Now Tulip can talk with your Google Assistant! Tulip can ask you for water, sunlight what every a plant needs. The best project by Google to talk with plants this is nothing but something innovative and needed. Google used machine learning and AI in programming what then can use to get and analysis more and more information from the plant. They analyze their movements, growth and behavior and using machine learning they analyze data and with AI they are now efficient of plants to speak with humans using Google Home!
How did they do it
The Netherlands produce nearly 12.5 billion flowers per year. Dutch tulips are among the tallest flowers in the world, and build strong communities within the fields. Researchers have shown that the tulips communicate with each other through their root systems and are able to share resources. Famously, a little red tulip was able to plug a leak in the seawall that protects Holland, thanks to the early warning system perfected by the network of roots that stretches all across the Netherlands.
Many people objectify tulips and want to just display them in vases in a way that is disconnected from the roots that supply so much meaning to their lives. At Google, we believe in organizing the world’s information and the information inherent in the root network was appealing to us. Thanks to collaboration with Wageningen University & Research and libraries of past audio files, we have digitized flower communications over the centuries and have built a machine learning system to identify what the tulips are communicating. By doing so, we have been able to improve the lives of the tulips (at least up to the point they are cut and shipped).
The training architecture was quite simple. We were able to use Google Cloud Speech to Text and Auto ML Natural Language to train the machine learning models without having to write any code. Carrying out real-time predictions was a bit more challenging, especially because of connectivity problems tying more than a million tulips together. We use Cloud IoT Core to collect the audio data from individual tulips, and carry out predictions on Kubeflow Pipelines “on-premises”. The requests from the tulips are then acted upon by human overseers, as shown in this video