Isbn: 9786204190266 - deep learning & iot based smart life saving emergency trafficlight control (18 resultados)

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2021

    6204190261 / 9786204190266

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2021

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2021

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    Paperback. Condición: Brand New. 64 pages. 5.91x0.15x8.66 inches. In Stock.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2021

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    Librería: Books Puddle, Woodside, NY, Estados Unidos de AmericaBooks Puddle

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Aug 2021, 2021

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    Librería: Wegmann1855, Zwiesel, AlemaniaWegmann1855

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    Taschenbuch. Condición: Neu. Neuware -In order to reduce the traffic congestion and to improve the service speed of ambulance and fire service, many systems need to be developed. In this project, a smart and automatic emergency traffic signal system is proposed. It supports especially like highest traffic congestion especially in cities. The proposed approach gives solution for emergency services like ambulance and fire trucks, in order to avoid traffic and reach the destination in time. This proposed system architecture is based on deep learning algorithm and with support Internet-of Things (IoT) devices. The problem of ambulance and fire engine getting stuck in traffic jam increasing and nearly 20% of emergency patients death were caused by traffic jam in a year. To overcome this problem, handling of traffic and emergency situation by detecting the ambulance or fire engine about 100 meters away by blocking other ways and sets back to normal operation after it crossed the signal. The end results, the emergency vehicles to pass through the traffic with no or minimum waiting time. In future work, need to avoid the uneven traffic flow and enhancing the safety.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Aug 2021, 2021

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Taschenbuch. Condición: Neu. Neuware - In order to reduce the traffic congestion and to improve the service speed of ambulance and fire service, many systems need to be developed. In this project, a smart and automatic emergency traffic signal system is proposed. It supports especially like highest traffic congestion especially in cities. The proposed approach gives solution for emergency services like ambulance and fire trucks, in order to avoid traffic and reach the destination in time. This proposed system architecture is based on deep learning algorithm and with support Internet-of Things (IoT) devices. The problem of ambulance and fire engine getting stuck in traffic jam increasing and nearly 20% of emergency patients death were caused by traffic jam in a year. To overcome this problem, handling of traffic and emergency situation by detecting the ambulance or fire engine about 100 meters away by blocking other ways and sets back to normal operation after it crossed the signal. The end results, the emergency vehicles to pass through the traffic with no or minimum waiting time. In future work, need to avoid the uneven traffic flow and enhancing the safety.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2021

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    Taschenbuch. Condición: Neu. Deep Learning & IOT Based Smart Life Saving Emergency Trafficlight Control | S. Jaganathan (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786204190266 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

  • 6204190261 / 9786204190266

    Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Aug 2021, 2021

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    Librería: Books-by-Floh, Paderborn, AlemaniaBooks-by-Floh

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    Taschenbuch. Condición: Neu. Neuware -In order to reduce the traffic congestion and to improve the service speed of ambulance and fire service, many systems need to be developed. In this project, a smart and automatic emergency traffic signal system is proposed. It supports especially like highest traffic congestion especially in cities. The proposed approach gives solution for emergency services like ambulance and fire trucks, in order to avoid traffic and reach the destination in time. This proposed system architecture is based on deep learning algorithm and with support Internet-of Things (IoT) devices. The problem of ambulance and fire engine getting stuck in traffic jam increasing and nearly 20% of emergency patients death were caused by traffic jam in a year. To overcome this problem, handling of traffic and emergency situation by detecting the ambulance or fire engine about 100 meters away by blocking other ways and sets back to normal operation after it crossed the signal. The end results, the emergency vehicles to pass through the traffic with no or minimum waiting time. In future work, need to avoid the uneven traffic flow and enhancing the safety. 64 pp. Englisch.…

  • 6204190261 / 9786204190266

    Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices

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    Condición: As New. Unread book in perfect condition.

  • 6204190261 / 9786204190266

    Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK

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  • 6204190261 / 9786204190266

    Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK

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    Condición: As New. Unread book in perfect condition.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Aug 2021, 2021

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    Librería: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, AlemaniaRheinberg-Buch Andreas Meier eK

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In order to reduce the traffic congestion and to improve the service speed of ambulance and fire service, many systems need to be developed. In this project, a smart and automatic emergency traffic signal system is proposed. It supports especially like highest traffic congestion especially in cities. The proposed approach gives solution for emergency services like ambulance and fire trucks, in order to avoid traffic and reach the destination in time. This proposed system architecture is based on deep learning algorithm and with support Internet-of Things (IoT) devices. The problem of ambulance and fire engine getting stuck in traffic jam increasing and nearly 20% of emergency patients death were caused by traffic jam in a year. To overcome this problem, handling of traffic and emergency situation by detecting the ambulance or fire engine about 100 meters away by blocking other ways and sets back to normal operation after it crossed the signal. The end results, the emergency vehicles to pass through the traffic with no or minimum waiting time. In future work, need to avoid the uneven traffic flow and enhancing the safety. 64 pp. Englisch.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Aug 2021, 2021

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In order to reduce the traffic congestion and to improve the service speed of ambulance and fire service, many systems need to be developed. In this project, a smart and automatic emergency traffic signal system is proposed. It supports especially like highest traffic congestion especially in cities. The proposed approach gives solution for emergency services like ambulance and fire trucks, in order to avoid traffic and reach the destination in time. This proposed system architecture is based on deep learning algorithm and with support Internet-of Things (IoT) devices. The problem of ambulance and fire engine getting stuck in traffic jam increasing and nearly 20% of emergency patients death were caused by traffic jam in a year. To overcome this problem, handling of traffic and emergency situation by detecting the ambulance or fire engine about 100 meters away by blocking other ways and sets back to normal operation after it crossed the signal. The end results, the emergency vehicles to pass through the traffic with no or minimum waiting time. In future work, need to avoid the uneven traffic flow and enhancing the safety. 64 pp. Englisch.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2021

    6204190261 / 9786204190266

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    Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books

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    Condición: New. Print on Demand.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2021

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    Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2021

    6204190261 / 9786204190266

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    Librería: moluna, Greven, Alemaniamoluna

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    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Jaganathan S.Jaganathan S. received his M.E. in power systems engineering from Government College of Technology, Coimbatore, India, in 2004, and his Ph.D. in electrical engineering from Anna University, Chennai, India, in 2013. He is.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Aug 2021, 2021

    6204190261 / 9786204190266

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In order to reduce the traffic congestion and to improve the service speed of ambulance and fire service, many systems need to be developed. In this project, a smart and automatic emergency traffic signal system is proposed. It supports especially like highest traffic congestion especially in cities. The proposed approach gives solution for emergency services like ambulance and fire trucks, in order to avoid traffic and reach the destination in time. This proposed system architecture is based on deep learning algorithm and with support Internet-of Things (IoT) devices. The problem of ambulance and fire engine getting stuck in traffic jam increasing and nearly 20% of emergency patients death were caused by traffic jam in a year. To overcome this problem, handling of traffic and emergency situation by detecting the ambulance or fire engine about 100 meters away by blocking other ways and sets back to normal operation after it crossed the signal. The end results, the emergency vehicles to pass through the traffic with no or minimum waiting time. In future work, need to avoid the uneven traffic flow and enhancing the safety.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.…