Conceptual Framework for the Application of Big Data in the Automobile Industry
Shubham Fialoke, Vibhu Dharmadhikari, Varun Bhati, Vaibhav Gupta · International Journal of Advance Research and Innovation · 2016
The paper sheds light on big data analytics, the science of machine learning viz. data science and how it can be used in today’s automobile industry. Data science is a new field that has emerged out of the coupling of computer science and statistics. The ‘what?’ and ‘how?’ of data sciences are explained thoroughly. After defining what Big Data and Data Science are, the job market of data science is explored. This includes the jobs data scientists undertake and the skills acquired by them viz. machine learning and natural language processing to find patterns in this data and make predictions. Furthermore, the future of big data analytics in manufacturing and production is analyzed, particularly in connected vehicular systems. Today, with the advancement of technology, much media attention has been focused on an area where big data and automobiles intersect: Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication collectively referred to as Machine-to-Machine (M2M) communication. This paper focuses primarily on data science in driverless cars and the advent of Internet of Things (IoT) in automobile technology.