Consistent context aware behaviour in smart home environment

Subbaraj, Rajarajeswari; Venkatraman, Neelanarayanan

doi:10.1504/ijssoc.2018.099025

Cited by 2 publications

(1 citation statement)

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“…Goncalves et al [ 17 ] determined and mapped out the physical and emotional state of home care users, implemented a participatory design that included the user within its social, psychological, and therapeutic context, and explored the flexible method when applied to older users. Subbaraj et al [ 18 ] described the process of checking the consistent behavior of a context-aware system in a smart home environment using formal modeling and verification methods. The results confirmed the consistent behavior of the context-aware system in the smart environment.…”

Section: Related Workmentioning

confidence: 99%

Human Activity Classification Using Multilayer Perceptron

Gorjani

Byrtus

Dohnal

et al. 2021

Sensors

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The number of smart homes is rapidly increasing. Smart homes typically feature functions such as voice-activated functions, automation, monitoring, and tracking events. Besides comfort and convenience, the integration of smart home functionality with data processing methods can provide valuable information about the well-being of the smart home residence. This study is aimed at taking the data analysis within smart homes beyond occupancy monitoring and fall detection. This work uses a multilayer perceptron neural network to recognize multiple human activities from wrist- and ankle-worn devices. The developed models show very high recognition accuracy across all activity classes. The cross-validation results indicate accuracy levels above 98% across all models, and scoring evaluation methods only resulted in an average accuracy reduction of 10%.

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Section: Related Workmentioning

confidence: 99%