Machine Learning in Optical Sensor Data Analysis
Chinmay Das · 2025
The application of machine learning in the process of understating optical sensor data has enhanced the degree of accuracy, as well as the speed and comprehensiveness of the results obtained. Optical sensors are employed in various fields including health care and environmental, and structural health monitoring to produce enormous and intricate data. With the help of machine learning algorithms, entrepreneurial ability can be introduced to carry out predictive analysis and modeling, and to automate the classification and analysis of data. Here, we discuss how optical sensors complement machine learning: the kind of sensors being used, the kind of data they provide, and the difficulties that arise from dealing with such data. It explains different categories of the machine learning methods that is, supervised learning, unsupervised learning, and deep learning, and use of the data from sensors. Examples are provided where the procedures are illustrated, and further research is described to show the possible developments in the field.