Meaningful Insights Lacking in Sensor Big Data

The largest growth area in data storage is sensor information. This includes areas like automotive, aerospace, industry/IoT and even security. The workflows that deal with such data are not built for scale. These data-burdened workflows
 require too much data to find challenges and flaws. Automation of review with AI and Machine Learning only addresses specific narrow areas of analysis. Today this means in many cases human intervened review which introduces its own problems.

If we look specifically at automotive, where Ottometric focuses as their beachhead, we see pre-autonomous systems, like ADAS struggling to achieve higher system effectiveness rates. Industry stakeholders have called out such systems as moderately effective where the risk is the end-user disabling such systems out of frustration.

The ability to better analyze where effectiveness in such systems is lacking is essential, this is an area that is lacking in current proprietary in house tools and solutions on the market today. Better simulation and better processes to emulate scenarios are essential but it doesn’t solve analysis of real generated data, specifically in automotive with the millions of miles and multi-petabytes of validation data generated from endurance testing.

Ottometric Solves the Data Analysis Challenges

Advanced-Driver-Assistance-Systems (ADAS) being delivered in modern vehicles enhance vehicle safety but the effectiveness of these systems needs to improve greatly. As vehicle complexity increases with more sensors and systems, the difficulty and interdependency of the data fusion makes validation ever more complex, time consuming and expensive.

The Ottometric solution provides a robust platform to ingest, clean and identify valuable data, visualize this data for deeper understanding where challenges occur and generate analytics with our proprietary artificial intelligence (AI) and computer vision technology, thus augmenting or replacing ineffective manual review processes.

The result is significant cost reductions and higher accuracy than manual review of data that has become dependent on in-house or off the shelf unscalable tools. With more extensive and rapid analysis, long tail problems can be better understood, further improving ADAS features being delivered to the market.

Why Ottometric?

We are a team based in Boston with global presence for customer interactions and development.

Our expertise is in automotive, big data, machine learning and AI. Our team has diverse backgrounds from Analog Devices, Autoliv, NVIDIA, Optimus Ride and VMware.

Our investors include Trucks Venture Capital and Berkeley SKYDECK

Today we work across the ecosystem of automotive Tier 1, Tier 2 and branded OEM’s who utilize the Ottometric platform to evolve their workflows to better development and validation success. We do this across public, private and hybrid clouds ensuring data security is maintained while scalable processing is available.

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