Chris LaPré

For years, the smart home has relied on explicit triggers: button presses, voice commands, and line-of-sight motion PIR sensors. Now, the convergence of Wi-Fi wave sensing, RF spatial dynamics, and edge AI is introducing a fundamental shift: continuous, non-invasive Ambient Context. This educational session explores how non-line-of-sight (NLOS) RF sensing captures room-level presence, activity levels, sleep/rest dynamics, and fall occurrences through walls without relying on invasive cameras or wearable devices. Integrators will learn how this emerging "context layer" sits between physical sensors and control automation platforms (Alarm.com, Matter/Thread networks, climate, and security platforms). We will cover RF signal processing basics, optimal mesh topologies, false-alarm reduction via fusion sensing, and high-growth revenue opportunities in aging-in-place care, security, and occupancy-driven HVAC energy management. Learning Objectives : By the end of this 60-minute session, attendees will be able to: 1. Understand RF & Wi-Fi Wave Sensing Fundamentals: Explain the mechanics of Channel State Information (CSI), non-line-of-sight wave disruption, and multi-sensor fusion (Wi-Fi + Thread mesh). 2. Map Context to the CEDIA Control Architecture: Identify how ambient occupancy, motion, and anomalous behavioral pattern data (linked to distress situations or falls) integrate into existing security, climate (HVAC), lighting, and automation platforms. 3. Target High-Growth Market Segments: Apply ambient context solutions across residential security, aging-in-place (CareTech), multi-dwelling units (MDUs), and energy management. 4. Design & Deploy Non-Invasive Mesh Networks: Evaluate network topology requirements, avoid common RF interference pitfalls, and ensure privacy-first installations that build client trust.