April 29th 2025
New research highlights how remote satellite sensing technologies are changing the way scientists monitor inland water quality, offering powerful tools for tracking pollutants, analyzing ecological health, and supporting environmental policies across the globe.
LIBS Illuminates the Hidden Health Risks of Indoor Welding and Soldering
April 23rd 2025A new dual-spectroscopy approach reveals real-time pollution threats in indoor workspaces. Chinese researchers have pioneered the use of laser-induced breakdown spectroscopy (LIBS) and aerosol mass spectrometry to uncover and monitor harmful heavy metal and dust emissions from soldering and welding in real-time. These complementary tools offer a fast, accurate means to evaluate air quality threats in industrial and indoor environments—where people spend most of their time.
Smarter Sensors, Cleaner Earth Using AI and IoT for Pollution Monitoring
April 22nd 2025A global research team has detailed how smart sensors, artificial intelligence (AI), machine learning, and Internet of Things (IoT) technologies are transforming the detection and management of environmental pollutants. Their comprehensive review highlights how spectroscopy and sensor networks are now key tools in real-time pollution tracking.
New AI Strategy for Mycotoxin Detection in Cereal Grains
April 21st 2025Researchers from Jiangsu University and Zhejiang University of Water Resources and Electric Power have developed a transfer learning approach that significantly enhances the accuracy and adaptability of NIR spectroscopy models for detecting mycotoxins in cereals.
Illuminating Robotics and the Role of Optical Sensors in Continuum Robots
March 19th 2025A recent review published in Sensors explores the dynamic field of continuum robotics, with a particular focus on the advances in optical sensing technologies. The study, led by researchers from the Technical University of Košice and the University of Texas at Austin, highlights the dominance of optical fiber sensors in tracking robotic shape perception and environmental interactions, demonstrating spectroscopic applications and future potential.
New Fluorescence Model Enhances Aflatoxin Detection in Vegetable Oils
March 12th 2025A research team from Nanjing University of Finance and Economics has developed a new analytical model using fluorescence spectroscopy and neural networks to improve the detection of aflatoxin B1 (AFB1) in vegetable oils. The model effectively restores AFB1’s intrinsic fluorescence by accounting for absorption and scattering interferences from oil matrices, enhancing the accuracy and efficiency for food safety testing.
Advanced Optical Fiber Sensor Enhances Wind Turbine Vibration Monitoring
March 5th 2025Researchers have developed a high-sensitivity optical fiber vibration sensor based on Fabry-Perot (F-P) interference, designed to improve wind turbine tower monitoring. This innovation addresses issues with traditional electrical sensors and has strong potential for integration into the Internet of Things (IoT) for real-time structural health monitoring.
Smart Farming Using AI, IoT, and Remote Sensing
March 4th 2025A study by researchers at Universidad de Talca in Chile explores the integration of artificial intelligence (AI), the Internet of Things (IoT), and remote sensing to modernize modern farming. The research highlights how these technologies optimize resource use, improve crop yields, and promote sustainable agricultural practices.
Transforming Connectivity with a Comprehensive Review of IoT Sensors
March 3rd 2025A recent review by researchers at Nagpur University and Seth Kesarimal Porwal College explores the ever advancing landscape of the Internet of Things (IoT) and its essential components—sensors and actuators. The review paper classifies various IoT sensors and examines their role in integrating the physical and digital worlds to enable smarter devices and enhanced automation.
IoT-based Spectral Sensing Brings Real-Time Grape Ripeness Monitoring to Vineyards
February 26th 2025A team of researchers from the International Iberian Nanotechnology Laboratory (INL) in Braga, Portugal, has developed an autonomous Internet of Things (IoT) spectral sensing system designed to monitor grape ripening in real-time. The study, led by Hugo M. Oliveira, Alessio Tugnolo, Natacha Fontes, Carlos Marques, and Álvaro Geraldes, was published in Computers and Electronics in Agriculture and introduces a novel approach to non-destructive, in-situ optical monitoring of grape maturity.
Smarter Cities Using IoT with Optical Sensors to Drive Urban Sustainability
Published: February 25th 2025 | Updated: February 25th 2025A new study examines the role of Internet of Things (IoT) technology in fostering sustainable urban development. Through a systematic review of 73 publications, researchers highlight how IoT-enabled sensors improve air quality, transportation, disaster management, and resource efficiency in smart cities.
Smart Farming and How IoT and Sensors are Changing Agriculture
Published: February 24th 2025 | Updated: February 24th 2025Researchers highlight the growing role of Internet of Things (IoT) and sensor technologies in enhancing food security and agricultural sustainability. The study, published in Ain Shams Engineering Journal, explores the applications, benefits, and challenges of smart agriculture, emphasizing the potential of optical sensors in monitoring and optimizing farming practices.
From Classical Regression to AI and Beyond: The Chronicles of Calibration in Spectroscopy: Part I
February 14th 2025This “Chemometrics in Spectroscopy” column traces the historical and technical development of these methods, emphasizing their application in calibrating spectrophotometers for predicting measured sample chemical or physical properties—particularly in near-infrared (NIR), infrared (IR), Raman, and atomic spectroscopy—and explores how AI and deep learning are reshaping the spectroscopic landscape.
Improving Citrus Quality Assessment with AI and Spectroscopy
February 13th 2025Researchers from Jiangsu University review advancements in computer vision and spectroscopy for non-destructive citrus quality assessment, highlighting the role of AI, automation, and portable spectrometers in improving efficiency, accuracy, and accessibility in the citrus industry.
Advancing Near-Infrared Spectroscopy and Machine Learning for Personalized Medicine
February 12th 2025Researchers have developed a novel approach to improve the accuracy of near-infrared spectroscopy (NIRS or NIR) in quantifying highly porous, patient-specific drug formulations. By combining machine learning with advanced Raman imaging, the study enhances the precision of non-destructive pharmaceutical analysis, paving the way for better personalized medicine.
New Method for Detecting Fentanyl in Human Nails Using ATR FT-IR and Machine Learning
February 11th 2025Researchers have successfully demonstrated that human nails can serve as a reliable biological matrix for detecting fentanyl use. By combining attenuated total reflectance-Fourier transform infrared (ATR FT-IR) spectroscopy with machine learning, the study achieved over 80% accuracy in distinguishing fentanyl users from non-users. These findings highlight a promising, noninvasive method for toxicological and forensic analysis.