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Machine learning interpretation of sensor data

I work as a visual artist. My project is based upon the goal that a houseplant control motor actuators. More info about the project can be found here: [url removed, login to view]

Two differential signals (four electrodes) are collected from the plant's leafs. The signals goes to a raspberry pi by a ads1115 16-bit adc. The goal is that the plant, as far as it is possible, control the motor actuators (robot legs).

I want a machine learning/ann solution to interpret the signals and choose between available actuator movements. The python script at [url removed, login to view] defines possible movements based on the physical construction.

Regarding the machine learning code I see that different possible solutions are suggested by various papers dealing with a similar problem when prosthetics are trying to classify emg signals to motor movements.

I believe unsupervised classification is desired since there is no way to classify a plant's electrophysiology to this project's goals (to move robot legs in some autonomous way). I see that autoencoder configurations have been used to reduce/abstract in an unsupervised way. Convolutional network in conjunction with k-means and autoencoder ([url removed, login to view]), and extreme learning machine based autoencoder ([url removed, login to view]) are two configurations I have seen. Another solution I have noticed are network based wavelet transform classification ([url removed, login to view]).

It should be noticed that I do not have any particular knowledge in machine learning, signal processing and so forth. The goal is mainly a conceptually sound treatment of the signals from the houseplant by the motor actuators.

Evner: Kunstig intelligens, Maskinoplæring, Python

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Om arbejdsgiveren:
( 0 bedømmelser ) Stokmarknes, Norway

Projekt ID: #16746290

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thomaspaniagua

Hey, I just tried to take a look at your plantoid project in Hackathon but the link appears to be down. Regardless, based on your description here I'd very much like to help you out with this project. I noticed you men Flere

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