Radio frequency based inpainting for indoor localization using memoryless techniques and wireless technology

• Autorzy: Prasanthi Tammineni Shanmukha , Rayavarapu Swarajya Madhuri , Rao Gottapu Sasibhushana , Goswami Raj Kumar , Kumar Gottapu Santosh

Identyfikatory

DOI

10.35784/iapgos.6236

Warianty tytułu

PL

Obrazowanie oparte na częstotliwości radiowej do lokalizacji wewnątrz pomieszczeń z wykorzystaniem technik bezpamięciowych i technologii bezprzewodowej

• Języki publikacji: EN

Abstrakty

EN

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.

PL

W ostatnim czasie Internet Rzeczy (IoT) rozwinął się i objął nadzór nad urządzeniami poprzez wykorzystanie Systemów Pozycjonowania Wewnętrznego (IPS) i Usług Lokalizacyjnych (LBS). Jedną z powszechnie stosowanych metod pozycjonowania wewnętrznego (IPS) jest wykorzystanie sieci bezprzewodowych do określenia lokalizacji celu. Osiąga się to poprzez wykorzystanie urządzeń o znanej pozycji. Usługi oparte na lokalizacji (LBS) odgrywają istotną rolę w wielu aplikacjach inteligentnych budynków, umożliwiając tworzenie wydajnych i efektywnych środowisk pracy. W niniejszym opracowaniu przeanalizowano cztery algorytmy pozycjonowania bez pamięci, a mianowicie K-Nearest Neighbour (KNN), drzewo decyzyjne, Naïve Bayes i Random Forest Regressor. Algorytmy są porównywane na podstawie ich wydajności pod względem błędu średniokwadratowego, pierwiastka błędu średniokwadratowego, średniego błędu bezwzględnego i współczynnika determinacji R2. Przeprowadzono analizę porównawczą w celu zweryfikowania wyników różnych technik bez pamięci w technologii Wi-Fi. Na podstawie dowodów empirycznych ustalono, że Naïve Bayes jest strategią lokalizacji, która wykazuje najwyższy poziom dokładności. Zbiór danych zawierający pomiary wskaźnika siły odbieranego sygnału (RSSI) ze wszystkich badań jest dostępny online.

Słowa kluczowe

EN

RSSI; K-Nearest Neighbour; indoor localization; Random Forest Regressor

PL

RSSI; K-Nearest Neighbour; lokalizacja wewnątrz pomieszczeń; Random Forest Regressor

• Wydawca: Wydawnictwo Politechniki Lubelskiej
• Czasopismo: Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
• Rocznik: 2024
• Tom: T. 14, nr 4
• Strony: 10--15
• Opis fizyczny: Bibliogr. 26 poz., rys., tab.

Twórcy

autor

Prasanthi Tammineni Shanmukha

• Andhra University College of Engineering, Department of Electronics and Communication Engineering, Visakhapatnam, India

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

autor

Rayavarapu Swarajya Madhuri

• Andhra University College of Engineering, Department of Electronics and Communication Engineering, Visakhapatnam, India

• https://orcid.org/0009-0007-7559-2142

autor

Rao Gottapu Sasibhushana

• Andhra University College of Engineering, Department of Electronics and Communication Engineering, Visakhapatnam, India

• https://orcid.org/0000-0001-6346-8274

autor

Goswami Raj Kumar

• Gayatri Vidya Parishad College of Engineering for Women, Departement of Electronics and Communication Engineering, Visakhapatnam, India

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

autor

Kumar Gottapu Santosh

• Gayatri Vidya Parishad College of Engineering, Departement of Civil Engineering, Visakhapatnam, India

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

Bibliografia

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