A Rapidly Growing Shift From Analog Methods To Predictive Roadway Analytics – How One Company Is Breaking Ground in AI-Based Predictive Traffic Analytics

Traffic management center personnel are burdened with monitoring multiple feeds and data sources, which can be overwhelming. These centers rely heavily on human operators to visually detect and comprehend roadway incidents. However, human observers are susceptible to missing important details, unlike AI systems. 

Rekor AI REKR is revolutionizing these centers by eliminating the need for a large number of human operators. As the world embraces AI, one of its most significant advantages lies in enhancing safety and expediting emergency response, primarily by eliminating human limitations in incident perception.

Predictive data has become increasingly important in today's technology-driven world. As more and more devices and systems become connected, the amount of data generated is growing exponentially. Predictive data analytics tools are used to analyze this data and identify patterns and trends that can be used to make predictions about future events or behaviors. This information can be used to make informed decisions and proactively prevent or mitigate potentially dangerous road conditions.  

When it comes to traffic data, the importance of predictive data cannot be overstated. According to the American Society of Civil Engineers (ASCE), the U.S. road infrastructure received a grade of "D" in their 2021 Infrastructure Report Card. AI-based predictive data can help assess road congestion or even show traffic managers problem areas like sudden lane closures or stretches of roadways with higher rates of accidents. 

As technology advances, reliance on AI-based predictive data is only expected to grow. The global predictive analytics market was valued at $10.5 billion in 2021, and it is expected to be worth $28.1 billion by 2026, with a CAGR of 21.7% over 2021-2026. AI adoption is a significant reason for the projected growth, and companies that successfully leverage AI technology will be in high demand in the coming years. 

AI roadway intelligence company Rekor has prepared for precisely this growth. Rekor is an AI-driven data company that uses its digital infrastructure operating system, Rekor OneTM, to ingest billions of data points from multiple sources – all in an attempt to transform data into knowledge that can be used to improve transportation systems into fully functioning and safe roadways. 

Because the company's Rekor One platform aggregates vast amounts of data to train an AI model, the company says that roadway anomalies are rapidly identified. Rekor's Command software platform can send real-time incident alerts to overworked transportation management center (TMC) operators, who can take action to confirm, mitigate, and clear the roadways of any disrupting events. The feedback from these incidents is then fed back into the model, allowing it to continue learning and improving its accuracy over time. 

Additionally, Rekor reports that the Command system can detect incidents eight minutes earlier than other methods and uniquely identify 43% of all events. This faster and more accurate detection enables quicker and more systematic identification and response, which can improve Traffic Incident Management (TIM) timelines, enhance traffic flow and minimize the risk of secondary accidents. Ultimately, this could enhance safety for motorists and emergency responders on U.S. roadways. The successful analysis of aggregate data is truly the beauty of predictive analytics. 

Predictive data platforms like Rekor One will be essential in transforming U.S. roadways into more functional infrastructure – all while driving down the cost of mismanaged systems. By leveraging predictive data, transportation officials can make more informed decisions about infrastructure investments and traffic management strategies, leading to more efficient and safe transportation systems. Predictive data has the potential to save lives, money, and energy. 

Featured photo by CHUTTERSNAP on Unsplash.

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