The chapter portrays a new development in the field of embedded systems.
It showcases the combination of Machine Learning algorithms and low-memory
microcontrollers (ESP32-CAM). The uniqueness of this idea lies in the fact that
Machine Learning is generally perceived as a processor-intensive task that requires
high memory and storage. However, as seen in this chapter, one may soon realize how
wrong this notion is with emerging technologies that are taking over the globe. This
project portrays the successful implementation of a binary colour classification model
on the ESP32-CAM with 68% accuracy post-training result with a mere 15 images of
each colour. Machine learning has increased over the years. Some applications include
image classification, object detection, and question-answering. This work merely puts
out awareness in this domain and is hopeful that dedicated efforts towards it can solve
many industrial problems.
Keywords: Arduino IDE, Arduino Language, Artificial Neural Network, Cloud Computing, MicroML, Object Detection, Python, Random Forest, Servo Motors
