Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Kenny Fong Peng Wye"'
Autor:
Kenny Fong Peng Wye1,2 pengwye@studentmail.unimap.edu.my, Mamduh Syed Zakaria1., Syed Muhammad2, Kamarudin, Latifah Munirah1,2, Zakaria, Ammar2,3, Ahmad, Norhawati1,2
Publikováno v:
International Journal of Nanoelectronics & Materials. 2021 Special Issue, Vol. 14, p117-125. 9p.
Autor:
Kenny Fong Peng Wye, E. Kanagaraj, N. Ahmad, Syed Muhammad Mamduh Syed Zakaria, Latifah Munirah Kamarudin, Ammar Zakaria
Publikováno v:
2019 IEEE International Conference on Sensors and Nanotechnology.
This paper documents the implementation of a zone-based localization in an industrial environment based on active RFID system by observing the RSSI values. The active RFID system uses signal strength information to classify which zone the RFID tags a
Autor:
Syed Muhammad Mamduh Syed Zakaria, Latifah Munirah Kamarudin, N. Ahmad, Kenny Fong Peng Wye, Ammar Zakaria
Publikováno v:
Journal of Physics: Conference Series. 1755:012032
Recent developments in location-based services have heightened the needs for decent accuracy localization system for different applications. The Global Positioning System (GPS) provides adequate accuracy in the outdoor environment but suffers from po
Autor:
Kenny Fong Peng Wye, Ammar Zakaria, Kamarulzaman Kamarudin, Latifah Munirah Kamarudin, Syed Muhammad Mamduh Syed Zakaria, N. Ahmad
Publikováno v:
Journal of Physics: Conference Series. 1755:012033
Radio Frequency (RF) based indoor is challenging due to the multipath effect in indoor signal propagation such as reflection, absorption, diffraction due to obstacles, interference and moving objects within the environments. The multipath effect phen
Autor:
Ammar Zakaria, N. Ahmad, Kamarulzaman Kamarudin, Latifah Munirah Kamarudin, Syed Muhammad Mamduh Syed Zakaria, Kenny Fong Peng Wye, E. Kanagaraj
Publikováno v:
IOP Conference Series: Materials Science and Engineering. 705:012038
This document discusses the novel approach to localize human location based on the current zone via k-mean clustering. A pilot experimental analysis of k-mean clustering to group similar RSSI pattern is compared to user defined zones. The dataset col