Advancements in Photonic Sensors and Their Applications

Dear Colleagues,

Technological innovations and applications drive progress in photonic sensors. Technological innovations have led to the development of new and improved photonic sensor head designs. These heads may utilize either standard or advanced photonic technologies, categorized according to various classifications. Photonic sensors for interacting with the examined medium can utilize single phenomena such as reflection, refraction, or attenuation of the optical signal, as well as combinations of phenomena in terms of the area of interaction and the combination of monitored phenomena, e.g., reflection and attenuation. Thus, the detection of the optical signal can be single, multi, or multipath, and the information can be of a single wavelength of optical light or the entire spectrum. Using standard photonic technologies often means applying mature and advanced electronic technologies to the development of the head and integrating detection circuits into multi-channel detector arrays. Therefore, progress in developing new photonic sensor applications is often related to the methods of processing received information. An interesting and significant area here is the increasingly widespread use of approaches related to machine learning, including the formalization of the sensor head's classification of measurement results into a form understandable to the sensor's end user. It should be noted that photonic sensors are often used as essential modules in interesting control and measurement systems, the names of which are related to the primary function being performed. Such applications are associated with dedicated integration and information processing methods, which I also believe is worth noting.

In this special edition, I aim to highlight the importance of integrating photonic technology with information processing methods, including machine learning techniques, in the development of photonic sensor applications.

Dr. Michal Borecki
Guest Editor

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• photonic sensors
• photonic sensing systems
• control and measurement systems
• inforamtion prosessing
• machine learning
• applications