RADIO FREQUENCY BASED INPAINTING FOR INDOOR LOCALIZATION USING MEMORYLESS TECHNIQUES AND WIRELESS TECHNOLOGY

Tammineni Shanmukha Prasanthi; Swarajya Madhuri Rayavarapu; Gottapu Sasibhushana Rao; Raj Kumar Goswami; Gottapu Santosh Kumar

doi:10.35784/iapgos.6236

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Published: Dec 21, 2024

DOI: https://doi.org/10.35784/iapgos.6236

Issue Vol. 14 No. 4 (2024)

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RADIO FREQUENCY BASED INPAINTING FOR INDOOR LOCALIZATION USING MEMORYLESS TECHNIQUES AND WIRELESS TECHNOLOGY
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FUNCTIONALLY INTEGRATED DEVICE FOR TEMPERATURE MEASUREMENT
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STUDY OF THE OZONE CONTROL PROCESS USING ELECTRONIC SENSORS
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COMPUTER SIMULATION OF A SUPERCONDUCTING TRANSFORMER SHORT-CIRCUIT
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AI-BASED FIELD-ORIENTED CONTROL FOR INDUCTION MOTORS
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THE UTILIZATION OF MACHINE LEARNING FOR NETWORK INTRUSION DETECTION SYSTEMS
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Arman Mohammad Nakib

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154-163

DOI

https://doi.org/10.35784/iapgos.6236

Authors

Tammineni Shanmukha Prasanthi

prashanthitammineni.rs@andhrauniversity.edu.in

Andhra University, India

https://orcid.org/0009-0000-5352-2265

Swarajya Madhuri Rayavarapu

madhurirayavarapu.rs@andhrauniversity.edu.in

Andhra University, India

Gottapu Sasibhushana Rao

sasigps@gmail.com

Andhra University, India

Raj Kumar Goswami

rajkumargoswami@gmail.com

Gayatri Vidya Parishad College of Engineering for Women, India

https://orcid.org/0000-0002-0651-6783

Gottapu Santosh Kumar

kumar.santou@gmail.com

Gayatri Vidya Parishad College of Engineering, India

https://orcid.org/0000-0002-1452-9752

Abstract

Recently, the Internet of Things (IoT) has grown to encompass the surveillance of devices through the utilization of Indoor Positioning Systems (IPS) and Location Based Services (LBS). One commonly used method for developing an Intrusion Prevention System (IPS) is to utilize wireless networks to determine the location of the target. This is achieved by leveraging devices with known positions. Location-based services (LBS) play a vital role in many smart building applications, enabling the creation of efficient and effective work environments. This study examines four memoryless positioning algorithms, namely K-Nearest Neighbour (KNN), Decision tree, Naïve Bayes and Random Forest regressor. The algorithms are compared based on their performance in terms of Mean Square Error, Root Mean Square Error, Mean Absolute Error and R². A comparative analysis has been conducted to verify the outcomes of different memoryless techniques in Wi-Fi technology. Based on empirical evidence, Naïve Bayes has been determined to be the localization strategy that exhibits the highest level of accuracy. The dataset containing the Received Signal Strength Indicator (RSSI) measurements from all the studies is accessed online.

Keywords:

RSSI, K-Nearest Neighbor, Indoor Localization, Random Forest Regressor

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Prasanthi, T. S., Rayavarapu, S. M., Rao, G. S., Goswami, R. K., & Kumar, G. S. (2024). RADIO FREQUENCY BASED INPAINTING FOR INDOOR LOCALIZATION USING MEMORYLESS TECHNIQUES AND WIRELESS TECHNOLOGY. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 14(4), 10–15. https://doi.org/10.35784/iapgos.6236

RADIO FREQUENCY BASED INPAINTING FOR INDOOR LOCALIZATION USING MEMORYLESS TECHNIQUES AND WIRELESS TECHNOLOGY

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