Translating Tails into Tales
HeartTail AI Smart Pet Collar is the first dedicated, non-invasive solution for real-time, objective canine emotional health monitoring. Designed for high-value working dogs including military K-9 units, police dogs, and service animals.
Key Features
91%+ Accuracy - AI-powered emotional state detection using advanced deep learning
Real-Time Alerts - Immediate notifications on stress, anxiety, and emotional changes
HRV Analysis - Advanced Heart Rate Variability monitoring for objective mental health assessment
Multi-Modal Data - Captures physiological metrics, activity patterns, and vocalizations
Long-Term Tracking - Comprehensive reports for veterinarians and training staff
Why HeartTail AI?
The Problem: 5-10% of military working dogs show signs of PTSD. Early signs of stress and anxiety are often missed, leading to performance degradation, early retirement, and handler risk.
The Solution: HeartTail AI provides objective, data-driven insights into your dog's mental state, enabling preventive intervention before problems become chronic.
The Science
SDNN (Standard Deviation) - Overall HRV measure indicating parasympathetic tone and calmness
RMSSD - Short-term variability reflecting parasympathetic activity and relaxation
LF/HF Ratio - Critical stress indicator (Low = calm, High = stressed)
Perfect For
Military Working Dogs (detection, patrol, protection)
Police K-9 Units
Service Dog Organizations (PTSD support, mobility assistance)
Search and Rescue Teams
High-value working animals (investment $20k-$40k+ per dog)
Value Proposition
Asset Protection - Prevent loss of highly trained dogs due to avoidable mental health issues
Performance Maintenance - Proactive stress management ensures peak operational capacity
Cost Reduction - Reduce costs associated with early retirement and replacement training
Ethical Standard - Demonstrate commitment to highest animal welfare standards
HeartTail AI Smart Pet Collar
Deep Learning Engine: Our proprietary Modified EfficientNetB5 architecture processes visual data through: - Squeeze-and-Excitation (SE) Modules:Adaptively recalibrate feature channels to focus on critical emotional indicators (e.g., eye tension, ear angles) - Dense Residual Blocks: Capture subtle hierarchical features through residual connections, enabling detection of minute changes in posture and expression HRV Analysis Engine: Advanced signal processing algorithms extract three key biomarkers: - SDNN (Standard Deviation of NN Intervals): Overall HRV measure indicating autonomic tone - RMSSD (Root Mean Square of Successive Differences): Short-term HRV correlating with calmness - LF/HF Ratio (Low Frequency/High Frequency Power): Critical stress indicator (high = stress/fear, low = calm/contentment) Acoustic Classifier: A 1D-CNN + LSTM network analyzes vocal patterns to identify distress signals (87% accuracy across breeds).