What is it about?
A new algorithm used in wearable sensors to track a real-time fall effectively and focuses on fall detection via fuzzy-as-a-service based on IEEE 1855-2016, Java fuzzy markup language and service-oriented architecture. Fuzzy logic systems (FLSs) have revealed their capability in ambient intelligence (AmI) applications. However, FLS deployment requires committed and quasi-scalable hardware/software systems. Sharing FLSs capability as web services allows flexibility, transparency, load balancing, efficient resource allocation, and cost-effectiveness.
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Why is it important?
In this study, wearable sensors (i.e., accelerometer and gyroscope) that stimulate human activity monitoring using a rule-dependent FLS are demonstrated. Research findings exhibit that the proposed algorithm could easily differentiate between fall and non-fall occurrences with an accuracy, sensitivity and specificity of 90%, 88.89% and 91.67%, respectively.
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This page is a summary of: Fuzzy logic web services for real-time fall detection using wearable accelerometer and gyroscope sensors, June 2020, ACM (Association for Computing Machinery),
DOI: 10.1145/3389189.3397989.
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