Citation

Bari, Md Ahsanul and Tan, Kim Geok and Sayeed, Md. Shohel and Hossen, Md Ismail and Pa, Pa Min (2022) IoT Based Indoor Object Location Tracking Solution. In: 2022 10th International Conference on Information and Communication Technology (ICoICT), 2-3 August 2022, Bandung, Indonesia.

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Abstract

Internet of Things (IoT) is enhancing the pleasant of present-day life. IoT-based objects tracking is a crying need for a smart indoor environment. In the age of smart cities, there are many applications in which indoor localization can be used for monitoring and tracking objects inside smart buildings. This research study is based on the development of a robust real-time system capable of localizing and tracking objects accurately. Global Positioning Systems (GPS) are typically used for outdoor localization because of their ease of implementation and accuracy of up to five meters. Because of the limited space and the many obstacles in indoor environments, GPS is not an appropriate option for overcoming those obstacles. Thus, tracking objects in an indoor environment is a major challenge, both in terms of accuracy and efficiency. The main objective of this research is to design and develop an IoT-based effective solution for tracking the location of objects indoors using the fingerprinting technique. There are some existing applications for tracking objects in indoor localization. Those existing indoor location tracking technologies' reported pitfalls are expensive infrastructure, high connectivity, and less accuracy. Therefore, we have come up with this proposed algorithm to solve those problems. The proposed approach has the potential to estimate the position and track objects very accurately indoors. The proposed algorithm is applied in two different indoor location simulations. The proposed method has been implemented and experiments have been conducted. Experiment results demonstrate that the proposed approach works very well with wi-fi/LTE collected data.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	IoT , Indoor Location , Tracking , RSSI , Fingerprinting , GPS
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions:	Faculty of Engineering and Technology (FET) Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	05 Jan 2023 01:37
Last Modified:	10 Apr 2023 04:02
URII:	http://shdl.mmu.edu.my/id/eprint/10758

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