Abstract
Subjective well-being has a critical affect on progress and productivity vital for digital and strategical trans-formation. Increase in the suicide attempts of the college and university students is a clear indication of stress and anxiety among the students. Offering a fulfilling and healthy life to promote the life-long learning journey is also one of the important objectives of the Vision 2030 for modernization of the Kingdom of Saudi Arabia. Due to the multifaceted nature of subjective well-being, real-time mood measurement and reflection is a challenging task and demands using latest technologies. This paper aims to present Meezaj, an interactive system for real-time mood measurement and reflection leveraging the Internet of Things (IoT) technology. Architecture and workflow of the Meezaj system are discussed in detail. Meezaj not only promotes the sense of significance in the students, by indicating that their happiness matters in decision making, but also assists policy makers to identify factors affecting the happiness in an educational institute.
Highlights
Mental health contributes significantly in our perception about the world and how we react to it
Positive feelings are mainly reflected by happiness, pleasure, and joy while negative feelings are often reflected by stress, sadness, and angriness
Measures that are based on subjective input like Experience Sampling Method (ESM) and Day Reconstruction Method (DRM) are affected by personal bias and take a lot of work from the participant where they have to walk around with a beeper and papers to write down their input [11], [12]
Summary
Mental health contributes significantly in our perception about the world and how we react to it. Measures that are based on subjective input like Experience Sampling Method (ESM) and Day Reconstruction Method (DRM) are affected by personal bias and take a lot of work from the participant where they have to walk around with a beeper and papers to write down their input [11], [12]. Measures that are based on objective input like physical activity, amount of sleep, and social interactions present the challenge of data collection (as the participants must use wearable devices) and the complexity of the data. Large amount and heterogeneity of the data hampers the real-time reflection of the mood Another dimension of the mood reflection challenge is personalization of the working environment to maximize happiness among the individuals. The data collected in terms of responses to the mood survey is analyzed in real-time and mood of the participants is projected through the Meezaj Mood Reflector.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Advanced Computer Science and Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
