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When the COMS camera of optical camera communication (OCC) system acquired the information image, the grayscale value of pixels fluctuated due to the influence of blooming effect and light noise, so that the data logic could not be correctly judged by the decision threshold, which affected the bit error rate (BER) performance transmission distance and data rate, and degraded the system performance. In this paper, the adaptive exponential weighted moving average algorithm is proposed, and the optimal grayscale value matrix of signal demodulation is verified by experiment, so as to reduce the fluctuation of grayscale value and improve the performance of OCC system. The experimental results show that for data processing and analysis based on ZYNQ7020 experimental platform, a 7% forward error correction（BER = 3.8 × 10−3）requirements can be satisfied at 150 cm when the data rate is 3 Kbps, and a 7% forward error correction（BER = 3.8 × 10−3）requirements can be satisfied at 100 cm when the data rate is 5 Kbps. [ABSTRACT FROM AUTHOR]

Routine, remote, and process analysis for foodstuffs is gaining attention and can provide more confidence for the food supply chain. A new generation of rapid methods is emerging both in the literature and in industry based on spectroscopy coupled with AI-driven modelling methods. Current published studies using these advanced methods are plagued by weaknesses, including sample size, abuse of advanced modelling techniques, and the process of validation for both the acquisition method and modelling. This paper aims to give a comprehensive overview of the analytical challenges faced in research and industrial settings where screening analysis is performed while providing practical solutions in the form of guidelines for a range of scenarios. After extended literature analysis, we conclude that there is no easy way to enhance the accuracy of the methods by using state-of-the-art modelling methods and the key remains that capturing good quality raw data from authentic samples in sufficient volume is very important along with robust validation. A comprehensive methodology involving suitable analytical techniques and interpretive modelling methods needs to be considered under a tailored experimental design whenever conducting rapid food analysis. [ABSTRACT FROM AUTHOR]

A mid-level data fusion coupled with multivariate analysis approach is applied to dual-platform mass spectrometry data sets using Rapid Evaporative Ionization Mass Spectrometry and Inductively Coupled Plasma Mass Spectrometry to determine the correct classification of salmon origin and production methods. Salmon (n = 522) from five different regions and two production methods are used in the study. The method achieves a cross-validation classification accuracy of 100% and all test samples (n = 17) have their origins correctly determined, which is not possible with single-platform methods. Eighteen robust lipid markers and nine elemental markers are found, which provide robust evidence of the provenance of the salmon. Thus, we demonstrate that our mid-level data fusion - multivariate analysis strategy greatly improves the ability to correctly identify the geographical origin and production method of salmon, and this innovative approach can be applied to many other food authenticity applications., (© 2023. The Author(s).)