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

Document Type : Research Paper


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.


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.


Abdel Hafez, H. (2017). Big Data in Smart Cities: Analysis and Applications in Arab World. Egyptian Computer Science Journal, 41(1), 38-52.
Adi, E., Anwar, A., Baig, Z., Zeadally, S. (2020). Machine learning and data analytics for the IoT. Neural Computing and Applications, 32(10), 16205–16233.
Ahmed, E., Yaqoob, I., Targio Hashem, I. A., Khan, I., Abdalla Ahmed, A. I., Imran, M., & Vasilakos, A. V. (2017). The Role of big data analytics in internet of things. Computer Networks, 129(2), 459-471.
Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, 54(15), 2787-2805.
Baber, M., & Arif, F. (2018). Real-time data processing scheme using big data analytics in internet of things based smart transportation environment. Journal of Ambient Intelligence and Humanized Computing, 10, 4167–4177.
Bessis, N., & Dobre, C. (2014). Big Data And Internet of things: A Roadmap For Smart Environments. Switzerland: Springer.
Cecchinel, C., Jimenez, M., Mosser, S., & Riveill, M. (2014). An Architecture to Support the Collection of Big Data in the Internet of Things. IEEE Computer Society, Anchorage. DOI: 10.1109/SERVICES.2014.83.
Díaz, R., González, D., & Muñoz, L. (2017). Business model analysis of public services operating in the smart city ecosystem: The case of SmartSantander. Future Generation Computer Systems, 7, 198-214.
Elias Bibri, S. (2017). The IoT for smart sustainable cities of the future: An analytical framework for sensor-based big data applications for environmental sustainability. Sustainable Cities and Society, 38, 230-253.
Elijah, O., Rahman, T., Orikumhi,, I., Leow, C., & Hindia, M. (2018). An Overview of Internet of Things (IoT) and Data Analytics in Agriculture: Benefits and Challenges. IEEE Internet of Things Journal, 5(5), 3758 - 3773.
Farahani, B., Firouzi, F., Chang, V., Badaroglu, M., Constant, N., & Mankodiya, K. (2018). Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare. Future Generation Computer Systems, 78(2), 659-676.
Firouzi, F., Rahmani, A., Mankodiya, K., Badaroglu, M., Merrett, G., Wong, P., & Farahani, B. (2017). Internet of Things and big data for smarter healthcare: From device to architecture, applications and analytics. Future Generation Computer Systems, 78(2), 583-586.
Ge, M., Bangui, H., & Buhnova, B. (2018). Big Data for Internet of Things: A Survey. Future Generation Computer Systems, 87, 601-614.
Grovar, P., & Kar, A. K. (2017). Big Data Analytics: A Review on Theoretical Contributions and Tools Used in Literature. Global Journal of Flexible Systems Management, 18(3), 203–229.
Hashem, I., Ahmed, E., Chang, V., Adewole, K., Yaqoob, I., Gani, A., & Chiroma, H. (2016). The role of big data in smart city. International Journal of information management, 36(5), 748-758.
Hassan, Q., Khan, A. R., & Madani, S. (2018). Internet of Things, Challenges, Advances, and Applications. Boca Raton: CRS Press.
Hopkins, J., & Hawking, P. (2018). Big Data Analytics and IoT in logistics: a case study. International Journal of Logistics Management, 29(2), 575-591.
Hurwitz, J., Nugent, A., Halper, F., & Kaufman, M. (2103). Big Data for Dummies. New Jersey: John Wiley & Sons.
Hussain, F. (2017). Internet of Things Building Blocks and Business Models. Switzerland: Springer.
Iqbal, M., Mehmood, M., Jabbar, S., Khalid, S., Ahmad, A., & Jeon, G. (2018). An enhanced framework for multimedia data: Green transmission and portrayal for smart traffic system. Computers and Electrical Engineering, 67, 291-308.
Iqbala, R., Doctorb, F., Moreb, B., Mahmudb, S., & Yousufb, U. (2018). Big data analytics: Computational intelligence techniques and application areas. Technological Forecasting & Social Change, 153, 119253.
Jeong, H., Park, B., Park, M., Kim, K., & Choi, k. (2017). Big data and rule-based recommendation system in Internet of Things. Cluster Computing, 22(3), 1837-1846.
Kamel Boulos, M., & Al-Shorbaji, N. (2014). On the Internet of Things, smart cities and the WHO Healthy Cities. International Journal of Health Geographics, 13(1).
Kamilaris, A., Kartakoullis, A., & Prenafeta-Boldú, F. (2017). A review on the practice of big data analysis in agriculture. Computers and Electronics in Agriculture, 143, 23-37.
Kannimuthu, S., Somesh, C., Mahendhiran, P., Bhanu, D., & Bhuvaneshwari, K. (2016). Certain investigation on significance of Internet of Things (IoT) and Big Data in vehicle tracking system. Indian Journal of Science and Technology, 9(39).
Kundhavai, K.R. & Sridevi, S. (2016). IoT and Big Data- The Current and Future Technologies: A Review. International Journal of Computer Science and Mobile Computing, 5(1), 10-14.
Leung, R. (2018). Smart hospitality: Taiwan hotel stakeholder perspectives. Tourism Review, 74(1), 50-62.
Lomotey, R., Pry, J., & Sriramoju, S. (2017). Wearable IoT data stream traceability in a distributed health information system. Pervasive and Mobile Computing, 40, 692-707.
Marjani, M., Nasaruddin, F., Gani, A., Karim, A., Tardio Hashem, I., Siddiqa, A., & Yaqoob, I. (2017). Big IoT Data Analytics: Architecture, Opportunities, and Open Research Challenges. IEEE Access, 5, 5247-5261.
Mazon, O., Bertha, Hernández, R., Dixys, M.-S., José, Pan, & Alberto. (2018). Rules engine and complex event processor in the context of internet of things for precision agriculture. Computers and Electronics in Agriculture, 154(2), 347-360.
Mohammadi, A., Shojaei, P. (2016). Proposal for a comprehensive model of supply chain risk management: Meta-synthesis Approach. Journal of Executive Management, 8(15), 93-112. (in Persian)
Mohammadi, M., Al-Fuqaha, A. S., & Guizani, M. (2017). Deep Learning for IoT Big Data and Streaming Analytics: A Survey. IEEE Communications Surveys and Tutorials, 20(4), 2923-2960.
Ohlhorst, F. (2013). Big Data Analytics, Turning Big Data into Big Money. New Jersey: John Wiley & Sons.
Paulraj, G., Francis, S., Peter, J., & Jebadurai, I. (2018). Resource-aware virtual machine migration in IoT cloud. Future Generation Computer Systems, 85, 173-183.
Rathore, M., Ahmad, A., Paul, A., & Rho, S. (2015). Urban planning and building smart cities based on the Internet of Things using Big Data analytics. Computer Networks, 101, 63-80.
Rathore, M., Paul, A., Hong, W., Seo, H., Awan, I., & Saeed, S. (2018). Exploiting IoT and big data analytics: Defining Smart Digital City using real-time urban data. Sustainable Cities and Society journal, 40, 600-610.
Rehman, M., Yaqoob, I., Salah, K,. Imran, M., Jayaraman, P., Pereea, Ch. (2019). The role of big data analytics in industrial Internet of Things. Future Generation Computer Systems, 99, 247-259.
Riggins, F., & Wamba, S. (2015). Research Directions on the Adoption, Usage and Impact of the Internet of Things through the Use of Big Data Analytics. 48th Hawaii International Conference on System Sciences, 1531-1540.
Saggi, M. K., & Jain, S. (2018). A survey towards an integration of big data analytics to big insights for value-creation. Information Processing and Management, 54(5), 758-790.
Saleem, T., & Chishti, M. (2019). Data Analytics in the Internet of Things: A Aurvey. Scalable Computing: Practice and Experience, 20(4), 607-629.
Siow, E., Tiropanis, T., & Hall, W. (2018). Analytics for the Internet of Things: A Survey. ACM Computing Surveys (CSUR), 51(4).
Sunhare, P., Chowdhary, R., Chattopadhyay, M. (2020). Journal of King Saud University - Computer and Informaion Sciences, 32(6).
Zhang, J., Wang, F., Wang, K., Lin, W., Xu, X., Chen, C. (2012). Data-driven intelligent transportation systems. A survey. IEEE Transactions on Intelligent Transportation Systems, 12(4), 1624-1639.