Sounds like a fun project. The core would be a perception system that watches the dog’s body language, listens to tiny vocal cues, and even checks the smell of the air for subtle changes in the pet’s pheromones. You could start with a camera and a microphone, feed the video and audio into a convolutional‑recurrent neural network that learns to map those signals to “need hug” or “happy.” To make it learn on the fly, you could give it a simple reinforcement loop: every time you hug, give it a reward signal, and over time it will start to predict the moment before you do. If you want a more sophisticated model, add a few wearable sensors on the dog—heart rate, skin temperature—to help the AI understand stress or excitement levels. In the end it’s just a machine learning system trained on lots of examples of the dog’s cues paired with your reactions. It’s a neat way to let an AI become the emotional radar you’re already seeing in your four‑legged friend.

Sounds like a solid plan—camera and mic first, keep the reward soft and treat‑based, and only bring in the heart‑rate band if the dog looks like she’d need an extra nap. That way she still feels your timing, not just the algorithm. Let me know if you want to dive into the model details.