شناسایی و رتبه‌بندی کاربردهای تحلیل عظیم‌‌داده مبتنی بر اینترنت اشیا

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 دانشیار، گروه مدیریت فناوری اطلاعات، دانشکده مدیریت دانشگاه تهران، تهران، ایران.

2 کارشناس ارشد، گروه مدیریت فناوری اطلاعات، دانشکده مدیریت، دانشگاه تهران، تهران، ایران.

3 استادیار، گروه مدیریت فناوری اطلاعات، دانشکده مدیریت دانشگاه تهران، تهران، ایران.

چکیده

هدف: هر روز داده‌های زیادی تولید می‌شود و این داده‌ها روزبه‌روز در حال افزایش است. سهم وسایل متصل به اینترنت در تولید این داده‌ها، انکارناپذیر است. این داده‌ها در صورت تحلیل، برای سازمان‌ها و افراد جامعه، کاربردهای بسیاری خواهند داشت. با توجه به اینکه در پژوهش‌های گذشته به شناسایی و اولویت‌بندی این کاربردها پرداخته نشده است، هدف این پژوهش، شناسایی و رتبه‌بندی کاربردهای تحلیل عظیم ‌داده مبتنی بر اینترنت اشیا است.
روش: در این پژوهش، ابتدا به روش فراترکیب، کاربردهای تحلیل عظیم‌داده مبتنی بر اینترنت اشیا شناسایی شدند، سپس با استفاده از تصمیم‌گیری چندمتغیره و نظر خبرگان، کاربردهای تحلیلی شناسایی شده، رتبه‌بندی شدند. در این پژوهش برای رتبه‌بندی کاربردها از روش امکان‌سنجی TELOS، برای وزن‌دهی به معیارهای TELOS از روش تحلیل سلسله‌مراتبی (AHP) و برای رتبه‌بندی کاربردها نیز از روش تصمیم‌گیری چندمتغیره ویکور استفاده شده است.
یافته‌ها: در این پژوهش 256 زیرکاربرد شناسایی شد که در 113 کاربرد اصلی در 16 صنعت و هفت نوع کاربرد تحلیلی دسته‌بندی شدند. کاربردهای تشخیصی، در دو صنعت حمل‌ونقل و سلامت و کاربردهای نظارتی در سه صنعت سلامت، حمل‌ونقل و کشاورزی بیشترین کاربرد را به خود اختصاص داده‌اند. همچنین با اولویت‌بندی صورت‌گرفته در دو صنعت حمل‌ونقل و سلامت، در صنعت حمل‌ونقل کاربردهای پیش‌بینی و در صنعت سلامت کاربردهای خودکارسازی در اولویت قرار گرفتند.
نتیجه‌گیری: با توجه به یافته‌های پژوهش، تحلیل داده‌های اینترنت اشیا در صنایع حمل‌ونقل و سلامت، بیشترین کاربرد را دارند و با توجه به متفاوت‌بودن اولویت‌بندی این دو صنعت، توجیه‌پذیری کاربردها در دو صنعت با یکدیگر متفاوت است.

کلیدواژه‌ها


عنوان مقاله [English]

Identifying and Ranking the Application of Big Internet of Things Data Analyses

نویسندگان [English]

  • Saeed Rouhani 1
  • Hadi Sedaghat 2
  • Ayob Mohammadian 3
1 Associate Prof., Department of Information Technology Management, Faculty of Management, University of Tehran, Tehran, Iran.
2 MSc., Department of Information Technology Management, Faculty of Management, University of Tehran, Tehran, Iran.
3 Assistant Prof., Department of Information Technology Management, Faculty of Management, University of Tehran, Tehran, Iran.
چکیده [English]

Objective: As more and more data are generated day by day, the applicability of internet of things (IoT) devices becomes inevitable. The analysis of such data can have many benefits for the organizations and societies. Since previous research has not addressed the identification and prioritization of these applications, the purpose of this study is to identify and rank big IoT data analyses.
 
Methodology: This article was divided into two sections. In part 1, the researchers used the meta-synthesis method to identify the applications; and in part 2, the multivariable method was used to prioritize the applications. Moreover, TELOS feasibility (Technical, Economic, Legal, Operational, & Scheduling) and AHP were used to weight and rank the criteria. Then, the applications were ranked based on the experts’ opinions through Vikor’s method.
 
Findings: In this research, the meta-synthesis method has been used to identify the applications of big IoT data analyses. In this meta-synthesis method, 490 articles were initially identified and after eliminating conference papers, 257 articles were selected to initiate the meta-synthesis process. Finally, 51 articles were selected and as a result, 256 sub-applications were identified which were categorized into 114 main categories, 16 industries, and 7 analytic applications. It is also noteworthy that the diagnostic application within the health and transportation industries (with 102 & 100 applications, respectively), as well as the monitoring application within the health, transportation, and agriculture industries were reported to have the highest functioning. The most identified applications in industry-analysis belong to transport-diagnostic (32 applications), health-diagnostic (29 applications), health-monitoring (26 applications), agriculture-monitoring (25 applications), and transport-monitoring (20 applications). In the prioritization step, after calculating the weights based on the experts’ opinions and hierarchical analysis, the applications of transportation and health industries were ranked using TELOS feasibility as well as the experts’ ratings and the Vikor’s method. According to the experts’ opinions and TELOS feasibility criteria, the predictive applications in the transportation industry and the automation applications in the health industry have received the highest priorities.
 
Conclusion: According to the research findings, big IoT data analysis is mostly used in the transportation and health industrieswhere the predictive applications in the transportation industry and the automation applications in the health industry have been regarded as a priority. Based on these results, the two health and transportation industries and their priority applications are proposed for the companies that want to work in this area. Due to differences in prioritization of the applications in the two transportation and health industries, the justifications for the two industries are different as well.

کلیدواژه‌ها [English]

  • Big data
  • Big Data Analyses
  • Internet of Things (IoT)
  • Meta-synthesis
  • Multi-Variable Decision Making
محمدی، علی؛ شجاعی، پیام (1395). ارائه مدل جامع مؤلفه‌های مدیریت ریسک زنجیره تأمین: رویکرد فراترکیب. پژوهشنامه مدیریت اجرایی، 8(15)، 93-112.
 
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