Challenges and Opportunities in Utilizing IoT-Based Stress Maps as a Community Mood Detector
| Autor: | Shafaq Chaudhry, Naim Kapucu, Wei Wang, Charles Millican, Murat Yuksel, Damla Turgut |
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| Rok vydání: | 2019 |
| Předmět: |
business.industry
05 social sciences Internet privacy 020206 networking & telecommunications Crisis response 02 engineering and technology 0506 political science Stress level Highly sensitive Mood Stress (linguistics) 050602 political science & public administration 0202 electrical engineering electronic engineering information engineering medicine Anxiety Social media medicine.symptom Psychology business Internet of Things |
| Zdroj: | 2019 IEEE International Symposium on Technologies for Homeland Security (HST). |
| DOI: | 10.1109/hst47167.2019.9032995 |
| Popis: | Stress has been known to cause physical and mental issues like depression, anxiety, insomnia, lower immunity, stroke, as well as leading to suicidal thoughts or violence towards others. Stress is not just a state of mind, but it is measurable. With the ubiquity of Internet of Things (IoT), and the integration with highly sensitive biosensors, it may be feasible to use these devices for detecting stress in public places. Moreover, correlating such stress data with social media streams can lead to insights into the psychological well-being of the community as a whole. We present a framework of such a community stress map based on social media and explore techniques for gathering data for measuring stress levels as well as detecting abnormal levels. This stress map can then be leveraged by emergency and crisis response teams for public safety and help them be proactive in allocating resources to the stressed areas indicated in the map. |
| Databáze: | OpenAIRE |
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