The foremost determination of the paper is to focus on different aspects of IoT and Data Analytics. The report will be having numerous sections, each sections having its own significance. Problem statement will be presented in the report briefly along with that the report will be having an annotated bibliography unit stating the opinion of each of the researchers.
The application of the use of Big Data Analytics and IoT has been increasing tangentially over the last years as the benefits provided by these technologies are very much essential for the growth of business organizations. The use of IoT based devices is also very much beneficial for our society as it helps in enhancing our quality of life. There are different types of IoT based technologies which are used in our daily life such as the smart thermostats, mimo monitor, Philips hue bulbs, smart phones, smart cars microchips and Ralph Lauren Polotech Shirt and vending machines. The use of IoT devices such as Amazon Alexa, Google home, Apple smartwatches, internet connected baby monitors and video doorbells are increasing every day. The experience of the consumers is very much essential before the installation procedure of IoT.
The application of the big data analytics is also increasing both in our society as well as in the business organization as is helps in filtering the structured data from the unstructured data. The business records of the organizations are very much important for the progress and the growth of the firm which can be maintained using the concepts of data analytics. The application of the use of big data analytics are improving every day as its enhanced modules are being used in both the business to business application as well in the business to consumer applications. The big data analysis can be categorized into two sections such as the exploratory data analysis and the confirmatory data analysis.
The prime resolution of this paper is to discuss the impact of IoT and Big Data Analytics in our society as well as in our business organization. The following unit of the paper will be important to understand the format of the report.
The report will be having numerous segments the abstract will be stating about the structure of the report. The report introduces with the purpose if the report is to focus on the impact of the big data analytics and IoT. The succeeding unit of the paper will be stated about the changes of the discussed technologies in the problem statement. The report will be concluding with annotated bibliography stating the opinion of each of the researchers discussing different aspects of the Big Data Analytics and IoT.
The use of the big data analytics and the IoT based technologies have few challenges such as the alignment with the expectation of the consumers and the security concerns of the IoT enabled devices which have to be considered in the first place so that the desired results are obtained with the use of these technologies.
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.
According to this resource the business organizations who are using the concepts of Big Data Analytics and IoT in their working environment must be understanding the architecture of the system and the opportunities provided by the technologies in order to get the desired results. The paper helps in understanding how the cloud based technologies are associated with Big Data Analytics as it helps in maintaining the integrity of the data. The paper also suggests the use of analytical tools to analyse the outcome of the use of these technologies. Thus the paper helps in understand how IoT and Big Data Analysis helps in maintaining data integrity.
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.
The resource states that the deep learning and the ordered learning algorithm of IoT as well as Big Data Analytics are very much significant to deal with the neutral networks. The paper discusses the comparison between deep learning and machine learning techniques. The intelligent decision making is done using deep learning techniques. The management of the sensory data can be done using machine learning techniques. The potential challenges of the machine learning techniques for IoT were discussed in details in this paper. Thus, the concepts of deep learning were understood from this paper.
Hwang, K., & Chen, M. (2017). Big-data analytics for cloud, IoT and cognitive computing. John Wiley & Sons.
According to this resource, big data analytics are used in most of the business organizations for managing the networks, storing the data and organizational servers. The paper suggests that big data analysis can be very much beneficial for the business organization to achieve the mission and vision of the organization. The difference between cloud based technologies and big data analytics has be differentiated in this paper. Concepts of cognitive computing using the computerized models has been also stated in the paper. The paper also discusses the self-learning algorithms and the application of cognitive computing in the data mining techniques. Thus the paper is very much useful to comprehend the implementation of big data analytics in cloud computing and cognitive computing.
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.
The paper highlights the significance of the application of the IoT big data analytics in smart buildings. The paper provides different types of case studies stating the reputation of Internet of things in smart buildings. The paper helps in understanding the IoT Big Data Analysis framework for the storing and analysis of the data. The velocity challenge of the real time data can be understood from the paper as well. The use of real time data management can be done successfully using data analytics. The paper also discusses the constraints of big data analysis in business organizations as well.
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.
The paper suggests and identifies the use of the IoT in smart city. The paper suggest the application of the IoT based sensors as it helps in the dealing with issues such as heating of the automated systems, ventilation of the smart buildings, air conditioning, lighting, security and other systems. The paper also highlights the concepts of building management system. The paper suggests that the use of IoT based technologies can be very much beneficial for the business organizations for improving the operational efficiency of the automated systems. Thus, the paper helps in understanding the application of IoT in smart cities.
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.
According to this paper, internet of things are increasingly used in smart cities. The paper emphases on the improved standard of living of the citizens with the use of the different categories of technologies like the IoT and big data analytics. The paper also successfully highlights the procedure to conduct urban planning using IoT based data analytics. Community services provided by the IoT based technologies in terms of the use of wearable technologies and smart televisions which are used in the smart cities has been discussed briefly in this paper. Thus the paper helps in understanding the application of IoT based data analysis in smart cities and urban planning.
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.
The paper suggests the application of the internet of things and big data analytics in the smart cities and the connected communities. The paper describes the networking concepts of the connected devices, According to this paper sustainable development of the smart cities is also possible with the application of the big data analytics and IoT. The paper describes the different aspects of smart and connected community such as the liveability, preservation, revitalization and sustainability. The use of the different smart appliance such as accelerometer, IoT based sensors, GPS, gyrator, compass, smart meters, smart speakers, commercial security systems and IoT devices. Thus the paper helps in understanding concepts of use of the IoT devices in smart and connected communities.
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.
According to this paper, fog computing can be very much significant for smart cities. The computation of the data along with its storage facilities and communication facilities can be entirely managed using fog computing. The fog networking consists of a control plane and data plane, these planes are very much important for the computations services offered from the IoT based systems. The local resources pooling are done in a more efficient way using fog computing. The concepts of edge computing and fog computing are mentioned in the paper with primary importance. The paper determines the improved efficiency of the data which are circulated between the business organizations. Thus this paper explains the use of fog computing in the IoT smart cities.
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.
According to this paper, the application of big data analytics is very much important for the business organizations to deal with the storage facilities of both the structured and the unstructured data. The paper suggests that by the year 2020 the number of devices which will be associated with the IoT will be around 75 billion. The widespread expansion in the field of IT has ensued the evolution of plentiful technologies like IoT and big data technologies. The bigger volume of the data, the huge speed of the data which are transported from one unit of the organization to another are managed using the big data analytics. The alignment between business and IT facilities was described in the paper. Thus the paper was very much useful to understand the impact of IoT in big data analytics.
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.
The paper concludes the role of the big data in Internet of Things which are used in our daily life as well as in the business organizations. The details of the data storage facility provided by the IoT based devices and the processing services can be understood from this paper. The main feature of this paper highlights the importance of data analytics in IoT to make better decisions. The current market trends of the use of the big data technologies in Internet of Things such as Hadoop and cloud based analytics can be also understood from the paper. Thus the paper helps in understanding the role of the big data for the IoT based devices.
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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