Develop a smart environment for dog social network

• Main Author: Leong, Wai Chun
• Format: Final Year Project / Dissertation / Thesis
• Published: 2021
• Subjects: QA75 Electronic computers. Computer science; T Technology (General)
• Online Access: http://eprints.utar.edu.my/4291/1/18ACB06442_FYP.pdf; http://eprints.utar.edu.my/4291/

This project is regarding to the problem of dog loneliness. Dog can be lonely when the dog’s owner left the dogs alone at home without understand what the dogs will feel when they are at home alone. Dog might be depressed due to the feel of loneliness being left alone at home. The major problem that will be focus on this project will be the dog loneliness and the problem of dog does not have any other dog companion to connect with each other when they are lonely. As most of the existing product unable to solve one of the problems which will be the dog’s emotion. The existing product unable to detect that what does the dog felt when they are left alone. The only feature that the existing product offers is connected 2 parties with each other which is between dog’s owner and the dog. Some researches and literature reviews will be carried out to look deeper into how a machine can able to understand the dog’s emotion to solve the dog loneliness problem by using image recognition and sound recognition method. The reviews of existing products including will be Pawbo+, PetChatz, Furbo Dog Camera, Petcube Bites Treat Camera, and Petzi Treat Cam are written in the literature review section of this report. After reviewing the strengths and weakness of the existing products above, a clearer vision will be captured on the challenges will be presented in this report. The proposed solution of this project is to develop a dog social network which able to connect 2 dogs together to communicate with each other and understand how the dog feel by developing a model which will recognize the dog’s emotion to tell the dog owner that how does the dog feel when they are left alone. The development technologies and tools involve in this project will be Google Cloud Platform, Android Mobile, Keras, Jupyter Notebook, Audacity, Python, Node.js and Android Kotlin language for program implementation.