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.

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  • cognitive computing

    The Safety Side Effect of Cognitive Computing

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  • cognitive computing

    Cognitive Automobile

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