Carlo Guarnieri Calò Carducci

A Smart Sensor Network for Sea Water Quality Monitoring

Measurement of chlorophyll concentration is gaining more-and-more importance in evaluating the status of the marine ecosystem. For wide areas monitoring a reliable architecture of wireless sensors network is required. In this paper, we present a network of smart sensors, based on ISO/IEC/IEEE 21451 suite of standards, for in situ and in continuous space-time monitoring of surface water bodies, in particular for seawater. The system is meant to be an important tool for evaluating water quality and a valid support to strategic decisions concerning critical environment issues. The aim of the proposed system is to capture possible extreme events and collect long-term periods of data.

A Portable Optical Sensor for Sea Quality Monitoring

In this paper, we propose the modeling, the design, and the development of a high sensitivity cheap optical sensor for chlorophyll a and water transparency based on chlorophyll fluorescence and turbidity due to scattering for in situ monitoring of trophic status of seawater. The sensor is designed in order to detect very low chlorophyll concentration and low level turbidity by means of a numeric lock-in amplifier technique, with a common resonant input stage. The sensor is designed and implemented by considering a proper layout suitable for a good light source coupling. The presented prototype integrates on a board two LED sources emitting red and blue light to measure both chlorophyll-a and turbidity. The system assures a chlorophyll sensitivity of 1 mV/2.5 μg/l, a detectivity of 0.2 μg/l, with a 40-dB minimum attenuation of all the other light sources. It is attractive with respect to commercial systems because it guarantees considerable reliability with low manufacturing costs.

Fast Thermal Characterization of Thermoelectric Modules Using Infrared Camera

Thermoelectric modules are receiving more and more attention due to the increasing interest in the energy harvesting sector. The selection of the proper module for a particular application can be done comparing the values of the figure of merit, which depend on electrical parameters such as internal electrical resistance and Seebeck voltage, and the equivalent thermal resistance. Despite its importance, thermal resistance is more difficult to estimate than other parameters, as a well-engineered experimental setup is usually needed. In this paper, a new, fast, and noninvasive method based on thermal imaging techniques, to estimate the thermal resistance of thermoelectric modules, is presented. The comparison between this method and a direct measurement method based on thermocouple probes shows that very similar performance, with a small relative error, is achieved quicker, also avoiding to implement a complex measurement setup involving many temperature probes. Moreover, due to the contactless nature of the procedure, the proposed experimental setup can be easily tuned for modules of different sizes without the need to modify any mechanical part.

High Dynamic Range Power Consumption Measurement in Microcontroller-Based Applications

This paper proposes an innovative method for power consumption measurement in microcontroller-based systems that provides high accuracy on a wide dynamic range of current values, which makes it particularly suitable for all those applications characterized by alternating low-/high-power modes and fast current variations. We demonstrate that using an op-amp-based voltage feedback configuration, it is possible to use shunt resistor values higher than usual to obtain increased voltage drops without affecting the microcontrollers power supply voltage. Consequently, it is possible to directly use a data acquisition board to acquire the shunt voltage, eliminating all those common errors, like offset and gain, due to the use of an additional intermediate amplification stage. The proposed scheme has been successfully used to accurately characterize the power consumption of a single sensor node of a wireless sensor network.

An Extensive Unified Thermo-Electric Module Characterization Method

Thermo-Electric Modules (TEMs) are being increasingly used in power generation as a valid alternative to batteries, providing autonomy to sensor nodes or entire Wireless Sensor Networks, especially for energy harvesting applications. Often, manufacturers provide some essential parameters under determined conditions, like for example, maximum temperature difference between the surfaces of the TEM or for maximum heat absorption, but in many cases, a TEM-based system is operated under the best conditions only for a fraction of the time, thus, when dynamic working conditions occur, the performance estimation of TEMs is crucial to determine their actual efficiency. The focus of this work is on using a novel procedure to estimate the parameters of both the electrical and thermal equivalent model and investigate their relationship with the operating temperature and the temperature gradient. The novelty of the method consists in the use of a simple test configuration to stimulate the modules and simultaneously acquire electrical and thermal data to obtain all parameters in a single test. Two different current profiles are proposed as possible stimuli, which use depends on the available test instrumentation, and relative performance are compared both quantitatively and qualitatively, in terms of standard deviation and estimation uncertainty. Obtained results, besides agreeing with both technical literature and a further estimation method based on module specifications, also provides the designer a detailed description of the module behavior, useful to simulate its performance in different scenarios.

A MATLAB-Based Method for Designing High-Gain Resonant Transimpedance Amplifiers

In this paper, we propose a novel efficient method for the design of high-gain resonant transimpedance amplifiers (TIAs) using MATLAB. The procedure provides the designer with an effective tool, useful to explore the effects of different device parameter combinations in complex network topologies used in several application fields. We applied this method to improve the detection capability of a previously designed chlorophyll-A (Chl-A) sensor, in order to in-vivo assess the seawater quality. By exploiting the interesting bandpass behavior exhibited by a T feedback network, we were able to redesign the resonant TIA stage of a low-cost lock-in amplifier working at 1 kHz, easily increasing the gain by a factor of 100, and reaching an overall gain of 216 dB while reducing the detectivity to almost 500 fA. Moreover, the proposed analysis provides the optimal circuit parameter values for a wide working frequency range without further numerical optimization, giving an interesting perspective of its potential use in those telecommunication applications where high sensitivity is required.

An Improved DAQ-Based Method for Ferrite Characterization

In this paper, we propose an improved version of the classical volt-amperometric measurement method for the characterization of magnetic hysteresis and losses in soft magnetic cores. Using an appropriate circuital solution for the automatic cancellation of the measurement offset and a synchronous data-acquisition-based scheme for both generation and acquisition of signals, we are able to implement a high performance and low error fully automatic test system. This reduces the testing time, while allowing the use of new segmentation algorithms for the study of both major and minor hysteresis loops and the extraction of all the desired properties. We tested the system on a ferrite core, reproducing results already known from the literature with a higher degree of accuracy and reliability, and propose a test to assess the limits of applicability of the method. Energetic magnetic behavior during the formation of asymmetric minor loops is shown and discussed throughout this paper.

Corrections to “A Smart Sensor Network for Sea Water Quality Monitoring”

Presents corrections to the paper, “A smart sensor network for sea water quality monitoring,” (Adamo, F., et al; IEEE Sensors J., vol. 15, no. 5, pp. 2514–2522, May 2015).