IoT based Emergency Vehicle Communication System

Syed, Moazzam Shah Bukhari; Memon, Fahad; Memon, Saima Q.; Khan, Rahat

doi:10.1109/icisct49550.2020.9079940

Cited by 13 publications

(5 citation statements)

References 6 publications

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“…Systems such as traffic lights, signals, and others govern the direction of traffic. After all, a new traffic-controlling environment will be required as AI develops [14][15][16].…”

Section: Traffic Lightmentioning

confidence: 99%

EVATL: A novel framework for emergency vehicle communication with adaptive traffic lights for smart cities

Dodia,

Kumar,

Rani

et al. 2023

IET Smart Cities

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Fixed cycle traffic lights primarily regulate road traffic, in which traffic light control systems are for specific lanes or crossings in urban areas. Also, not being appropriately installed can prolong the congestion delay and unnecessarily long wait times for crossing intersections, which can cause emergency vehicles to become stuck at intersections. Adaptive signal timing management technique that is more computationally viable than current fixed cycle signal control systems and can improve network‐wide traffic operations by reducing traffic delay and energy consumption. Even though specific adaptive control systems exist, there is no mechanism to communicate with emergency vehicles, which is crucial for smart cities. Motivated by this problem, a novel framework, Emergency Vehicle Adaptive Traffic Light (EVATL), is proposed for smart cities where an adaptive mode of operation for traffic lights is employed with emergency vehicle communication, improving their functioning and reducing overall congestion delay. EVATL detects emergency vehicle location using GPS with the Internet of Things(IoT), which integrates with traffic signals and works adaptively according to vehicle density at the traffic signal using YOLOv8. So, the primary goal of the proposed EVATL is to prioritise an emergency vehicle while simultaneously integrating adaptive traffic signals for smart cities. A GUI is developed for evaluating the proposed model by creating different scenarios for an adaptive traffic light and emergency vehicle communication. While analysing the simulation results of the proposed model EVATL, a clear improvement can be seen in the wait time of vehicles at a traffic light with the timely detection of an emergency vehicle at a set distance.

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“…Systems such as traffic lights, signals, and others govern the direction of traffic. After all, a new traffic-controlling environment will be required as AI develops [14][15][16].…”

Section: Traffic Lightmentioning

confidence: 99%

EVATL: A novel framework for emergency vehicle communication with adaptive traffic lights for smart cities

Dodia,

Kumar,

Rani

et al. 2023

IET Smart Cities

View full text Add to dashboard Cite

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“…In [35], a system based on V2V and V2I communication is developed to help emergency vehicles select the best routes to reach their intended destination. The best route is calculated before the emergency vehicle starts its route.…”

Section: Related Workmentioning

confidence: 99%

Mobility Sensing and V2X Communication for Emergency Services

et al. 2022

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Palavras-chavevanet, mobilidade veículos de emergência, sensorização em tempo real ResumoAo longo dos anos, a população mundial que vive em cidades tem vindo a crescer, levantando vários problemas de gestão de mobilidade. Os tempos de viagem, o número de acidentes e a poluição gerada têm vindo a aumentar. Com a evolução das smart cities, do desenvolvimento de sensores, da comunicação IoT e veicular, torna-se possível o processamento de dados em tempo real, assim como a comunicação entre veículos que permite não apenas o melhoramento da mobilidade nas cidades, mas também da segurança nas estradas. Esta dissertação propõe um sistema que recolhe, processa e dissemina dados em tempo real dentro de uma rede veicular, integrando dados de diferentes sensores relacionados com a mobilidade, e desenvolvendo um serviço de disseminação para o alerta de emergências, tendo como foco contribuir para a redução do tempo de resposta de veículos de emergência. Com o auxílio de RADARs e de mensagens enviadas por veículos, que são recolhidos e processados em tempo real, é possível obter informações sobre o congestionamento das vias, permitindo a geração de alertas de trânsito e alertas de emergência que serão disseminados por veículos e outros nós de uma smart city, mais particularmente no aviso de aproximação de veículos de emergência. Os sistemas desenvolvidos foram testados em laboratório e num cenário real de cidade, utilizando uma infraestrutura já implementada (Aveiro Tech City Living Lab) na cidade de Aveiro, Portugal. Com esta abordagem, os resultados obtidos demonstram a possibilidade de transmissão de informações em tempo real entre veículos e unidades rodoviárias para envio de avisos sobre a aproximação de veículos de emergência. Comparando os modos de comunicação infraestrutura-para-veículo, veículo-para-veículo, ou uma abordagem híbrida em que ambas as comunicações são simultaneamente usadas, houve uma redução de um máximo de 80% para 20% de perdas de comunicação na disseminação de avisos, quando a solução hibrida é utilizada.

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“…The WSN must continuously track the equipment and medicines to help clinical staff, doctors and nurses to quickly and immediately find them in real-time [ 60 ]. One of the applications is generating the network of ambulances using IoT based WSN systems to effectively respond in emergency situations [ 61 , 62 , 63 ]. This WSN should be deployed to cover the whole of the smart city so that when an accident occurs in every place of the city, emergency medical services could be offered at the right time.…”

Section: Literature Reviewmentioning

confidence: 99%

Performance Analysis of IoT-Based Health and Environment WSN Deployment

Shakeri

Sadeghi‐Niaraki

Choi

et al. 2020

Sensors

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With the development of Internet of Things (IoT) applications, applying the potential and benefits of IoT technology in the health and environment services is increasing to improve the service quality using sensors and devices. This paper aims to apply GIS-based optimization algorithms for optimizing IoT-based network deployment through the use of wireless sensor networks (WSNs) and smart connected sensors for environmental and health applications. First, the WSN deployment research studies in health and environment applications are reviewed including fire monitoring, precise agriculture, telemonitoring, smart home, and hospital. Second, the WSN deployment process is modeled to optimize two conflict objectives, coverage and lifetime, by applying Minimum Spanning Tree (MST) routing protocol with minimum total network lengths. Third, the performance of the Bees Algorithm (BA) and Particle Swarm Optimization (PSO) algorithms are compared for the evaluation of GIS-based WSN deployment in health and environment applications. The algorithms were compared using convergence rate, constancy repeatability, and modeling complexity criteria. The results showed that the PSO algorithm converged to higher values of objective functions gradually while BA found better fitness values and was faster in the first iterations. The levels of stability and repeatability were high with 0.0150 of standard deviation for PSO and 0.0375 for BA. The PSO also had lower complexity than BA. Therefore, the PSO algorithm obtained better performance for IoT-based sensor network deployment.

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IoT based Emergency Vehicle Communication System

Cited by 13 publications

References 6 publications

EVATL: A novel framework for emergency vehicle communication with adaptive traffic lights for smart cities

EVATL: A novel framework for emergency vehicle communication with adaptive traffic lights for smart cities

Mobility Sensing and V2X Communication for Emergency Services

Performance Analysis of IoT-Based Health and Environment WSN Deployment

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