TY - CHAP
T1 - Artificial intelligence for localisation of ultra-wide bandwidth (UWB) sensor nodes
AU - Che, Fuhu
AU - Ahmed, Abbas
AU - Ahmed, Qasim
AU - Shakir, M. Z.
PY - 2020/12/31
Y1 - 2020/12/31
N2 - In this chapter, we have designed an NB classifier for a UWB-based localization system. With the help of NB classifier and RMSE, the data are classified into three categories: high, medium, and low accuracy. ROCs are plotted to show the effec-tiveness of the NB classifier. As our developed technique obtains more than 90% classification accuracy, we have tested it into two different environments: LOS and partial NLOS conditions. Furthermore, to test the accuracy, small-sized and medium-sized rooms were used. From our measurements, it is observed that the accuracy of the developed NB classifier is dependent upon the environment. For LOS and NLOS envi-ronments, the accuracy are around 97% and 87.38%, respectively. Our future research will concentrate on technique that can further improve the localization classification and improve the positioning accuracy of the IPS
AB - In this chapter, we have designed an NB classifier for a UWB-based localization system. With the help of NB classifier and RMSE, the data are classified into three categories: high, medium, and low accuracy. ROCs are plotted to show the effec-tiveness of the NB classifier. As our developed technique obtains more than 90% classification accuracy, we have tested it into two different environments: LOS and partial NLOS conditions. Furthermore, to test the accuracy, small-sized and medium-sized rooms were used. From our measurements, it is observed that the accuracy of the developed NB classifier is dependent upon the environment. For LOS and NLOS envi-ronments, the accuracy are around 97% and 87.38%, respectively. Our future research will concentrate on technique that can further improve the localization classification and improve the positioning accuracy of the IPS
KW - Artificial intelligence
KW - Ultra-wide bandwidth sensor nodes
UR - https://shop.theiet.org/ai-for-emerging-verticals
UR - http://www.scopus.com/inward/record.url?scp=85114584781&partnerID=8YFLogxK
U2 - 10.1049/pbpc034e_ch9
DO - 10.1049/pbpc034e_ch9
M3 - Chapter
SN - 9781785619823
T3 - Computing and Networks
SP - 189
EP - 203
BT - AI for Emerging Verticals
A2 - Shakir, Muhammad Zeeshan
A2 - Ramzan, Naeem
PB - IET
ER -