Research Article
A Data Science Methodology for Internet-of-Things
@INPROCEEDINGS{10.1007/978-3-030-23943-5_13, author={Sarfraz Brohi and Mohsen Marjani and Ibrahim Hashem and Thulasyammal Pillai and Sukhminder Kaur and Sagaya Amalathas}, title={A Data Science Methodology for Internet-of-Things}, proceedings={Emerging Technologies in Computing. Second International Conference, iCETiC 2019, London, UK, August 19--20, 2019, Proceedings}, proceedings_a={ICETIC}, year={2019}, month={7}, keywords={Internet-of-Things Data science Analytics Big data}, doi={10.1007/978-3-030-23943-5_13} }- Sarfraz Brohi
Mohsen Marjani
Ibrahim Hashem
Thulasyammal Pillai
Sukhminder Kaur
Sagaya Amalathas
Year: 2019
A Data Science Methodology for Internet-of-Things
ICETIC
Springer
DOI: 10.1007/978-3-030-23943-5_13
Abstract
The journey of data from the state of being valueless to valuable has been possible due to powerful analytics tools and processing platforms. Organizations have realized the potential of data, and they are looking far ahead from the traditional relational databases to unstructured as well as semi-structured data generated from heterogeneous sources. With the numerous devices and sensors surrounding our ecosystem, IoT has become a reality, and with the use of data science, IoT analytics has become a tremendous opportunity to perceive incredible insights. However, despite the various benefits of IoT analytics, organizations are apprehensive with the dark side of IoT such as security and privacy concerns. In this research, we discuss the opportunities and concerns of IoT analytics. Moreover, we propose a generic data science methodology for IoT data analytics named as Plan, Collect and Analytics for Internet-of-Things (PCA-IoT). The proposed methodology could be applied in IoT scenarios to perform data analytics for effective and efficient decision-making.
