Integrated near-infrared spectral sensing

Spectral sensing is increasingly used in applications ranging from industrial process monitoring to agriculture. Sensing is usually performed by measuring reflected or transmitted light with a spectrometer and processing the resulting spectra. However, realizing compact and mass-manufacturable spectrometers is a major challenge, particularly in the infrared spectral region where chemical information is most prominent. Here we propose a different approach to spectral sensing which dramatically simplifies the requirements on the hardware and allows the monolithic integration of the sensors. We use an array of resonant-cavity-enhanced photodetectors, each featuring a distinct spectral response in the 850-1700 nm wavelength range. We show that prediction models can be built directly using the responses of the photodetectors, despite the presence of multiple broad peaks, releasing the need for spectral reconstruction. The large etendue and responsivity allow us to demonstrate the application of an integrated near-infrared spectral sensor in relevant problems, namely milk and plastic sensing. Our results open the way to spectral sensors with minimal size, cost and complexity for industrial and consumer applications.

Towards a wearable sensor for spectrally-resolved personal light monitoring

Given the large impact that the spectrum and intensity of light can have on people's health and well-being, it is of fundamental importance to understand the properties of light received under normal living conditions. Historically, as research into the biological responses of light has traditionally focused on laboratory studies with controlled lighting conditions, little is known about people's light exposure outside of experimental environments. Spectrace is the first wearable compressive spectrometer designed for continuous spectral light tracking in everyday environments. This paper presents the sensor and its evaluation based on wearability considerations and three performance criteria: 1) its accuracy (in terms of spectral sensing capability), 2) its reliability (notably as far as directional response is concerned), and 3) its adaptability to the large dynamics of ambient conditions. Results show the potential use of the newly developed sensor for chronobiological studies and beyond.

Development of technique of remote spectral sensing of technogenically loaded territories

Introduction. The article considers the problem of monitoring technologically loaded landscapes. To solve it, the authors proposed an innovative method for studying the chemical composition of objects using direct spectral sensing means. Problem Statement. The objective of this study is to consider the possibility of using spectral sensing to control the composition of soils in technogenically loaded territories. Practical Part. To confirm the hypothesis that observing changes in the parameters of reflection spectra in non-selective areas will make it possible to establish the presence of basic biogenic macroelements for plants in the soil and evaluate its fertility, or determine the degree of contamination of the territory, a laboratory experiment was conducted using modern spectral equipment and multidimensional data calibration was performed. Conclusion. The results of the analysis show the fundamental possibility of using spectral sensing in the monitoring of technogenically loaded territories using methods of multidimensional data analysis.

Advanced Optical Technologies in Food Quality and Waste Management

Food waste is a global problem caused in large part by premature food spoilage. Seafood is especially prone to food waste because it spoils easily. Of the annual 4.7 billion pounds of seafood destined for U.S. markets between 2009 and 2013, 40 to 47 percent ended up as waste. This problem is due in large part to a lack of available technologies to enable rapid, accurate, and reliable valorization of food products from boat or farm to table. Fortunately, recent advancements in spectral sensing technologies and spectroscopic analyses show promise for addressing this problem. Not only could these advancements help to solve hunger issues in impoverished regions of the globe, but they could also benefit the average consumer by enabling intelligent pricing of food products based on projected shelf life. Additional technologies that enforce trust and compliance (e.g., blockchain) could further serve to prevent food fraud by maintaining records of spoilage conditions and other quality validation at all points along the food supply chain and provide improved transparency as regards contract performance and attribution of liability. In this chapter we discuss technologies that have enabled the development of hand-held spectroscopic devices for detecting food spoilage. We also discuss some of the analytical methods used to classify and quantify spoilage based on spectral measurements.

Load monitoring of a cantilever plate by a novel multimodal fibre optic sensing configuration

Optical fibre sensors and in particular fibre Bragg gratings (FBG) have received a lot of interest for Structural Health Monitoring in different application fields, such as aerospace, pipeline and civil engineering. FBGs are conventionally used to monitor strain and sometimes temperature. In this paper, we propose a new method for load monitoring of a cantilever plate subjected to point loading. The bending of plate is complex due to the interaction between the axial and transverse bending stiffnesses of the material. We use a novel algorithm for interrogating fibre Bragg grating sensors based on both hybrid interferometry and FBG spectral sensing. The method is demonstrated in this paper using a single-mode optical fibre containing four FBG sensors to estimate both the point loading position and the loading magnitude at an arbitrary location on a 1 m$$^{2}$$ 2 cantilever plate. The algorithm first utilizes point strain information through spectral sensing as well as strain from interferometric sensing over a long path. The gratings are interrogated using Wavelength Division Multiplexing (WDM). We calibrated the system using an experimental model. This model was then verified by using single point static loading tests and comparing the calculated sensing position with the actual position. The method achieved a good estimation of loading position achieving a measurement error of about 9% in a 2D plane. The analysis discusses the possible sources of inaccuracies. This study forms the basis of our future work involving morphing smart-wing sections for the purpose of load monitoring. Article highlights A new optical sensing configuration is demonstrated for load and structural health monitoring of cantilever structures. The algorithm successfully estimates the position of an arbitrary load on a cantilever plate, with an error of 9%. This methodology will be extended to monitor more complex structures, in- cluding morphing aircraft wing sections.