Skip to main content
SpringerLink
Log in

Evolution in Big Data Analytics on Internet of Things: Applications and Future Plan

  • Chapter
  • First Online:
Multimedia Big Data Computing for IoT Applications

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 163))

Abstract

The term Big Data shows the large and varied set of electronic information that can be the combination of data collected from multiple sources. Reliably, we make 2.5 quintillion bytes of facts; so much that 90% of the facts on earth nowadays has been made over the trendy two years alone. Security and surety problems are widely spreading out by using velocity, volume, and mixture of colossal records, as an example, generous scale cloud systems, varying characteristics of information sources and setups, spilling nature of information acquirement and high extent among cloud movements. IoT is a great idea for everyone and also the best path for innovation age. The IoT could play a very important role and be extensively delivered with the aid of the splendid amount of heterogeneous devices that produce critically “Huge information” (Lee et al. Research on iot based cyber physical system for industrial big data analytics. IEEE, pp. 1855–1859, [1]). As we know that a number of records are being gathered today through numerous associations and these records need a large storage, so how to accommodate a large memory space is also a big question in today scenario. It ends up being computationally wasteful to dissect any such huge data. The amount of the handy crude facts has been developing an exponential scale. A standout amongst the maximum vital highlights of IoT is its ongoing or close to constant correspondence of facts approximately the “connected matters”. The four precept peculiarity of IoT is (a) Large information degree (TBs to PBs), (b) High velocity of statistics circulation, information alternate (OLTP) and facts making ready (OLAP, examination) (c) Diverse prepared and unstructured information, differing information models and inquiry dialects, diverse facts resources and veracity (Rizwan et al. Real-time smart trafficmanagement systemfor smart cities by using internet of things and big data. IEEE, pp. 1–7, [2]). Big data and IoT are widely used in many applications worldwide. Many researchers are working day night to improve the services of Big data and IoT. There are many deficiencies are present in both the technologies. And the most common is its security. Big data and IoT both requires the concern about its security. The reason behind is that, the big data and IoT applications are accessing the use of cloud widely. And in many cases, the data stored to cloud is very secret. So from the security point of view, it is necessary to take these technologies seriously. Some researchers are also working on RFID and Internet of Things, like a combine approach. RFID is also a latest technology and due to its deficiencies, RFID technology is extracting out by many vendors. In UK, big numbers of RFID cards have been deployed in many places but it failed due to lacking in security. To improve RFID security, researchers are also having a look at IOT. The question is what the outcome will be. Will the researchers get success by using this combine approach? May be yes. In this chapter, some applications are discussed and try to explain the utilization of Big data and IoT in brief. Secondly, the deficiencies are also the matter of concern in the chapter. The desired solutions to overcome the drawbacks of the Big Data and Internet of Things are also discussed. This chapter is present about the development in the subject of Big Data on Internet of things applications.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 69.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 89.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 119.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. C. Lee, C. Yeung, M. Cheng, Research on iot based cyber physical system for industrial big data analytics, in Industrial Engineering and Engineering Management (IEEM), 2015 EEE International Conference on (IEEE, 2015), pp. 1855–1859

    Google Scholar 

  2. P. Rizwan, K. Suresh, M.R. Babu, Real-time smart traffic management system for smart cities by using internet of things and big data, in Emerging Technological Trends (ICETT), International Conference on (IEEE, 2016), pp. 1–7

    Google Scholar 

  3. Q. Zhang, X. Zhang, Q. Zhang, W. Shi, H. Zhong, Firework: big data sharing and processing in collaborative edge environment, in Hot Topics in Web Systems and Technologies (HotWeb), 2016 Fourth IEEE Workshop on (IEEE, 2016), pp. 20–25

    Google Scholar 

  4. M.M. Rathore, A. Ahmad, A. Paul, Iot-based smart city development using big data analytical approach, in Automatica (ICA-ACCA), IEEE International Conference on (IEEE, 2016), pp. 1–8

    Google Scholar 

  5. B. Ahlgren, M. Hidell, E.C.-H. Ngai, Internet of things for smart cities: Interoperability and open data. IEEE Int. Comput. 20(6), 52–56 (2016)

    Article  Google Scholar 

  6. J.L. P´erez, D. Carrera, Performance characterization of the servioticy api: an iot-as-a-service data management platform, in Big Data Computing Service and Applications (BigDataService), 2015 IEEE First International Conference on (IEEE, 2015), pp. 62–71

    Google Scholar 

  7. F. Alam, R. Mehmood, I. Katib, A. Albeshri, Analysis of eight data mining algorithms for smarter internet of things (iot). Procedia Comput. Sci. 98, 437–442 (2016)

    Article  Google Scholar 

  8. H. Wang, O.L. Osen, G. Li, W. Li, H.-N. Dai, W. Zeng, Big data and industrial internet of things for the maritime industry in northwestern norway, in TENCON 2015-2015 IEEE Region 10 Conference (IEEE, 2015), pp. 1–5

    Google Scholar 

  9. O.B. Sezer, E. Dogdu, M. Ozbayoglu, A. Onal, An extended iot framework with semantics, big data, and analytics, in Big Data (Big Data), 2016 IEEE International Conference on (IEEE, 2016), pp. 1849–1856

    Google Scholar 

  10. A.J. Jara, D. Genoud, Y. Bocchi, Big data for cyber physical systems: an analysis of challenges, solutions and opportunities, in Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), 2014 Eighth International Conference on (IEEE, 2014), pp. 376–380

    Google Scholar 

  11. C. Vuppalapati, A. Ilapakurti, S. Kedari, The role of big data in creating sense ehr, an integrated approach to create next generation mobile sensor and wearable data driven electronic health record (ehr), in Big Data Computing Service and Applications (BigDataService), 2016 IEEE Second International Conference on (IEEE, 2016), pp. 293–296

    Google Scholar 

  12. Z. Ding, X. Gao, J. Xu, H. Wu, Iot-statisticdb: a general statistical database cluster mechanism for big data analysis in the internet of things, in Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing (IEEE, 2013), pp. 535–543

    Google Scholar 

  13. I.-L. Yen, G. Zhou, W. Zhu, F. Bastani, S.-Y. Hwang, A smart physical world based on service technologies, big data, and game-based crowd sourcing, in Web Services (ICWS), 2015 IEEE International Conference on (IEEE, 2015), pp. 765–772

    Google Scholar 

  14. A. Ahmad, M.M. Rathore, A. Paul, S. Rho, Defining human behaviors using big data analytics in social internet of things, in Advanced Information Networking and Applications (AINA), 2016 IEEE 30th International Conference on (IEEE, 2016), pp. 1101–1107

    Google Scholar 

  15. D. Arora, K.F. Li, A. Loffler, Big data analytics for classification of network enabled devices, in Advanced Information Networking and Applications Workshops (WAINA), 2016 30th International Conference on (IEEE, 2016), pp. 708–713

    Google Scholar 

  16. R.P. Minch, Location privacy in the era of the internet of things and big data analytics, in System Sciences (HICSS), 2015 48th Hawaii International Conference on (IEEE, 2015), pp. 1521–1530

    Google Scholar 

  17. A. Mukherjee, H.S. Paul, S. Dey, A. Banerjee, Angels for distributed analytics in iot, in Internet of Things (WF- IoT), 2014 IEEE World Forum on (IEEE, 2014), pp. 565–570

    Google Scholar 

  18. R. Ramakrishnan, L. Gaur, Smart electricity distribution in residential areas: internet of things (iot) based advanced metering infrastructure and cloud analytics, in Internet of Things and Applications (IOTA), International Conference on (IEEE, 2016), pp. 46–51

    Google Scholar 

  19. M.H. Berlian, T.E.R. Sahputra, B.J.W. Ardi, L.W. Dzatmika, A.R.A. Besari, R.W. Sudibyo, S. Sukaridhoto, Design and implementation of smart environment monitoring and analytics in real-time system framework based on internet of underwater things and big data, in Electronics Symposium (IES), 2016 International (IEEE, 2016), pp. 403–408

    Google Scholar 

  20. D. Mourtzis, E. Vlachou, N. Milas, Industrial big data as a result of iot adoption in manufacturing. Procedia CIRP 55, 290–295 (2016)

    Article  Google Scholar 

  21. B. Cheng, A. Papageorgiou, F. Cirillo, E. Kovacs, Geelytics: geo-distributed edge analytics for large scale iot systems based on dynamic topology, in Internet of Things (WF-IoT), 2015 IEEE 2nd World Forum on (IEEE, 2015), pp. 565–570

    Google Scholar 

  22. E. Ahmed, M.H. Rehmani, Introduction to the special section on social collaborative internet of things, p. 382384 (2017)

    Article  Google Scholar 

  23. M.M. Rathore, A. Ahmad, A. Paul, S. Rho, Urban planning and building smart cities based on the internet of things using big data analytics. Comput. Netw. 101, 63–80 (2016)

    Article  Google Scholar 

  24. G. Suciu, V. Suciu, A. Martian, R. Craciunescu, A. Vulpe, I. Marcu, S. Halunga, O. Fratu, Big data, internet of things and cloud convergence–an architecture for secure-health applications. J. Med. Syst. 39(11), 1–8 (2015)

    Article  Google Scholar 

  25. F. Bonomi, R. Milito, J. Zhu, S. Addepalli, Fog computing and its role in the internet of things, in Proceedings of the first edition of the MCC workshop on Mobile cloud computing (ACM, 2012), pp. 13–16

    Google Scholar 

  26. S. Tanwar, S. Tyagi, S. Kumar, The role of internet of things and smart grid for the development of a smart city, in Intelligent Communication and Computational Technologies (Lecture Notes in Networks and Systems: Proceedings of Internet of Things for Technological Development, IoT4TD 2017, Springer International Publishing, vol. 19, pp. 23–33

    Google Scholar 

  27. N. Mishra, C.C. Lin, H.T. Chang, A cognitive adopted framework for IoT big-data management and knowledge discovery prospective. Int. J. Distrib. Sens. Netw. 2015, 6 (2015)

    Article  Google Scholar 

  28. D. Slezak, P. Synak, J. Wr ´oblewski, G. Toppin, Infobright analytic database engine using rough sets and granular computing, in Granular Computing (GrC), 2010 IEEE International Conference on (IEEE, 2010), pp. 432–437

    Google Scholar 

  29. A. Mukherjee, S. Dey, H.S. Paul, B. Das, Utilizing condor for data parallel analytics in an iot contextan experience report, in Wireless and Mobile Computing, Networking and Communications (WiMob), 2013 IEEE 9th International Conference on (IEEE, 2013), pp. 325–331

    Google Scholar 

  30. A. Ahmed, E. Ahmed, A survey on mobile edge computing, in Intelligent Systems and Control (ISCO), 2016 10th International Conference on (IEEE, 2016), pp. 1–8

    Google Scholar 

  31. H.R. Arkian, A. Diyanat, A. Pourkhalili, Mist: fogbased data analytics scheme with cost-efficient resource provisioning for iot crowdsensing applications. J. Netw. Comput. Appl. 82, 152–165 (2017)

    Article  Google Scholar 

  32. H. Aly, M. Elmogy, S. Barakat, Big data on internet of things: Applications, architecture, technologies, techniques, and future directions. Int. J. Comput. Sci. Eng. (IJCSE), 4, 300–313 (2015)

    Google Scholar 

  33. I.A.T. Hashem, N.B. Anuar, A. Gani, I. Yaqoob, F. Xia, S.U. Khan, Mapreduce: review and open challenges. Scientometrics, 1–34 (2016)

    Google Scholar 

  34. F. F¨arber, S.K. Cha, J. Primsch, C. Bornh¨ovd, S. Sigg, W. Lehner, Sap hana database: data management for modern business applications. ACM Sigmod Rec. 40(4), 45–51 (2012)

    Article  Google Scholar 

  35. E. Ahmed, M.H. Rehmani, Mobile edge computing: opportunities, solutions, and challenges, pp. 59–63

    Article  Google Scholar 

  36. R. T¨ onjes, P. Barnaghi, M. Ali, A. Mileo, M. Hauswirth, F. Ganz, S. Ganea, B. Kjærgaard, D. Kuemper, S. Nechifor et al., Real time iot stream processing and large-scale data analytics for smart city applications, in Poster Session, European Conference on Networks and Communications (2014)

    Google Scholar 

  37. M. Villari, A. Celesti, M. Fazio, A. Puliafito, Alljoyn lambda: an architecture for the management of smart environments in iot, in Smart Computing Workshops (SMARTCOMP Workshops), 2014 International Conferenceon (IEEE, 2014), pp. 9–14

    Google Scholar 

  38. M.A. Hayes, M.A.M. Capretz, Contextual anomaly detection in big sensor data, in IEEE International Congress On Big Data, 2014, pp. 64–70

    Google Scholar 

  39. U. Shaukat, E. Ahmed, Z. Anwar, F. Xia, Cloudlet deployment in local wireless networks: Motivation, architectures, applications, and open challenges. J. Netw. Comput. Appl. 62, 18–40 (2016)

    Article  Google Scholar 

  40. J. Nandimath, E. Banerjee, A. Patil, P. Kakade, S. Vaidya, D. Chaturvedi, Big data analysis using apache hadoop, in Information Reuse and Integration (IRI), 2013 IEEE 14th International Conference on (IEEE, 2013), pp. 700–703

    Google Scholar 

  41. V. Morabito, Managing change for big data driven innovation, in Big Data and Analytics (Springer, 2015), pp. 125–153

    Google Scholar 

  42. S. Burke, Hp haven big data platform is gaining partner momentum, CRN [online] http://www.crncom/news/applications-os/240161649 (2013)

  43. A. Bhardwaj, S. Bhattacherjee, A. Chavan, A. Deshpande, A.J. Elmore, S. Madden, A.G. Parameswaran, Datahub: collaborative data science and dataset version management at scale, arXiv preprint arXiv:1409.0798 (2014)

  44. J. Jin, J. Gubbi, T. Luo, M. Palaniswami, Network architecture and qos issues in the internet of things for a smart city, in Communications and Information Technologies (ISCIT), 2012 International Symposium on (IEEE, 2012), pp. 956–961

    Google Scholar 

  45. 2017, Accessed on 3rd June) Hortonworks. [Online]. https://hortonworks.com/

  46. Y. Zhuang, Y. Wang, J. Shao, L. Chen, W. Lu, J. Sun, B. Wei, J. Wu, D-ocean: an unstructured data management system for data ocean environment. Front. Comput. Sci. 10(2), 353–369 (2016). http://dx.doi.org/10.1007/s11704-015-5045-6

    Article  Google Scholar 

  47. Z. Ding, Q. Yang, H. Wu, Massive heterogeneous sensor data management in the internet of things, in IEEE International Conferences On Internet Of Things, And Cyber, Physical And Social Computing, pp. 100–108 (2011)

    Google Scholar 

  48. 2017, Accessed on 3rd June) Mapr. [Online]. https://mapr.com

  49. E. Al Nuaimi, H. Al Neyadi, N. Mohamed, J. AlJaroodi, Applications of big data to smart cities. J. Int. Serv. Appl. 6(1), 1 (2015)

    Google Scholar 

  50. E. Ahmed, M. Imran, M. Guizani, A. Rayes, J. Lloret, G. Han, W. Guibene, Enabling mobile and wireless technologies for smart cities: Part 2. IEEE Commun. Mag. 55(3), 12–13 (2017)

    Article  Google Scholar 

  51. S. Tanwar, P. Patel, K. Patel, S. Tyagi, N. Kumar, M.S. Obaidat, An advanced internet of thing based security alert system for smart home, in International Conference on Computer, Information and Telecommunication Systems (IEEE CITS-2017), Dalian University, Dalian, China, 21–23 July 2017, pp. 25–29

    Google Scholar 

  52. R. Sharma, Steps for implementing big data and its security challenges, of the book titled “Data Intensive Computing Application for Big Data” to be published by Advances in Parallel Computing series of IOS PRESS (Scopus Indexed) ISSN 1879-808X, Vol. 29, February 2018

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. SRM Institute of Science and Technology, Ghaziabad, India

    Rohit Sharma, Pankaj Agarwal & Rajendra Prasad Mahapatra

Authors
  1. Rohit Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pankaj Agarwal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rajendra Prasad Mahapatra
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rohit Sharma .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India

    Sudeep Tanwar

  2. Department of Electronics and Communication Engineering, Thapar Institute of Engineering and Technology, Deemed University, Patiala, Punjab, India

    Sudhanshu Tyagi

  3. Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Deemed University, Patiala, Punjab, India

    Neeraj Kumar

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Sharma, R., Agarwal, P., Mahapatra, R.P. (2020). Evolution in Big Data Analytics on Internet of Things: Applications and Future Plan. In: Tanwar, S., Tyagi, S., Kumar, N. (eds) Multimedia Big Data Computing for IoT Applications. Intelligent Systems Reference Library, vol 163. Springer, Singapore. https://doi.org/10.1007/978-981-13-8759-3_18

Download citation

Publish with us

Policies and ethics

Search

Navigation