Automatic Home Security Management (LAAS-CNRS)
Internship project (June–Dec 2015) applying per-time-slice behavioral models to automate alarm arming and disarming decisions.
TL;DR: Modeling per-time-slice behavior preserves heterogeneity and improves detection — tailor models to temporal patterns rather than forcing a single global baseline.
Summary
During an internship at LAAS-CNRS (Toulouse), I worked on Smartfox projects to make home alarm systems (Myfox Home Alarm) more autonomous. The approach builds empirical models of "normal" behavior per time-of-day slice so the system can detect deviations and suggest or trigger arming/disarming actions.
Approach
Instead of a single global model, the system learns multiple per-slot models (morning, afternoon, evening, night) because occupant behavior varies by hour. For each time slice we fit a behavioral normality model and compare live sensor streams (presence, motion, keyfob events) against predicted indicators. Significant deviations trigger alerts or automated actions depending on confidence and recent history.
Implementation
- Feature engineering on motion sensors, IntelliTAG events, badge/keyfob logs and temporal presence rates.
- Per-time-slot empirical models trained on a few weeks of data to create user-specific baselines.
- Real-time comparison of predicted vs observed indicators to detect drift and trigger alarms or suggestions.
Outcome
The approach reduced false alarms and provided a path to automatic arming/disarming suggestions tailored to each household. The work was part of LAAS-CNRS research lines and fed into Smartfox/Homecare projects focused on longitudinal monitoring.
Key Takeaway
Design insight: Modeling per-time-slice behavior preserves heterogeneity and improves detection — tailor models to temporal patterns rather than forcing a single global baseline.
FAQ
What is the key takeaway from "Automatic Home Security Management (LAAS-CNRS)"?
Modeling per-time-slice behavior preserves heterogeneity and improves detection — tailor models to temporal patterns rather than forcing a single global baseline.
Who wrote this and what is it about?
This was written by Mahmoud Trigui, Senior Data Scientist. Internship project: behavioral models for automatic arming/disarming of Myfox Home Alarm. LAAS-CNRS, Toulouse, 2015.