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  • First Update!

    We have some progress regarding the definition of the scope and the expected outcomes for our project.

    From an in-depth literature review, we found that several studies have shown that pets can improve the social relationships of their owners since they reduce the feeling of loneliness and social isolation, particularly helping the elderly, children, or people with physical disabilities. For this reason, pets have become a fundamental part of the home and family. However, adopting a pet comes with responsibilities and care.

    One of the most important aspects of a pet care is the timed and balanced diet that provides the proper nutrients to keep them healthy. Yet, due to work and personal commitments, many people are unable
    to adapt to these schedules.

    From this analysis, we found out that there is a gap in current solutions for smart pet feeders, which are an excellent option to control pets’ diets.

    Currently, commercially available solutions have standard features such as time-based feeding, and portion control. However, the price is significantly higher than for regular feeders, and the features they provide (from our perspective) are not worth it. Therefore, our project is to develop a feeder
    based on IoT technologies, including smart capabilities thath will include novel features based on machine vision algorithms and AI models to enable active pet identification
    and physical tracking to determine the optimal portion and feeding times.

  • This is our first blog post!

    We are Diana Narvaez and Alejandro Solorio. We are students from Purdue University. Alejandro is a PhD student working in industrial instrumentation and robotics and Diana is a Master student working in wireless optical communications and microelectronics. For the CNIT 581000 course, we will develop and Smart pet feeder! We are currently working on our proposal, and we will post some updates soon.

    Ps. This is our second try of a blog. Our previous one on GitHub didn’t work as we expected.