MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202641106015 A) filed by Saveetha Institute Of Medical And Technical Sciences on September 03, 2026, for Dog Lang Decoder System.
Inventors include Mohamed Fasil Hak; Dr. J. Mohemed Yasin; Dr. S. Jothi Arunachalam; and Dr Ramya Mohan.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: Communication between humans and dogs is often limited due to the inability of humans to accurately interpret canine vocalizations, body language, and behavioral patterns. The Dog Language Decoder System is an Artificial Intelligence—based solution developed to analyze and interpret dog behaviors and translate them into meaningful information that can be easily understood by pet owners. The primary objective of this system is to bridge the communication gap between humans and dogs, thereby improving pet care, safety, and emotional bonding.The proposed system utilizes advanced technologies such as machine learning, computer vision, and audio signal processing to monitor and analyze various behavioral indicators, including barking sounds, whining, growling, tail movements, ear positions, and overall body posture. Real-time data is collected through integrated sensors, cameras, and microphones. The collected data is processed using trained AT models that classify the dog's emotional and physical states, such as happiness, fear, aggression, anxiety, hunger, or the need for attention.The decoded outputs are presented through a user- friendly mobile or web-based application interface in the form of text notifications or alerts. In addition, the system maintains behavioral history logs that help in identifying patterns and predicting potential health or stress-related issues. This predictive capability supports early intervention and promotes better animal welfare.The Dog Language Decoder System can be applied in smart homes, veterinary clinics, animal shelters, and pet training environments. By enabling more accurate understanding of canine communication, the system contributes to responsible pet ownership, reduces behavioral misunderstandings, and enhances the overall quality of interaction between humans and dogs. Continuous model training and data expansion can further improve system accuracy and reliability in real-world scenarios.
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