Smart Spectral Sensors for Aquatic Environments II
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".
Deadline for manuscript submissions: closed (10 July 2022) | Viewed by 379
Special Issue Editor
2. German Research Center for Artificial Intelligence (DFKI), Marine Perception Research Group, Oldenburg, Germany
Interests: marine optics and physics; marine sensors; detection of biogeochemical parameters and hazardous substances; autonomous long-term sensor systems and observatories; comprehensive perception; artificial intelligence; data stream mining; event detection; situational awareness
Special Issue Information
Dear Colleagues,
A new generation of spectral sensors and sensor systems for pollution detection and biogeochemical observations in aquatic environments is being born. These optical sensors are showing not only improved measurement capabilities, but also enhanced sensor data evaluation and integration functionalities, e.g., hyperspectral radiometers that perform embedded data analysis, multispectral imaging sensors with in-built feature characterization, or multimodal ad hoc sensor systems that collaboratively perform risk assessment. With improved embedded computational capacities, the ascent of machine learning, data stream mining, and other algorithmic approaches at hand, smart spectral sensors can be realized for more comprehensive assessment and protection of marine environments, inland water, as well as other water-related processes.
I am proud to announce this Special Issue entitled “Smart Spectral Sensors for Aquatic Environments”. It is an effort to include the most relevant work on state-of-the-art as well as upcoming smart spectral sensors and sensor systems. It highlights not only research on improved performance but also the higher level of integration and embedded intelligence that allow the realization of complex tasks as part of a more complete aquatic environmental situational awareness.
Prof. Dr. Oliver Zielinski
Guest Editor
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Keywords
- smart optical sensors
- multimodal sensor systems
- multispectral and hyperspectral sensing
- spectral imaging
- aquatic environmental sensing
- in situ and remote sensing
- marine hazard detection, e.g., oil spills or harmful algae blooms
- water pollutants, e.g., plastic waste or excessive nutrients
- biogeochemistry of natural water bodies
- operational observation
- real-time event and trend detection
- data stream mining and machine learning
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