroom environment, and its implementation were presented. The system enables access and monitoring of data wherever there is Internet connection. Moreover, it was designed based on IoT because it allows for data transfer over web services or data-dependent operations. All the necessary equipment was placed in the classroom without affecting the learning environment and distracting the class. Cronbach’s α coefficient, which indicates the reliability of the implemented model, was 0.891.