Cognitive Computing in Automotive

Cognub challenges automotive domain problems with the use of Machine Learning methods/algorithms. Intelligent assistance and prediction is a problem domain where it is difficult to provide precise specifications for desired system/program behavior. Selecting correct feature vectors requires involvement of domain experts, and selecting correct algorithms requires experienced data scientists. So we work together closely – not only to select correct feature vectors and learning algorithms, but also to define the problem domain and business objectives, validate the selected algorithm in terms of functionality and performance metrics, and collaborate with business teams to finally deploy the learning algorithms in products to demonstrate tangible business benefits.

Recommendation Engine

Recommendation Engine which provides recommendation for the best fit car to a consumer considering the trends in the demographic and market segments. Recommendations are personalized to meet the expectation based on purchase preferences. This will be based on a proprietary score, which is used to push the suggestions. Technologies used include correlation score and collaborative filtering.

Predicting appropriate driving actions based on time-series data

The machine-learning algorithm uses a combination of data on “normal driving” and time-series data on the actual vehicle and driver to predict appropriate driver actions in real time.The technology detects cognitive distractions if the driver’s actions differ drastically from the algorithm-based prediction of what would be appropriate.

Virtual Dealer

Virtual Dealer helps the dealer to avoid losses that may be incurred on a trade-in car. We use adaptive learning technique to clone an in house expertise into an intelligent decision machine, which gives a suggestion with a confidence percentage. The tool allows the provision to set the profit margin and a tolerance to be entertained while negotiating the customer.

Application of Machine Learning for Predictive Maintenance

Machine Learning systems can help manufacturers improve their operations and competitiveness and involves regular and systematic application of engineering knowledge and maintenance attention to equipment and facilities to ensure their proper functionality and to reduce their rate of deterioration.

Our Blog

  • cognitive-computing

    Automotive Insurance – A Cognitive Approach

    The headline that we read every day is of automotive insurance. The media never portrays both sides of the story. In most cases in the interest of ratings, the media showcases the automotive dealers or the insurance firm as the bad guys. Like the old saying “History is written by the victors” we never know […]

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    The Safety Side Effect of Cognitive Computing

    People in this digital age will not be surprised at driverless cars. The advancements of science have boggled our mind completely. It has even enabled cars to care for human comfort, information and entertainment preferences in unimaginable ways. The future will have cars capable of self-repair and even communicating with its adjacent cars. Imagine a […]

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    Cognitive Automobile

    There is a widespread propaganda on the conceptualization of Artificial Intelligence in the field of Automobiles. The question daunting in everyone’s mind would be the purpose of A.I in an otherwise smooth-flowing system which is the automotive industry. The real question everyone must actually be pondering should be where all A.I can help the field. […]

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    Humans more often than not are always in a state of confusion. They are unaware of the next decision they need to implement. No matter how small or how big of a decision it is. People always hesitate before their final judgment. Even the best decision makers stagger when the stakes are high on a […]