Application of Big Data in Automotive Industry

Industry projections uncover that by 2015 the motor vehicle industry can be the 2nd major generator of data from proliferating resources; which includes sensor signals, Gps navigation founded navigation logs, ad-hoc network structured in-car data, subscription & license information, warrantee & insurance state directories, etc. Harnessing this incredible quantity, variety, speed & veracity of data instigates manifold applications and regions of concentration for key stakeholders of the motor vehicle industry.

Designers, OEMs and ancillary manufacturers can boost ruggedness, efficiency, longevity, features, security, fraud prevention options of vehicles & free parts in position with inputs from the best data analytics of anatomist variables, routes & driving a vehicle habits, cabin choices, communication advertising usages, service information, to mention a few – thus living up to the remarkable shifts in expectation and connection with customers. Car dealers can revamp their balance-sheets by maintaining a perfect synchronization between value-cum-supply chain management, inventory management, aftermarket service, proper warrantee coverage policies and reminders.

Do not forget to read: [The Benefits of Midsize Sedans]

Commercial fleet professionals, tax government bodies, traffic controllers, insurance providers and Status/ Local Government authorities can address several common and exclusive concerns by implementing unusual revelations of data crunching techniques. Of particular importance is a proxy model that can standardize several appropriate issues like monitoring of insert, over-the-road fees, emission levels, course optimization, traffic guideline violation & diversion, analysis of idle time, multiple drivers scenarios, crash susceptible individuals and situations, fraud and fraud detection & confirming- many of these in a real-time situation resulting in annunciation and predictive computerized prevention. A particular case for review is that of taxes evasion by individuals after gaining easy cash for scrap vehicles, by identifying the probability of retailing his car within the certain span of their time, and thus alerting the worried government bodies.

In addition to the mainstream advantages, fringe great things about big data are also aplenty if conventional mindsets and processes shares the stage with it. For example, websites and softwares catering to the queries of car owners regarding depreciation of resale value because of their used cars can capitalize on the worthiness added by data analytics, to be able to optimize their responses around an acceptable maximum value – a more uniform, practical, and acceptable approach for folks seeking cash for scrap cars, but delaying your choice for insufficient dread and information to getting exploited.

Incidentally, many micro, small and medium level business in the ‘used car’ industry has floated an seemingly lucrative structure called “cash for scrap vehicles” only after re-christening a vintage concept with the normal yet catchy term. As such, it isn’t objectionable, but only up to the real point when no murky affairs are structured behind the lifeless, rusted metals with their junkyards. From a sociable perspective, a sizable and sophisticated puzzle involving evidently disparate issues like increased regularity of carjacking & other legal occurrences in a certain area, combined with the lifestyle of unexplained, unaccounted cash in loan provider accounts of residents of this same area, is definitely very much a huge data problem with a potential of fabricating serious offenses if not inspected instantly, bypassing the convention of causal inspections.

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