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We have developed a sensing system that utilizes a low-cost computer (Raspberry Pi) and its imaging camera as an optical sensing core for the continuous detection of NO₂in the air (PiSENS-A). 

In this paper, we demonstrate the suitability, sensitivity, and precision of low‐cost and easy‐to‐use ion‐selective electrodes (ISEs) for concurrent detection of NH4+ and NO3‐ in soil and water by technical and non‐technical end‐users to enable efficient soil and water management exposed to chronic reactive nitrogen loading. We developed a simplified methodology for sample preparation followed by the demonstration of an analytical methodology resulting in improvements of sensitivity and precision of ISEs. Herein, we compared and contrasted ISEs with traditional laboratory‐based technique such as Flow Injection Analysis (FIA) and portable colorimetric assay followed by comparisons of linear regression and Bayesian nonlinear calibration approaches applied on both direct potentiometry and standard addition modes of analysis in terms of in‐field applications and improvement of sensitivity and precision. The ISEs were validated for sensing on a range of ambient soil and water samples representing a range of NH4+ and NO3‐ concentrations from pristine to excessive saturation conditions. Herein developed methodology showed excellent agreement with lab‐based and portable analytical techniques while demonstrating improvements in precision and sensitivity analysis illustrated by a decrease in confidence intervals by 50‐60%. We also demonstrated the utilization of the entire ISE response curve thus removing the biases originating from linear approximation which is often currently employed. Therefore, we show that ISEs are robust yet low cost and an easy to use technology that can enable high‐frequency measurement of mineral N and help to improve our understanding of N transformation processes as influenced by soil management, fertilization, land use, and climate change. 

We report on the development of a simple and cost-effective potentiometric sensor array that is based on manual “drawing” on the polymeric support with the pencils composed of graphite and different types of zeolites. The sensor array demonstrates distinct sensitivity towards a variety of inorganic ions in aqueous media. This multisensor system has been successfully applied to quantitative analysis of 100 real-life surface waters sampled in Mahananda and Hooghly rivers in the West Bengal state (India). Partial least squares regression has been utilized to relate responses of the sensors to the values of different water quality parameters. It has been found that the developed sensor array, or electronic tongue, is capable of quantifying total hardness, total alkalinity, and calcium content in the samples, with the mean relative errors below 18%.