To help AI catch small routine shifts early, track a handful of consistent, everyday signals—then focus on trends, not one-off “weird days.” The goal is to create a simple baseline for your pet and let the system flag gradual changes that can be easy to miss.
Track total sleep time, nighttime restlessness, and changes in nap timing. Useful signals include frequent position changes, pacing at night, sleeping in unusual locations, or struggling to settle. For cats, note time spent hiding or staying in one spot longer than usual.
Log meal timing, portion size eaten, speed of eating, and interest in food. Also track water intake (especially for cats and small dogs), repeated visits to the bowl, or sudden preference changes. Consistent “leftovers,” grazing when they normally finish meals, or new food-guarding behaviors can be meaningful patterns.
Monitor daily movement (steps, play sessions, zoomies), time spent inactive, and willingness to jump, climb stairs, or go on walks. Subtle mobility changes often show up as shorter play bursts, lagging behind, reluctance to jump onto furniture, or slower transitions from sitting to standing.
For cats, track litter box visit frequency, duration, clumps/volume patterns, and accidents outside the box. For dogs, track potty frequency, urgency, and any indoor accidents. Straining, very frequent small eliminations, or sudden avoidance of the usual potty spot are important signals to flag.
Note changes in barking/meowing frequency, intensity, and timing (like nighttime yowling or new separation vocalizations). Pair vocal patterns with context: door sounds, feeding time, being touched, or being left alone. Also track social shifts—seeking more attention, withdrawing, irritability, or changes in greeting behavior.
For a deeper walkthrough of turning these signals into usable routine insights, visit this guide to AI pet behavior tracking.
Record 1–2 weeks of “normal” sleep, meals, activity, and bathroom habits with consistent timing. Keep inputs steady (same feeders, litter, and walk schedule) so changes are easier for AI to detect.
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