Video can be used as the input data for the real-time monitoring of machines, products, or processes to which sensors cannot be affixed. Industrial and scientific monitoring applications, compared to other video sources, such as those from surveillance, broadcast, mobile robotics, social media, or entertainment, can often be engineered and structured. Yet, applications of video-based instrumentation in industrial, manufacturing, and scientific experimentation environments are not extensively addressed by the computer vision community.
We discuss the needs, challenges, and recent success in deploying real-time, data-science enabled techniques to efficiently reduce the complexity and dimensionality of raw video data to extract actionable information for real-time feedback and process control, defect detection, and wear and degradation related for factories and the factory subsystem.
In the next five years, autonomous vehicle technology may finally blossom and enter our lives. The first applications of intelligent self-driving vehicles may embark on highways, campuses, and warehouses. Bottlecap-size consumer drones may roam around, filming the next big hit video on social media. What are some of the technical challenges and technological enablers? How will the new technology impact new products, markets, businesses, and ultimately our lives? Professor Sertac Karaman's research is enabling new ways of designing autonomous vehicles with the help of rigorous, mathematical thinking that leads to valuable insights.
CATALOG The world will generate 160 zettabytes of data in 2025. That’s more bytes than there are stars in the observable universe. Conventional storage media like flash-drives and hard-drives do not have the longevity, data density, or cost efficiency to meet the global demand. CATALOG is building the world’s first DNA-based platform for massive digital data storage.
Interpretable AI The company is bringing interpretability to machine learning and artificial intelligence and was co-founded by Professor Dimitris Bertsimas of MIT Sloan School of Management’s Operations Research Center (ORC).
Osaro Advanced imaging AI for robotics that can identify objects others cannot.