Abstract
A Real-time available platform for deployment and implementation of mobile motion-based biometric behavior is provided by smartphones and smartwatches, including sensors. Sensors and physical activity evaluation are quite limited for motion-based commercial devices. In some cases, the accelerometer sensor of the smartwatch is utilized or walking is investigated. The combination of multiple sensors can perform better in terms of sensors, which can be determined by sensors on both the smartwatch and phones, i.e., accelerometer and gyroscope. For biometric efficiency, some of the diverse activities of daily routine have been evaluated with biometric authentication. The study’s main objective is to track and monitor the daily lives activities using digital devices like smartphones and smartwatches for healthy human life. The result shows that using the different computing techniques in phones and watching for biometric can provide a suitable output based on the mentioned activities. This indicates that the feasibility results of continuous biometrics analysis in terms of average daily routine activities, can enhance the everyday routine life. The study also shows some of the easy to do activities like clapping, and walking may be a viable alternative for healthy life. Fuzzy based classification system is being utilized to improve the tracking system. In the present research, the Fuzzy Rule-Based Classification System justified the improved classification efficiency over the existing techniques for biometric activities.
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Sharma, P., Alshehri, M. & Sharma, R. Activities tracking by smartphone and smartwatch biometric sensors using fuzzy set theory. Multimed Tools Appl 82, 2277–2302 (2023). https://doi.org/10.1007/s11042-022-13290-4
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DOI: https://doi.org/10.1007/s11042-022-13290-4