Introduction
Introducing Background Control System
Implementing Pub-Sub Communication Using MQTT
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Introduction (0:58)
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Publish-Subscribe Communication Fundamentals (3:26)
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How MQTT Communication Protocol Works (2:26)
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Implementing MQTT Pub-Sub Communication For Demo Factory (3:13)
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Installing an MQTT Broker at the Edge (3:01)
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Creating Demo Factory MQTT Clients (4:31)
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Demonstrating MQTT Communication (3:45)
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Conclusion: setting The Stage For Machine Learning Integration (1:09)
Building & Integrating ML Image Classifier Into Control System
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Introduction (1:55)
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Fundamentals of Convolutional Neural Networks and Tensorflow (3:36)
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Introduction to Google Colab ML Development Environment (1:40)
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Gathering Images and Creating Training Dataset (2:54)
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Training Image Classification Model Using Python, Tensorflow and Keras API (11:13)
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Saving and Testing Image Classification Model (3:58)
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Introducing Tensorflow Lite: ML For Edge Devices (3:26)
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Converting Image Classification Model Into Tensorflow Lite Model (6:39)
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Deploying Tensor-flow Lite ML Model onto Edge Device (1:34)
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Building Python App For Image Classification Using TFLite Model, raspberry Pi and Pi Camera (5:54)
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Integrating Python Image Classifier with Control System Using MQTT (5:17)
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Demonstrating Edge Intelligent Demo Factory (3:19)
Conclusion
