ML model and data processing pipeline for manufacturing
Project for image analysis using ML to detect harmful emissions in manufacturing

Project definition
Location
North America
Client
Furniture factory
Industry
Manufacturing and energy
Project type
ML model
Service list
ML Engineering / Computer Vision
Problem
The main task of this project was to develop an ML model capable of detecting and annotating smoke coming from factory chimneys in images. In addition to the model itself, a data pipeline needed to be implemented to process a large number of surveillance camera images in real-time for smoke detection. The model was trained using manually annotated data with images of smoke coming from chimneys in various weather conditions
Solution
The model and data pipeline were successfully implemented at various client factories in North America. The solution enabled real-time monitoring of factory conditions, alerting to unforeseen situations related to the emission of harmful substances into the air, as well as detecting emergency situations. With a model accuracy of 81%, the system reduced the number of incorrect decisions made by personnel and allowed the implementation of an external automated system for starting and stopping production based on the situation assessment
- Python
- Azure
- Apache
- OpenCV
- numpy PyTorch
Project highlights
Highlights of the developed ML model
01
Data processing from 150 cameras
Developed a data pipeline capable of processing a large number of images from 150 cameras in real-time
02
81%
The accuracy of the ML model recognition is 81%

Technologies
Python
Azure
Apache
OpenCV
numpy PyTorch
Our workflow
Development Process
In FTECH-IT we have a cohesive team of professionals across various IT fields, enabling us to handle projects end-to-end without needing external specialists. No matter how complex the project is, all you need to provide is the idea — FTECH-IT will take care of everything else

ML model and data processing pipeline for manufacturing
Project for image analysis using ML to detect harmful emissions in manufacturing