دانلود مقاله بررسی داده کاوی و آنالیز کلان داده در اینترنت اشیا
چکیده
مقدمه
داده کاوی و کلان داده در اینترنت اشیا
روش تحقیق
دسته بندی و تحلیل مقاله
نتایج و بحث
نتیجه گیری
منابع
Abstract
Introduction
Data mining and big data in IoT
Research methodology
Article categories and analysis
Results and discussion
Conclusion
References
چکیده
اینترنت اشیا (IoT) یک الگوی نوظهور است که فرصت های قابل توجهی برای داده کاوی و تجزیه و تحلیل ارائه می دهد. اینترنت اشیا دنیایی را متصور است که در آن همه گوشی های هوشمند، وسایل نقلیه، امکانات خدمات عمومی و لوازم خانگی که می توانند به اینترنت متصل شوند به عنوان منابع داده عمل می کنند. حتی امروزه، بخش قابل توجهی از دستگاه‌های الکترونیکی، از جمله ساعت‌ها، هشدارهای اضطراری، درهای پارکینگ و بسیاری از لوازم خانگی را می‌توان به سیستم‌های اینترنت اشیا متصل کرد و از راه دور کنترل کرد. روش های تجزیه و تحلیل کلان داده و داده کاوی را می توان برای بهبود عملکرد سیستم های اینترنت اشیا و رفع چالش های آنها در زمینه ذخیره سازی، پردازش و تجزیه و تحلیل داده ها مورد استفاده قرار داد. مطالعات گسترده بر روی اینترنت اشیا با داده های بزرگ می تواند جمع آوری داده های عظیم و تبدیل آن به دانش ارزشمند با استفاده از تکنیک های داده کاوی را ممکن سازد. با این پیشینه، این مقاله یک بررسی سیستماتیک از ادبیات استفاده از تجزیه و تحلیل داده های بزرگ و روش های داده کاوی در اینترنت اشیا ارائه می دهد. هدف این بررسی شناسایی خطوط تحقیقی است که باید در کارهای آینده مورد توجه بیشتری قرار گیرند. برای دستیابی به این هدف، مقالات منتشر شده بین سال های 2010 تا 2021 با موضوعات داده کاوی مبتنی بر اینترنت اشیا و داده کاوی مبتنی بر اینترنت اشیا (60 مقاله) بررسی شده است. این مقالات از نظر تمرکز در چهار دسته کلی قرار می گیرند: معماری/پلتفرم، چارچوب، برنامه ها و امنیت. این مقاله خلاصه‌ای از روش‌های مورد استفاده در تجزیه و تحلیل داده‌های بزرگ مبتنی بر اینترنت اشیا و داده‌کاوی مبتنی بر اینترنت اشیا را در این چهار دسته ارائه می‌کند تا راه‌های امیدوارکننده پژوهش را برای کارهای آینده برجسته کند.
توجه! این متن ترجمه ماشینی بوده و توسط مترجمین ای ترجمه، ترجمه نشده است.
Abstract
The Internet of Things (IoT) is an emerging paradigm that offers remarkable opportunities for data mining and analysis. IoT envisions a world where all smartphones, vehicles, public services facilities, and home appliances that can be connected to the internet act as data sources. Even today, a significant portion of electronic devices, including watches, emergency alarms, parking doors, and many appliances can be linked to IoT systems and remotely controlled. Big data analysis and data mining methods can be utilized to improve the performance of IoT systems and address their challenges in the area of data storage, processing, and analysis. Extensive studies on IoT with big data can make it possible to accumulate tremendous data and transform it into valuable knowledge using data mining techniques. With this background, this paper provides a systematic survey of the literature on the use of big data analytics and data mining methods in IoT. This review aims to identify the lines of research that should receive more attention in future works. To achieve this goal, the articles published between 2010 and 2021 on the subjects of IoT-based big data and IoT-based data mining (60 articles) have been reviewed. These articles fall into four general categories in terms of focus: architecture/platform, framework, applications, and security. The paper provides a summary of the methods used in IoT-based big data analysis and IoT-based data mining in these four categories to highlight the promising avenues of research for future works.
Introduction
The ascendance of the Internet and computers has marked the beginning of a new era, where a progressively increasing number of people engage in information exchange over the Internet using personal computers, laptops, tablets, cell phones, and other data transmission and reception gadgets [1]. In recent years, this trend has stimulated the growth of a technology known as the Internet of Things (IoT) [1, 2], which is based on the idea that any object on earth can be identifed, controlled, and monitored via the Internet [3]. IoT was frst introduced by Kevin Ashton in 1999 when he observed the breadth of communication and information exchange between devices. IoT-based systems can detect objects that are connected to the Internet and provide a platform for a variety of communications and data sharing using information technology. Figure 1 illustrates the concept of IoT, which is envisioned as having a sensor on anything that has an Internet connection.
Conclusion
While today’s world is called the world of big data, the popularization of IoT technologies is expected to cause an even greater explosion of data in future. The huge network of IoT devices generates a new type of data known as the IoT big data. Only big data-based frameworks can hope to control this huge amount of diverse data. The existing big data frameworks can efectively collect and store sensor data so that they can be analyzed with data mining methods. The biggest challenge in today’s data mining world comes with several issues like security, privacy, management, data storage, and processing limitations such as real-time/streaming data. However, data analysis is a challenging task requiring the profcient use of IoT and big data analytics tools to reveal hidden patterns, trends, and correlations, a process that helps us better understand the data and use them for smart decision making. Basically, in IoT analytics, big data is the fuel and data miner are the brain of the operation. In this paper, the literature on big data in IoT and data mining in IoT was reviewed. The selected articles were divided into four categories based on their focus: architecture/ platform, framework, applications, and security. Most of the reviewed articles were focused on architecture/platform, and the Kyungpook National University of South Korea was found to have the greatest contribution to the examined literature. The countries with the highest number of articles in this feld were found to be South Korea, China, India, and the United States in that order.