Explanation video : Implementation of A Real-Time Smart Pest Monitoring & Detection System for Urban Farming using YOLOv5 on Raspberry Pi4 with Farmbot ~ Project Tithonus
Thank you for sharing your work and the vision behind this project. The idea of implementing a real-time pest monitoring and detection system using YOLOv5 on a Raspberry Pi 4, integrated with FarmBot, is undeniably ambitious and inspiring. It’s the kind of innovation that sparks excitement and curiosity within the community.
However, it’s important to acknowledge the practical challenges of turning such concepts into fully functional, reliable systems. Real-world applications of AI in farming, especially on resource-constrained devices like a Raspberry Pi, involve significant hurdles in terms of computational efficiency, environmental variability, and robustness under diverse conditions. The presentation, while engaging, appears to oversimplify some of these complexities.
That said, we would love to see this project evolve into something tangible and accessible. A truly open-source implementation, backed by rigorous testing and community feedback, could be transformative. It would also strengthen credibility to share more technical details about the system’s limitations, challenges faced, and steps toward overcoming them.
We’re looking forward to updates, perhaps with deeper insights into the implementation and how the community can contribute or adapt the system for their use. Keep dreaming big, but also stay grounded in the realities that make such dreams achievable. Best of luck!
Thank you, Jan, for your thoughtful feedback. Project Tithonus is indeed a proof-of-concept project and we fully acknowledge the complexities involved in transitioning such concepts into fully operational systems.
We understand that for real-world applications—especially on resource-constrained devices like the Raspberry Pi—there is a need for deeper model training, more comprehensive integration, and rigorous testing to ensure robustness across diverse environmental conditions.
The presentation’s intent was to demonstrate the potential and generate discussion, but as you rightly pointed out, there are practical challenges like computational efficiency and variability in farming environments that need to be addressed for scalability and reliability. Moving forward, these are key areas of focus for the project’s development.
Thank you again for highlighting these critical aspects!
