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Traditional location tracking systems are great at answering "where," but fail to answer "what is happening?" This creates a massive problem in real-world software engineering: operators are flooded with false alerts because a safe, normal event (like driving past a school) triggers the exact same alarm as a genuine threat (like loitering near a school).
In this talk, we’ll solve this context problem by building a practical, hands-on application of vector spaces. While vectors are incredibly popular right now for LLMs and text search, we will look at how to encode physical behavior - like speed, dwell time, and proximity - into a simple, 3-dimensional vector space.
You don't need any prior experience with spatial data to follow along. Using Oracle AI Database 26ai, we will walk through the database architecture and SQL required to combine basic location tracking with AI Vector Search. By the end of the session, you'll see how creating a simple vector space can reduce alert noise by up to 90% in high-stakes environments like parolee tracking and museum security.
What you will learn:
SDO_GEOMETRY) and vector math (VECTOR_DISTANCE) in a single query to prioritize real threats without missing true positives.Doug Drechsel has worked on many server side platforms including Tuxedo and WebLogic Server. He is currently a developer advocate working with the Database team and reaching out to full stack developers. His most recent work has been with creating servers as a service using Node.JS, specifically in the Mobile/Web use cases.