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IoT and Data Analytics Assignment: A Literature Review

Question

Task:Choose one of the topics given below and submit a research project, which should not exceed 4000 words. The help file is available in the Student Resources Folder on Interact2.

Topics to select from but not limited to:

  • IoT for Sustainability
  • IoT devices and Next Generation Manufacturing
  • IoT Revenue Model challenges
  • IoT in Automobile Industry
  • IoT Mining Industry
  • RFID Tags
  • IoT for Independent Living of the Older Generation
  • IoT for Reducing Food Wastage in Australia
  • IoT in Finance Industry and Security Challenges
  • IoT and Data Analytics

Do the Research: Literature Review

  • Review of Literature based on past and current work in your topic (download from conference proceedings, journal articles - use Primo search to access more articles and journals - Minimum 10 journals or articles)
  • Structure in chronological order and start summarising.
  • Based on the literature, list the requirements for your Project, then choose one or more requirements to work with.
  • Now you can modify your Problem Statement based on the requirements chosen for your project.
  • Write the current and past techniques or technologies used to solve your problem, the requirements and Literature Review.

Answer

I. Literature Review
Literature review in this data analytics assignment is one of the most prominent approach to identify the knowledge that is available over a topic. Hence, the discussed review is based on the identification of the knowledge available over the IoT and Data Analytics. IoT abbreviation for Internet of Things is one of the most disruptive technology that enables sharing of data between the connected devices and with the users (Bashir & Gill, 2016). On the contrary, data analytics refers to technology that is used for processing of the data and in the process convert it to information in this data analytics assignment.

The technologies in discussion have established themselves as one of the most prominent technologies because of the business and individual advancement it offers to the users. The data analytics tools are mostly equipped by the business organisations or those entities, which are dealing with a large scale of data (Hwang & Chen, 2017). The capabilities of the data analytics offers identification of patterns and strays from a set of data that can be used for decision making and other opportunities. Different sets of data can also be used for identification of patterns, and facts. The non-profit organisations or the governing entities are also making the use of data analytics capabilities to identify the patterns, gain information, and accordingly prepare their strategies and plans (Rathore et al., 2016). The data analytics are useful for NGOs abbreviation for Non-Government organisations or government organisation as they can process a very large data size in a very short time and with great efficiency and effectives (Ahmed et al., 2017). The plans and programs are then use for the benefits of the society and its survivors. Hence, as a summary it can be stated that the data analytics offers its services not only to business organisations but also plays a viable role in assisting the society.

IoT is also one of the most disruptive technologies that is offering its services to an individual as well as the organisation. The IoT offers capability of interconnectivity that enables the users and the network connected devices to share the data among each other (Bashir & Gill, 2016). The sharing of data among the devices provides the devices with a limited capability of automation. Based on the programming and the outputs received from the sensors, the devices can make the decisions that can enhance their performance and at the same instance keep, them safe (Sun et al., 2016). The internet of things can be developed using the LAN or WAN. The LAN network can enable the inter connecting between the devices in a specific area whereas, the WAN can offer a very broad geographical domain (Riggins & Wamba, 2015). The technology in discussion can play a major role in the organisations. It can offer ease of work, monitoring assistance, automation and several other benefits, which add values to the organisational productivity (Bonomi et al., 2014). Hence, it would be justified to state that the interconnectivity, ease of work, convenience, adding to the productivity and several other aspects adds to an individual’s performance and eventually benefits the society as a whole.

II. Requirement for the project
Hence, as a summary of the discussion above in this data analytics assignment would be justified to state that the IoT and the data analytics are capable of offering great services to the organisation and the society. However, they also expose the society and the organisation to a grave danger. The threats of data compromising are not the only threat that affects the society and the organisations but other threats are also associated. However, the data compromising is the threat common to both the technology and is also the most prominent; hence, has been taken into account.

III. Amendments
The purpose of the data analytics assignment can be amended based on the findings from the literature review and hence, the new purpose would be to assess the the impact of IoT and Big Data Analytics in our society as well as in our business organization in context with the advantages and potential threats.

The problem statement of the assignment on data analytics can also be modified to state that the primary concern with the use of the technologies in discussion is whether IoT and Data Analytics are being used for the obtaining the desired results or are the technologies compromising the results and eventually impacting the organisation and the society.

IV. Techniques used for solving the problem
The use of the secondary data and case studies can be used to resolve the problem that has been discussed in the section above of this assignment on data analytics. The findings from the secondary sources and the case studies can be analysed and summarised to conclude on the purpose of the assignment on data analytics. The analysis of the assignment on data analytics needs to be done in context with the ground theory approach that uses the critical thinking and the patterns that have been identified to conclude on the findings. The selection of the aforementioned approach have been done because of the ease and vast size of data it can offer. The extended data size adds validity to the reliability of the findings and is one of the primary aspects that needs to be taken in consideration. Data analytics assignment assignments are being prepared by our IT assignment help experts from top universities which let us to provide you a reliable university assignment help service.

V. Reference
Ahmed, E., Yaqoob, I., Hashem, I. A. T., Khan, I., Ahmed, A. I. A., Imran, M., & Vasilakos, A. V. (2017). The role of big data analytics in Internet of Things. Computer Networks, 129, 459-471.

Bashir, M. R., & Gill, A. Q. (2016, December). Towards an IoT big data analytics framework: smart buildings systems. In 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS) (pp. 1325-1332). IEEE.

Bashir, M. R., & Gill, A. Q. (2016, December). Towards an IoT big data analytics framework: smart buildings systems. In 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS) (pp. 1325-1332). IEEE.

Bonomi, F., Milito, R., Natarajan, P., & Zhu, J. (2014). Fog computing: A platform for internet of things and analytics. In Big data and internet of things: A roadmap for smart environments (pp. 169-186). Springer, Cham.

Hwang, K., & Chen, M. (2017). Big-data analytics for cloud, IoT and cognitive computing. John Wiley & Sons.

Marjani, M., Nasaruddin, F., Gani, A., Karim, A., Hashem, I. A. T., Siddiqa, A., & Yaqoob, I. (2017). Big IoT data analytics: architecture, opportunities, and open research challenges. IEEE Access, 5, 5247-5261.

Mohammadi, M., Al-Fuqaha, A., Sorour, S., & Guizani, M. (2018). Deep learning for IoT big data and streaming analytics: A survey. IEEE Communications Surveys & Tutorials, 20(4), 2923-2960.

Rathore, M. M., Ahmad, A., Paul, A., & Rho, S. (2016). Urban planning and building smart cities based on the internet of things using big data analytics. Computer Networks, 101, 63-80.

Riggins, F. J., & Wamba, S. F. (2015, January). Research directions on the adoption, usage, and impact of the internet of things through the use of big data analytics. In 2015 48th Hawaii International Conference on System Sciences (pp. 1531-1540). IEEE.

Strohbach, M., Ziekow, H., Gazis, V., & Akiva, N. (2015). Towards a big data analytics framework for IoT and smart city applications. In Modeling and processing for next-generation big-data technologies (pp. 257-282). Springer, Cham.

Sun, Y., Song, H., Jara, A. J., & Bie, R. (2016). Internet of things and big data analytics for smart and connected communities. IEEE access, 4, 766-773.

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