José Pelegri-Sebastia

Low-Cost Capacitive Humidity Sensor for Application Within Flexible RFID Labels Based on Microcontroller Systems

This paper reports on the fabrication of a capacitive-type relative humidity (RH) sensor using screen printing processes for electrode film deposition. The applied measurement method based on microcontrollers is also reported. In this specific case, the microcontroller is used to measure RH by means of a capacitive sensor with a simple low-cost electronic system. In addition, a comparison between two different types of polyester substrates [Melinex (DuPont) and CG3460 (3M)] is shown. Both polyester substrates have similar properties, and only the thickness is different (175 μm for Melinex and 100 μm for CG3460). A nonlineal response has been obtained in this type of sensors. In order to linearize the response and reduce the external hardware, an artificial neural network embedded into the microcontroller has been used.

A Method for Modeling the Battery State of Charge in Wireless Sensor Networks

In this paper, we propose a method for obtaining an analytic model of the battery state-of-charge in wireless sensor nodes. The objective is to find simple models that can be used to estimate accurately the real battery state and consequently the node lifetime. Running the model in the network nodes, we can provide the motes with the required information to implement applications that can be considered as battery-aware. The proposed methodology reduces the computational complexity of the model avoiding complicated electrochemical simulations and treating the battery as an unknown system with an output that can be predicted using simple mathematical models. At a first stage, during a setup period, the method starts with the measurement of several battery parameters under different environmental and operational conditions. After that, the method uses the previous collected data for building mathematical models, considering the linear regression or multilayer perceptron as the most appropriated. Finally, the models are validated experimentally with new measures. Results show the suitability of the method that produces accurate and simple models, capable of being implemented even in low cost and very constrained real motes.

Glucose detection in human sweat using an electronic nose

In the last years attempts to develop a non-invasive glucose system based on the glucose levels in sweat have been studied. In this paper, 32 metal oxide semiconductor (MOS) sensors operating at different temperatures have been used to develop a multisensor olfactory system that allows to study the glucose levels in sweat. In order to develop repeatable experiments, artificial sweat at different glucose concentrations were developed in the laboratory. The obtained results suggest high viability of the approach. Although, the sensitivity of the sensors system needs to be improved.

E-nose application to food industry production

Food companies worldwide must constantly engage in product development to stay competitive, cover existing markets, explore new markets, and meet key consumer requirements. This ongoing development places high demands on achieving quality at all levels, particularly in terms of food safety, integrity, quality, nutrition, and other health effects. Food product research is required to convert the initial product idea into a formulation for upscaling production with ensured significant results. Sensory evaluation is an effective component of the whole process. It is especially important in the last step in the development of new products to ensure product acceptance. In that stage, measurements of product aroma play an important role in ensuring that consumer expectations are satisfied. To this end, the electronic nose (e-nose) can be a useful tool to achieve this purpose. The e-nose is a combination of various sensors used to detect gases by generating signals for an analysis system. Our research group has investigated the scent factor in some foodstuff and attempted to develop e-noses based on low-cost technology and compact size. In this paper, we present a summary of our research to date on applications of the e-nose in the food industry.

Modeling of Photovoltaic Cell Using Free Software Application for Training and Design Circuit in Photovoltaic Solar Energy

There are numerous studies that develop the mathematical modeling of photovoltaic cells and verified by software, for example [1] or [2]. The model presented is based on an equiva‐ lent circuit implemented in free software. Free software used is Quite Universal Circuit Sim‐ ulator (QUCS), [3]. QUCS uses a generic diode for adjust the current and voltage curve (IV curve) at photovoltaic cell. Additionally, you can use equations to define the model of pho‐ tovoltaic cell and represent the characteristic curves on the same page, [4]. QUCS is a multi‐ platform application that runs on Windows and Linux, this software is available in Linux distributions for electronics. [5].

A Dual-Band Antenna for RF Energy Harvesting Systems in Wireless Sensor Networks

This work was supported in part by EMMAG Program 2014. The tests have been performed under the collaboration with the Electromagnetic Radiation Laboratory (GRE Lab) of the UPV.

Development of the MOOSY4 eNose IoT for Sulphur-Based VOC Water Pollution Detection

In this paper, we describe a new low-cost and portable electronic nose instrument, the Multisensory Odor Olfactory System MOOSY4. This prototype is based on only four metal oxide semiconductor (MOS) gas sensors suitable for IoT technology. The system architecture consists of four stages: data acquisition, data storage, data processing, and user interfacing. The designed eNose was tested with experiment for detection of volatile components in water pollution, as a dimethyl disulphide or dimethyl diselenide or sulphur. Therefore, the results provide evidence that odor information can be recognized with around 86% efficiency, detecting smells unwanted in the water and improving the quality control in bottled water factories.

Radio Frequency Energy Harvesting - Sources and Techniques

Energy harvesting technology is attracting huge attention and holds a promising future for generating electrical power. This process offers various environmentally friendly al‐ ternative energy sources. Especially, radio frequency (RF) energy has interesting key at‐ tributes that make it very attractive for low-power consumer electronics and wireless sensor networks (WSNs). Ambient RF energy could be provided by commercial RF broadcasting stations such as TV, GSM, Wi-Fi, or radar. In this study, particular attention is given to radio frequency energy harvesting (RFEH) as a green technology, which is very suitable for overcoming problems related to wireless sensor nodes located in harsh environments or inaccessible places. The aim of this paper is to review the progress ach‐ ievements, the current approaches, and the future directions in the field of RF harvesting energy. Therefore, our aim is to provide RF energy harvesting techniques that open the possibility to power directly electronics or recharge secondary batteries. As a result, this overview is expected to lead to relevant techniques for developing an efficient RF energy harvesting system.

Method for measuring internal resistance of batteries in WSN

In real Wireless Sensor Networks applications is very important to take into account the current battery state of health. A parameter that can provide significant information of the battery state is its internal resistance. For estimating the internal resistance, we assume a simple battery model composed of a source voltage and an internal resistor. This model is suitable for being implemented in low-cost motes with very limited computational capabilities. The procedure of estimating this value involves the acquisition of battery voltages and drained currents during the execution of a typical WSN application. We take advantage of the run-time execution of the program for measuring several voltages with different currents. Thus, the program measures the voltage and current when the system is in high power state (the radio is on) and in low power state (the radio is off). The method has been validated with real experiments with Telosb motes providing good results at different environmental conditions.

A method for obtaining dependence mathematical models from graphics in chemical sensors

In this paper, we try to solve a problem attached to the electronic design. When working with sensors, environmental conditions such as temperature and relative humidity must be taken into account because they affect the behaviour of the sensor, and the deviations must be corrected. Often the sensor manufacturers not provide clearly this information. In many cases only is provided a graph of the variability of the sensor according to physical parameters. So the designer has to find their own method of compensation. In this work is presented a simple procedure for obtaining mathematical models which relates the variation of the sensor (in this case resistive) with physical parameters to be corrected. The procedure could be extrapolated to any system in which one have to obtain a mathematical model from a graph. A high degree of resolution has been achieved considering information provided by the manufacturer, in the particular case of electrochemical sensors.