This paper presents a compact and modular system based on Internet-of- Things for monitoring cattle behavior and stress in real-time. It will help to model certain parameters such as temperature and certain weather variables such as relative humidity, solar radiation, among others thanks to Internet-of- Things (IoT) sensors localized in different points of barns and the fields for cattle farming. A main benefit of the system is that it is built with low-cost hardware and low battery consumption. The wireless system also allows the collection of data in real-time and obtains the temperature-humidity index. This index will give an approach to the heat stress in cattle not only on the farm but in the vicinity of the farm. Finally, the high amount of collected data will allow employing Big Data solutions for estimating the impact on milk productivity. In the future, more sensors will be deployed for a more detailed reading of weather variables and their impact on dairy cattle.

Many authors have been working on approaches that can be applied to social robots to allow a more realistic/comfortable relationship between humans and robots in the same space. This paper proposes a new navigation strategy for social environments by recognizing and considering the social conventions of people and groups. To achieve that, we proposed the application of Delaunay triangulation for connecting people as vertices of a triangle network. Then, we defined a complete asymmetric Gaussian function (for individuals and groups) to decide zones where the robot must avoid passing. Furthermore, a feature generalization scheme called socialization feature was proposed to incorporate perception information that can be used to change the variance of the Gaussian function. Simulation results have been presented to demonstrate that the proposed approach can modify the path according to the perception of the robot compared to a standard A* algorithm.

High directivity and large bandwidth directional couplers are foreseen in future electronic systems. These devices are expected in measurement, monitoring, control and protection applications. In this work, a novel design methodology of a directional coupler using microstrip technology is proposed. This design is based on traditional coupled line theory enhanced with capacitive compensation and matching network. Using this methodology, a directional coupler is implemented in microstrip technology using FR4 substrate obtaining a large bandwidth (ranging from 1 GHz to 8 GHz) and a directivity better than 20 dB.

In order to increase agricultural productivity, it is necessary to manage the nutrients that the plants receive. In this sense, nitrogen is one of the most important nutrients for the adequate development and growth of plants and whose control contributes to the conservation of the environment. Traditionally, the quantification of nitrates is performed employing methods such as ion chromatography conducted in a laboratory, which leads to problems such as processing time, complexity in the analysis process itself and the need to have people trained to handle such analysis equipment. To alleviate these difficulties, some sensors use electrochemical principles; however, they present several limitations such as manufacturing complexity, cost, and difficulties in conducting real-time measurements. On the other hand, capacitive sensors have also been developed whose operating principle is based on analyzing the changes in the electrical characteristics of these devices produced by variations in the environment surrounding the sensor. For example, solutions with different concentrations of nitrates will produce an alteration of the electric field generated by the electrodes of the capacitor, producing changes in parameters such as its electrical impedance. However, the materials used to manufacture these sensors are metals, being unattractive for agricultural applications due to the corrosion they may suffer. To counteract this problem, it is possible to use other types of materials, among which graphene emerge as it has been shown to have excellent properties such as being a mechanically strong material and presenting good electrical conductivity. For this reason, in this work, the study of the sensitivity of a graphene-based interdigital capacitive sensor applied to the measurements of nitrate concentrations is performed. Different analytical methods were used. In general, the interdigital capacitive sensor shows repeatability in the measurements, especially for concentrations greater than 10 ppm with variability of . Also, parameters such as the detection limit of the sensor were calculated, the result of which was 1.71 ppm. Also, measurements were made on agricultural soil samples showing differences in readings with respect to the ion chromatography method. Differences that are attributable to the different methodologies used in the calculation of the nitrate concentration and the fertilization process that was applied to the crop field a few weeks before. Despite the difference between the sensor measurements and the results obtained by ion chromatography, both procedures showed a high amount of nitrate concentration.

This paper explores the development of a low-cost instrument using a similar architecture to a one-port vector receiver intended for estimating Arsenic (As) ions diluted in water. The instrument is implemented with modular off-the-shelf-components. The measurements are performed with the designed prototype connected to a dielectric assessment kit 3.5 from Schmidt Partner Engineering AG and are compared for different levels of Arsenic solved in water. The preliminary results obtained are promising to continue the study of this instrumentation and pave the way to develop further sensor and instrumentation for water-sensing and monitoring applications.