In many countries, water quality monitoring is limited due to the high cost of logistics and professional equipment such as multiparametric probes. However, low-cost sensors integrated with the Internet of Things can enable real-time environmental monitoring networks, providing valuable water quality information to the public. To facilitate the widespread adoption of these sensors, it is crucial to identify which sensors can accurately measure key water quality parameters, their manufacturers, and their reliability in different environments. Although there is an increasing body of work utilizing low-cost water quality sensors, many questions remain unanswered. To address this issue, a systematic literature review was conducted to determine which low-cost sensors are being used for remote water quality monitoring. The results show that there are three primary vendors for the sensors used in the selected papers. Most sensors range in price from US$6.9 to US$169.00 but can cost up to US$500.00. While many papers suggest that low-cost sensors are suitable for water quality monitoring, few compare low-cost sensors to reference devices. Therefore, further research is necessary to determine the reliability and accuracy of low-cost sensors compared to professional devices.

Ultrasonic inspection techniques and non-destructive tests are widely applied in evaluating products and equipment in the oil, petrochemical, steel, naval, and energy industries. These methods are well established and efficient for inspection procedures at room temperature. However, errors can be observed in the positioning and sizing of the flaws when such techniques are used during inspection procedures under high working temperatures. In such situations, the temperature gradients generate acoustic anisotropy and consequently distortion of the ultrasonic beams. Failure to consider such distortions in ultrasonic signals can result, in extreme situations, in mistaken decision making by inspectors and professionals responsible for guaranteeing product quality or the integrity of the evaluated equipment. In this scenario, this work presents a mathematical tool capable of mitigating positioning errors through the correction of focal laws. For the development of the tool, ray tracing concepts are used, as well as a model of heat propagation in solids and an experimentally defined linear approximation of dependence between sound speed and temperature. Using the focal law correction tool, the relative firing delays of the active elements are calculated considering the temperature gradients along the sonic path, and the results demonstrate a reduction of more than $68\%$ in the error of flaw positioning.

Control of pressure changes within the well during the drill string tripping is challenging. Tripping the drill string at high speeds and accelerations can produce significant pressure changes, causing the well’s inner pressure to fall beyond safe operating limits, and conversely, adopting conservative pipe speeds results in a waste of operational and financial resources. This work proposes a velocity control model for drill string axial moves during well drilling operations, aiming to reduce non-productive time (NPT) and considering operational limitations, constraints imposed on the operational pressure window, and safety requirements. The proposed optimization admits that the fluid flow caused by pipe motion is compressible and transient. As a result, the model generates tripping acceleration and velocity profiles to keep pressure gradients within the operating window. Simulation results using the inner-point method show that the developed model effectively reduces operating tripping time while satisfying the operational constraints.

Low-cost sensors integrated with the Internet of Things can enable real-time envi-ronmental monitoring networks and provide valuable water quality informationto the public. However, the accuracy and precision of the values measured bythe sensors are critical for widespread adoption. In this study, 19 different low-cost sensors, commonly found in the literature, from four different manufacturersare tested for measuring five water quality parameters: pH, dissolved oxygen,oxidation-reduction potential, turbidity, and temperature. The low-cost sensorsare evaluated for each parameter by calculating the error and precision com-pared to a typical multiparameter probe assumed as a reference. The comparisonwas performed in a controlled environment with simultaneous measurements ofreal water samples. The relative error ranged from -0.33 to 33.77% and most of them were ≤ 5%. The pH and temperature were the ones with the most accurate results. In conclusion, low-cost sensors are a complementary alternative toquickly detect changes in water quality parameters. Further studies are necessaryto establish a guideline for the operation and maintenance of low-cost sensors.