Predictive analytics will save lives

Big data used to be a term that refers to a large volume of data. Over the years the term has expanded to include the ability to capture, store, and manage data to use analytics to make predictions about future events.

The integration of digital technologies and use of data in our daily lives occurs at an exponential pace. Companies in the automotive industry are finding new and efficient ways to analyze data to increase traffic safety by predicting behavior.

Car crashes killed more than 35,000 people in the U.S. 2018. Most of them because of human errors. They were attributed to more than 90% of the crashes. The autonomous technology represents a great opportunity to improve traffic safety.

LOOK AT THIS CRAZY PARKING..:-)

In 2019, we will see new efforts to combine technologies with products, using IoT to stream data and apply Machine Learning in real time.

Instead of using stored data from a traditional controlled environment it will be more common to process live streamed data with help of new frameworks. Daily intervals of data are often not sufficient. Predictive analytics is expected immediately.

With help of multiple sensors, including lidar, radar and cameras, automotive companies can process and analyze new data in real-time. Stream processing help users query continuous data streams and detect conditions immediately after receiving the data. Speed is necessary and new data has to be processed as soon as it’s known to the system.

Faster processing time will help to predict traffic behavior in real-time and enable automotive companies to emphasize on proactive safety rather than reactive safety. This paradigm shift will prevent a majority of car accidents, especially those who are attributed to human errors.

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