Building an end-to-end solution with Azure & AI
You are the leader of a group of climate scientists who are concerned about the dwindling polar-bear population in the Arctic. As such, your team has placed hundreds of motion-activated cameras at strategic locations throughout the region. Rather than manually examine each photograph to determine whether it contains a polar bear, you have been challenged to devise an automated system that processes data from these cameras in real time and displays an alert on a map when a polar bear is photographed. You need a solution that incorporates real-time stream processing to analyze raw data for potential sightings, and one that incorporates artificial intelligence (AI) and machine learning to determine with a high degree of accuracy whether a photo contains a polar bear. And you need it fast, because climate change won’t wait.
Jeff Prosise is cofounder of Wintellect (www.wintellect.com), a developer consulting and education firm that provides services to companies all over the world. He has written nine books and hundreds of articles on software development, and today spends most of his time doing working with Azure and AI and managing WintellectNOW (www.wintellectnow.com). In his spare time, Jeff builds and flies large radio-control jets. He loves the smell of jet fuel in the morning.