scholarly journals Lip Motion Pattern Recognition for Indonesian Syllable Pronunciation Utilizing Hidden Markov Model Method

2015 ◽  
Vol 13 (1) ◽  
pp. 173 ◽  
Author(s):  
Balza Achmad ◽  
Faridah Faridah ◽  
Laras Fadillah
Keyword(s):  
Pattern Recognition ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Motion Pattern ◽  
Model Method

scholarly journals A Proposed Hidden Markov Model Method for Dynamic Device Pairing on Internet of Things End-Devices

2021 ◽  
Vol 14 (3) ◽  
pp. 274-285
Author(s):  
Aji Gautama Putrada ◽  
Nur Ghaniaviyanto Ramadhan
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Access Point ◽  
Received Signal Strength Indicator ◽  
Model Method ◽  
Iot Platform ◽  
High Level ◽  
Device Pairing ◽  
Better Than

Dynamic device pairing is a context-based zero-interaction method to pair end-devices in an IoT System based on Received Signal Strength Indicator (RSSI) values. But if RSSI detection is done in high level, the accuracy is troublesome due to poor sampling rates. This research proposes the Hidden Markov Model method to increase the performance of dynamic device pairing detection. This research implements an IoT system consisting an Access Point, an IoT End Device, an IoT Platform, and an IoT application and performs a comparison of two different methods to prove the concept. The results show that the precision of dynamic device pairing with HMM is better than without HMM and the value is 83,93%.

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