Machine Learning Based Indoo Positioning System

Citation

Mazlan, Aqilah and Ng, Yin Hoe and Yip, Sook Chin (2022) Machine Learning Based Indoo Positioning System. In: Postgraduate Colloquium December 2022, 1-15 December 2022, Multimedia University, Malaysia. (Unpublished)

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Abstract

Location-based services (LBSs) offer services to users by leveraging a the user’s physical location. A highly accurate indoor localization system (IPS) is now achievable thanks to the advancements wireless communication networks and built-in sensors in mobile devices. However, deploying the system to a resource constrained device may still be difficult due to the system’s computational complexity and implementation costs. I

Item Type: Conference or Workshop Item (Poster)
Uncontrolled Keywords: wireless communication networks, convolutional neural network
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 28 Dec 2022 06:32
Last Modified: 28 Dec 2022 06:32
URII: http://shdl.mmu.edu.my/id/eprint/11031

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