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Towards Developing a Mobile Application for Detecting Intoxicated People through Interactive UIs

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Part of the Algorithms for Intelligent Systems book series (AIS)

Abstract

Alcohol and Cannabis are among the most frequently used drugs worldwide. Excessive drinking is one of the leading lifestyle-related causes of death across the whole world. Both alcohol and cannabis can cause short-term problems with thinking, remembering, concentrating, and performing psycho-motor tasks. Taking drugs like alcohol and cannabis can impair a person’s ability to perform tasks such as driving a car, flying an airplane, and making critical decisions. Clinical dope test methods are time-consuming, and instant testing devices, such as breathalyzers, are only available to law enforcement personnel which is expensive. Therefore, detecting intoxicated people using ubiquitous devices such as smartphones without any use of external hardware can be a cost-effective, time-saving, and efficient approach for ensuring safe performance in critical tasks. Hence, the objective of this research is to propose a conceptual framework for developing an interactive mobile application that detects intoxicated people by measuring behavioral abnormalities caused by alcohol and cannabis consumption. To accomplish this objective, the effects of alcohol and cannabis are investigated, followed by a review of the available tests in the literature. The proposed conceptual model encompasses testing of balancing capability, grip sense, simple reaction time, choice reaction time, short-time memory, and measuring a person’s heart rate using tasks based on the short-term effects of alcohol and cannabis. Prototypes of the user interfaces are also developed based on the proposed conceptual framework.

Keywords

  • Situational impairments
  • Intoxication
  • Drunkenness
  • Alcohol
  • Cannabis
  • Smartphone app

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Correspondence to Muhammad Nazrul Islam .

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Ara, I., Mubashshira, T., Amin, F.F., Khan, N.I., Islam, M.N. (2022). Towards Developing a Mobile Application for Detecting Intoxicated People through Interactive UIs. In: Uddin, M.S., Jamwal, P.K., Bansal, J.C. (eds) Proceedings of International Joint Conference on Advances in Computational Intelligence. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-0332-8_15

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