2019 IEEE Region 10 Symposium (TENSYMP) 2019
DOI: 10.1109/tensymp46218.2019.8971248
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Environment Dependent Neural Network Model For Occupancy Detection

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Cited by 3 publications
(2 citation statements)
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“…We sought to obtain a reliable model, that would also be lightweight, and which could be embedded into an IoT device with limited resources and be supported by several previous studies [ 28 , 30 , 32 , 33 ]. Artificial Neural Networks were selected as a classification technique for the proposed certificate model.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…We sought to obtain a reliable model, that would also be lightweight, and which could be embedded into an IoT device with limited resources and be supported by several previous studies [ 28 , 30 , 32 , 33 ]. Artificial Neural Networks were selected as a classification technique for the proposed certificate model.…”
Section: Methodsmentioning
confidence: 99%
“…Many previous studies argue that the tendency to use ANNs owes to their embedded strengths, their rapid processing prediction abilities [ 28 , 32 ], as well as their capacity to determine the relationships between different variables in the absence of any initial assumption or postulate. In addition to their more general advantages, several works have used these types of techniques in the field of occupancy control [ 29 , 30 , 33 ] and indoor air quality [ 31 , 34 , 35 ].…”
Section: Background and Related Workmentioning
confidence: 99%