مشخصات مقاله | |
ترجمه عنوان مقاله | سیستم نظارت بر رانندگان مبتنی بر فازی (FDMS): پیاده سازی دو FDMS هوشمند و یک بستر آزمایش برای رانندگی ایمن در شبکه ادهاک وسایل نقلیه |
عنوان انگلیسی مقاله | Fuzzy-based Driver Monitoring System (FDMS): Implementation of two intelligent FDMSs and a testbed for safe driving in VANETs |
انتشار | مقاله سال 2020 |
تعداد صفحات مقاله انگلیسی | 10 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس نمیباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
7.007 در سال 2019 |
شاخص H_index | 93 در سال 2020 |
شاخص SJR | 0.835 در سال 2019 |
شناسه ISSN | 0167-739X |
شاخص Quartile (چارک) | Q1 در سال 2019 |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | ندارد |
رفرنس | دارد |
رشته های مرتبط | کامپیوتر، مهندسی فناوری اطلاعات |
گرایش های مرتبط | محاسبات ابری، هوش مصنوعی، مهندسی نرم افزار، سامانه های شبکه ای، اینترنت و شبکه های گسترده، مدیریت سیستم های اطلاعات |
نوع ارائه مقاله |
ژورنال |
مجله | نسل آینده سیستم های کامپیوتری – Future Generation Computer Systems |
دانشگاه | Graduate School of Engineering, Fukuoka Institute of Technology (FIT), 3-30-1 Wajiro-higashi, Higashi-ku, Fukuoka, 811-0295, Japan |
کلمات کلیدی | شبکه ادهاک وسایل نقلیه، اینترنت اشیا، محاسبات مه، محاسبات لبه، منطق فازی، سیستم مدیریت اسناد |
کلمات کلیدی انگلیسی | VANETs، IoT، Fog computing، Edge computing، Fuzzy logic، DMS |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.future.2019.12.030 |
کد محصول | E14341 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract
1- Introduction 2- Background overview and related work 3- Proposed systems 4- Proposed system evaluation 5- Conclusions References |
بخشی از متن مقاله: |
Abstract Vehicular Ad hoc Networks (VANETs) have gained a great attention due to the rapid development of mobile Internet and Internet of Things (IoT) applications. On the other hand, the competition in the automotive industry has turned into an unprecedented race to who will be the first to provide the fully autonomous cars. However, the fully autonomous driving is still a bit far from deployment, and for now, they are providing automation only at a certain level and, at the same time, are offering connected services through their mobility service platforms. With Fog and Edge computing integrated in VANETs, these mobility platforms will be standardized to provide services for every car on the road, which will help VANETs to accomplish one of its main goals, the road safety. In this paper, we propose an intelligent Fuzzy-based Driver Monitoring System (FDMS) for safe driving. We present and compare two fuzzy-based systems: FDMS1 and FDMS2. To make a decision, FDMS1 considers Vehicle’s Environment Temperature (VET), Noise Level (NL) and Heart Rate (HR). While, for FDMS2, we consider Respiratory Rate (RR) as a new parameter to decide Driver’s Situational Awareness (DSA). We evaluate the ability of the driver to safely operate the vehicle by monitoring his condition and subsequently, based on the system output, a smart box informs the driver and provides assistance. We show through simulations and experiments the effect of the considered parameters on the determination of the driver’s situation and demonstrate the actions that can be performed accordingly. Introduction Every year the lives of approximately 1.35 million people are cut short as a result of a road traffic accident. Between 20 and 50 million more people suffer non-fatal injuries, with many incurring a disability as a result of their injury [1]. For years, in order to improve the road safety, many governments have undertaken initiatives by launching Intelligent Transport Systems (ITSs). ITS is a new road and traffic system which combines state-of-the-art information, communication, and control technologies to properly create an information network based on people, vehicles and roads. As a key part of ITS, the Vehicular Ad hoc Networks (VANETs) not only aim to help reducing the traffic accidents but also to enhance the traffic efficiency and the travel comfort of passengers and drivers. In VANETs, vehicles have networking capabilities and they send/receive valuable information such as safety warnings and traffic information to/from adjacent vehicles and roadside units (RSUs) via vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) communication. |