“A machine that’s stopped or without raw materials is money wasted, ” and this holds true for any industry. In this sense, having real-time information about production processes allows us to control and optimize resources.
Before resorting to artificial intelligence, there are some tools to explore, such as computer vision and its basic functions available in OpenCV. With this, I developed an algorithm to detect if a conveyor belt is moving and if raw materials are being transported. This automates the preliminary phase of data ingestion in the cloud.
The prototype consisted of a conveyor belt built from recycled materials and controlled by an Arduino. I implemented the algorithm in Python with OpenCV using Visual Studio Code as the development environment. Deployment and testing…
“A machine that’s stopped or without raw materials is money wasted, ” and this holds true for any industry. In this sense, having real-time information about production processes allows us to control and optimize resources.
Before resorting to artificial intelligence, there are some tools to explore, such as computer vision and its basic functions available in OpenCV. With this, I developed an algorithm to detect if a conveyor belt is moving and if raw materials are being transported. This automates the preliminary phase of data ingestion in the cloud.
The prototype consisted of a conveyor belt built from recycled materials and controlled by an Arduino. I implemented the algorithm in Python with OpenCV using Visual Studio Code as the development environment. Deployment and testing were performed on a Raspberry Pi.
The result is automatic detection of the conveyor belt’s movement, recognizing if there are items on it and even counting them, as seen in the video. The next step will be to send this information to the cloud.