Ubiquitous sensors to improve self-regulation skills in multiple environments
Unobtrusive technology (software and hardware) can be used to increase the capacity of human beings to observe themselves and their surrounding. Some contexts such as learning, collaboration, or healthy habits can benefit from applications that monitor, analyse and interact with subjects. Motivation, time management, self-regulation, emotional intelligence are all aspects that can be enhanced with the proper use of technology. These enhancements are challenging to achieve and require a careful design of applications so that they seamlessly blend with every day environments.
The objective of the work is to devise novel and creative applications combining hardware and software that can be used in every-day situations so that one or more aspects of an individual or community of users is observed, analysed and then affected by it so that it is improved. The identification of the most relevant contexts in which this paradigm can be applied are part of the work. A thorough exploration of the user needs and requirements is needed to identify those situations with larger potential for technology to have a positive impact. The research must include the deployment of demonstrators that prove the practicality of the proposed techniques. User validation is a must to ensure the potential for future exploitation.
The work requires the use of state-of-the-art technology to sense, observe or capture human or community aspects. As a guidance, contexts in the area of medicine, ageing, learning, team dynamics, energy consumption, environmental improvements, sustainability, fostering creativity, are desirable. These areas need truly innovative uses of technology to tackle problems that affect large sections of the population. Candidates must be proficient handling new hardware equipment, design new devices, and programming from the device to the application level. Additionally, a solid background on statistical science and quantitative and qualitative analysis is required to use in empirical studies with subjects.
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The opportunity ID for this research opportunity is: 1662
Other opportunities with Associate Professor Rafael A. Calvo