Sensing is an activity of paramount importance for smart cities. The coverage of large areas based on reduced infrastructure and low energy consumption is desirable. In this context, Low Power Wide Area Networks (LPWAN) play an important role. In this paper, we investigate LoRa, a low power technology offering large coverage, but low transmission rates. Radio range and data rate are tunable by using different spreading factors and coding rates, which are configuration parameters of the LoRa PHY layer. LoRa can cover large areas but variations in the environment affect link quality. This work studies the propagation of LoRa signals in forest, urban, and suburban vehicular environments. Besides being environments with variable propagation conditions, we evaluate scenarios with node mobility. To char

BACKGROUND Coffee is a raw material of global interest. Due to its relevance, this work evaluated the performance of calibration models constructed from spectral data obtained using near‐infrared spectroscopy (FT‐NIR) to determine the pH values and acidity in coffee beans in a practical and non‐destructive way. Partial least squares regression was used during the calibration and the cross‐validation to optimize the number of latent variables. The predictive capacity of the spectral pre‐processing methods was also accessed. RESULTS The results obtained showed that the best methods of pre‐processing were the first derivative for the pH variable and the standard normal variate for the acidity, which produced models with correlations of 0.78 and 0.92, ratios of prediction to deviation of 2.061 and 2.966 and biases of −0.00011 and −0.152 to test set validation, respectively. The average errors between predicted and experimental values were lower than 7%. CONCLUSIONS FT‐NIR was successfully applied to predict properties related to the quality of coffee. The method was demonstrated to be a fast and non‐destructive tool which allows the rapid inline evaluation of samples facilitating industrial and commercial processing. © 2020 Society of Chemical Industry

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