Deep Learning & IOT Based Smart Life Saving Emergency Trafficlight Control

S. Jaganathan

ISBN 10: 6204190261 / ISBN 13: 9786204190266

Published by LAP LAMBERT Academic Publishing Aug 2021, 2021

About this Item

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.

Seller Inventory # 9786204190266

Bibliographic Details

• Title: Deep Learning & IOT Based Smart Life Saving Emergency Trafficlight Control
• Publisher: LAP LAMBERT Academic Publishing Aug 2021
• Publication Date: 2021
• Language: English
• ISBN 10: 6204190261
• ISBN 13: 9786204190266
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 5D millimeters 220 millimeters width by 150 millimeters height by 5 millimeters depth
• Weight: 113 grams

About this title

Synopsis

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.