Application of Big Data in Automotive Industry

Industry projections reveal that by 2015 the automotive industry will become the 2nd largest generator of data from proliferating sources; that includes sensor signals, GPS based navigation logs, ad-hoc network based in-car data, registration & license records, warranty & insurance claim databases, etc. Harnessing this astounding quantity, variety, velocity & veracity of data instigates manifold applications and areas of focus for key stakeholders of the automotive industry.

Designers, OEMs and ancillary manufacturers can enhance ruggedness, efficiency, longevity, features, security, theft prevention measures of vehicles & spare parts in alignment with inputs from the big data analytics of engineering parameters, routes & driving habits, cabin preferences, communication media usages, service reports, to name a few – thus living up to the dramatic shifts in expectation and experience of customers. Car dealers can revamp their balance-sheets by maintaining a perfect synchronization between value-cum-supply chain management, inventory management, aftermarket service, proper warranty coverage policies and reminders.

Commercial fleet managers, tax authorities, traffic controllers, insurance agencies and State/ Local Governments will be able to address a wide array of common and exclusive concerns by adopting surprising revelations of data crunching techniques. Of particular importance is a proxy model that can standardize several compatible issues like monitoring of load, over-the-road taxes, emission levels, route optimization, traffic rule violation & diversion, assessment of idle time, multiple driver scenarios, accident prone situations and individuals, fraud and theft detection & reporting- all of these in a real-time scenario leading to annunciation and predictive automatic prevention. A special case for study is that of tax evasion by citizens after earning easy cash for scrap cars, by determining the likelihood of selling his car within a certain span of time, and thereby alerting the concerned authorities.

Apart from the mainstream advantages, fringe benefits of big data are also aplenty if conventional mindsets and processes shares the stage with it. For instance, websites and softwares catering to the queries of car owners regarding depreciation of resale value for their used cars can capitalize on the value added by data analytics, in order to optimize their responses around a reasonable maximum selling price – a much more uniform, practical, and acceptable approach for individuals seeking cash for scrap cars, but delaying the decision for lack of information and fear of getting exploited.

Incidentally, many micro, small and medium scale enterprise in the ‘used car’ industry has floated an apparently lucrative scheme called “cash for scrap cars” only after re-christening an old concept with the common yet catchy phrase. As such, it is not objectionable, but only up to the point when no murky affairs are organized behind the dead, rusted metals of their junkyards. From a social perspective, a large and complex puzzle involving apparently disparate issues like increased frequency of carjacking & other criminal occurrences in a certain area, along with the existence of unexplained, unaccounted funds in bank accounts of residents of that same area, is indeed very much a big data problem with a potential of creating serious offenses if not checked in real time, bypassing the convention of causal inspections.

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