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Here are the steps: 1. Prepare several objects and an ESP32-CAM. 2. Take pictures of objects with ESP32-CAM, collect a minimum of 20 images for each object. Besides the object image, make sure to also take a background image, to make it easier to identify when there is no object (take at least 5 images). To take pictures of objects and backgrounds, please use the CameraWebServer program, which is in Examples, in ESP32, in Camera. 3. After collecting object images successfully, the next step is to apply machine learning using Edge Impulse for object detection which can later be embedded into the ESP32-CAM. For that, open Edge Impulse here: https://edgeimpulse.com/ 4. After Edge Impulse generates the program code for object detection, the next step is to prepare the Dashboard to display the object image and label of the object detection result. So that it can be monitored remotely, in the example here Adafruit IO (https://io.adafruit.com) is used. To accommodate image and label data, 2 feeds are used, named camera and label. Then to display the values of the two feeds, a Dashboard is used which contains an Image block and a Text block. The Image block will display the value from the camera feed, while the Text block will display the value from the label feed. 5. After the feed and Dashboard have been successfully created on Adafruit IO, the next step is to program the ESP32-CAM with the library created by Edge Impulse, which is given additional instructions for sending data to Adafruit IO. Use Arduino Editor Online (https://cloud.arduino.cc/) to program the ESP32-CAM. Upload the library by Edge Impulse, and use the following code: https://pastebin.com/B8L4Yitq 6. After the program has been successfully uploaded to the ESP32-CAM, open Serial Monitor, wait until the text "MQTT Connected" appear. If the text doesn't appear, disconnect the USB cable from the ESP32-CAM to the computer, then connect it again, then press the Reset ESP32-CAM button, then the text "MQTT Connected" should appear in the Serial Monitor, and the Dashboard on the Adafruit IO should display an image of the object and the label of the object detection result. For further information please visit this blog: https://bermainadafruitio.blogspot.co...