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Use Cases | Sensors
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Speech Emotion Recognition App

Speech Emotion Recognition is the task of recognizing emotion on the basis of your speech. It has applications in recognizing mood of a person.


tinyML mic audio speech keras
+3
Published: Oct. 30, 2020, 7:54 p.m.
Arrhythmia Prediction App Using E.C.G.

The use of deep learning models in medical fields can help reduce error rates and increase the possibility of an earlier diagnosis for better treatement.


tinyML keras Sensors signal medical
+4
Published: Oct. 30, 2020, 3:45 p.m.
Pollen Carrying Honey Bees Detection App

This deep learning model differentiates between images of honey bees carrying pollen and those that aren't which can be useful in bee farming for analysis/inference generation.


vision tinyML keras IIoT Sensors
+1
Published: Oct. 28, 2020, 12:59 p.m.
Heartbeat Anomaly Detection App Using E.C.G.

According to WHO 17.9 million people die each year due to Cardiovascular Diseases. Deep Learning can be used in early diagnosis using ECG (Electrocardiography).


tinyML keras Sensors signal medical
+4
Published: Oct. 27, 2020, 1:40 p.m.
Emotion Detection App Using E.E.G.

Electroencephalography (EEG) is an electrophysiological monitoring method to record electrical activity of the brain.


tinyML keras Sensors EEG signal
+3
Published: Oct. 15, 2020, 12:02 p.m.
Iot Based Gesture Recognition App

Gestures are mapped to accelerometer and gyroscope values during motion.


tinyML accelerometer gyroscope arduino keras
+5
Published: Sept. 16, 2020, 12:30 p.m.
Predictive Maintenance Using L.S.T.M.

Predict run-to-failures of an airplane engine in real time.


TensorFlow IIoT Sensors LSTM
Published: Sept. 9, 2020, 2:30 p.m.
Pump Failure Detection App

Predicts whether a pump will fail in the next 24 hours or not.


TensorFlow keras IIoT Sensors
Published: Sept. 7, 2020, 6:22 p.m.
Human Activity Recognition App

Predict the activity being performed by a human being in real-time


accelerometer gyroscope TensorFlow Sensors CortexM4
+1
Published: Sept. 7, 2020, 5:22 p.m.