IoT-based real-time passenger safety system with Machine Vision at the Edge (Mez) technology

• Autorzy: Alawad Ali Abdulaziz , Chughtai Muhammad Tajammal

Identyfikatory

DOI

10.15199/48.2023.12.28

Warianty tytułu

PL

System bezpieczeństwa pasażerów w czasie rzeczywistym oparty na IoT z technologią Machine Vision at the Edge (Mez)

• Języki publikacji: EN

Abstrakty

EN

Passenger safety is a critical issue in the transportation industry. There is an additional concern for children’s safety with other regular issues. And that is the risk of having accidents because of the childish act of putting hands, heads, or the upper half of the body out of the window. Children are curious and fun-loving and enjoy school bus time with their friends. Their activities are not always pleasant to adults, which easily distract drivers. That is why the stable emotional state of the drivers of school buses is essential. This paper presents an IoT-based innovative passenger safety system developed to keep the safety concerns associated with school buses. The IR-based sensor in this project prevents passengers from crossing safety limits outside the window. A well-optimized Convolutional Neural Network (CNN) has been designed and developed in this paper to predict the risk level by reading the emotional states of the driver. Real-time video transmission is essential to recognize the driver’s emotional state. However, it is severely hampered by network latency. This paper incorporates the Machine Vision at the Edge (Mez) technology to solve the latency issue and effectively detect the driver’s emotion in real time. This innovative safety system is a potential solution to the unaddressed safety concern of children’s school buses. This paper’s unique approach to solving a practical problem strengthens bus passenger safety.

PL

Bezpieczeństwo pasażerów jest kluczową kwestią w branży transportowej. Dodatkową troską o bezpieczeństwo dzieci są inne regularne kwestie. I to jest ryzyko wypadku na skutek dziecinnego wystawiania rąk, głów lub górnej części ciała przez okno. Dzieci są ciekawskie i kochają zabawę. Lubią spędzać czas w autobusie szkolnym z przyjaciółmi. Ich zajęcia nie zawsze są przyjemne dla dorosłych, co łatwo odwraca uwagę kierowców. Dlatego tak istotny jest stabilny stan emocjonalny kierowców autobusów szkolnych. W artykule przedstawiono innowacyjny system bezpieczeństwa pasażerów oparty na IoT, opracowany w celu spełnienia wymagań bezpieczeństwa związanych z autobusami szkolnymi. Zastosowany w tym projekcie czujnik podczerwieni zapobiega przekraczaniu przez pasażerów granic bezpieczeństwa za oknem. W tym artykule zaprojektowano i rozwinięto dobrze zoptymalizowaną konwolucyjną sieć neuronową (CNN), aby przewidywać poziom ryzyka na podstawie odczytu stanów emocjonalnych kierowcy. Transmisja wideo w czasie rzeczywistym jest niezbędna do rozpoznania stanu emocjonalnego kierowcy. Jednakże jest to poważnie utrudniane przez opóźnienia sieci. W artykule wykorzystano technologię Machine Vision at the Edge (Mez), aby rozwiązać problem opóźnień i skutecznie wykrywać emocje kierowcy w czasie rzeczywistym. Ten innowacyjny system bezpieczeństwa jest potencjalnym rozwiązaniem nierozwiązanych problemów związanych z bezpieczeństwem autobusów szkolnych dla dzieci. Unikalne podejście niniejszego artykułu do rozwiązania praktycznego problemu zwiększa bezpieczeństwo pasażerów autobusów.

Słowa kluczowe

EN

IoT; public transportation; transportation safety

PL

IoT; transport publiczny; bezpieczeństwo transportu

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2023
• Tom: R. 99, nr 12
• Strony: 159--167
• Opis fizyczny: Bibliogr. 35 poz., rys., tab.

Twórcy

autor

Alawad Ali Abdulaziz

• University of Hail, Saudi Arabia

• https://orcid.org/0000-0001-7907-9169

autor

Chughtai Muhammad Tajammal

• University of Hail, Saudi Arabia

• https://orcid.org/0000-0001-9847-6776

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).