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Book of Abstracts | 2025 Information System Analysis and Design for a Social Network for Dog Owners
SE-E-12
Guy Aloosh; guyaloosh@gmail.com Guy Haliva; guyhaliva123@gmail.com
Advisor: Ms. Alona Kutsyy
SCE - Shamoon College of Engineering, Be'er-Sheva
The Woof application addresses the challenge of connecting dog owners by creating a dedicated social platform. This system helps users discover and connect with other dog owners nearby using a matching system based on shared interests and location. The platform features a modern interface where users can create profiles, share photos and videos, and chat in real time. A key feature is an interactive map showing nearby dog parks, veterinarians, and pet shops to support local engagement. The development process included research into user needs and social behavior, resulting in a friendly and intuitive experience. The final product offers secure login, personalized suggestions, and social features that build a strong community where dog owners can share, meet, and form lasting connections.
Keywords: chat (real-time), dog owners, location-based services, matching system, social network
Doggybreed: Identify Dog Breeds from Photos
SE-E-13
Gabriel Ben Shalom; gabriel.benshalom@gmail.com Ido Tamasis; idotamsis2@gmail.com
Advisor: Mr. Alexander Lazarovich
SCE - Shamoon College of Engineering, Be’er-Sheva
A dog is “man’s best friend,” but how much does the person know about their dog? DoggyBreed is an innovative app that uses machine learning to identify dog breeds from photos. Users can simply upload a picture of a dog. Our app offers a valuable solution for individuals who want to discover their dog’s breed without the hassle of a DNA test, providing a precise result with a free app. Additionally, veterinarians can refer people to DoggyBreed to easily identify the breed of a dog outside of working hours. DoggyBreed combines convenience with accuracy, making it a useful tool for pet owners and professionals alike.
Keywords: easily, identify, machine learning
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