Development of a gas nanosensor node powered by solar cells

This work focuses on the development of a stand-alone gas nanosensor node, powered by solar energy to track concentration of polluted gases such as NO2, N2O, and NH3. Gas sensor networks have been widely developed over recent years, but the rise of nanotechnology is allowing the creation of a new range of gas sensors [1] with higher performance, smaller size and an inexpensive manufacturing process. This work has created a gas nanosensor node prototype to evaluate future field performance of this new generation of sensors. The sensor node has four main parts: (i) solar cells; (ii) control electronics; (iii) gas sensor and sensor board interface [2-4]; and (iv) data transmission. The station is remotely monitored through wired (ethernet cable) or wireless connection (radio transmitter) [5, 6] in order to evaluate, in real time, the performance of the solar cells and sensor node under different weather conditions. The energy source of the node is a module of polycrystalline silicon solar cells with 410cm2 of active surface. The prototype is equipped with a Resistance-To-Period circuit [2-4] to measure the wide range of resistances (KΩ to GΩ) from the sensor in a simple and accurate way. The system shows high performance on (i) managing the energy from the solar panel, (ii) powering the system load and (iii) recharging the battery. The results show that the prototype is suitable to work with any kind of resistive gas nanosensor and provide useful data for future nanosensor networks

Application of an ANFIS Algorithm to Sensor Data Processing

Some sensors require frequent recalibrations; therefore, calibration cost must be limited. In this paper, a new calibration technique is presented. It is a two-phase method which is based on adaptive neuro-fuzzy networks, and it shows superior performances with respect to traditional algorithms, requiring fewer calibration points and less computational power in the recalibration phase. Feasibility has been demonstrated with a pyroelectric biaxial positioning system, reaching performance to the limit of the adopted test bench, on the order of 20 um with respect to a whole sensible area of 7 mm x 7 mm

Evaluation of the Use of Class B LoRaWAN for the Coordination of Distributed Interface Protection Systems in Smart Grids

The adoption of the distributed generation paradigm is introducing several changes in the design and operation of modern distribution networks. Modern grid codes are becoming more and more complex, and the adoption of smart protection systems is becoming mandatory. However, the adoption of newer and smarter units is only half of the story. Proper communication networks must be provided as well, and the overall costs may become critical. In this work, the adoption of the Long-Range Wide Area Network (LoRaWAN) technology is suggested as a viable approach to implement the coordination of Interface Protection Systems. A proper communication architecture based on the LoRaWAN Class B technology was proposed and evaluated in order to assess its feasibility for the considered application. A scalability analysis was carried out, by computing the number of devices that can be handled by a single LoRaWAN Gateway (GW) and the maximum expected time of response between a triggering event and the arrival of the related coordination command. The results of the study showed that up to 312 devices can be managed by a single GW, by assuring a maximum response time of 22.95 s. A faster maximum response time of 6.2 s is also possible by reducing the number of managed devices to 12

Denoising ECG Signal by CSTFM Algorithm: Monitoring During Motorbike and Car Races

mHealth technology, by using habitual devices, i.e., smartphones, improves prevention, diagnosis, treatment, monitoring, and management of health. Monitoring heart profile during intense sports activities allows to diagnose pathologies, not identifiable with the traditional Holter approach and, therefore, it can help preventing possible injuries. On the other hand, denoising and extracting features from electrocardiographic (ECG) signal acquired during physical activity is a challenging task due to motion artifacts and measurement noise. In this paper, we propose a solution enabling a complete analysis of ECG signal through the implementation of a robust denoising algorithm, which has been characterized on synthetic signals and then has been tested on real traces acquired with a low-cost smartphone-based device during motorbike and car races

Fast, Versatile, and Low-Cost Interface Circuit for Electrochemical and Resistive Gas Sensor

6nononenoneDEPARI A.; FLAMMINI A.; SISINNI E.; DE MARCELLIS A.; FERRI G.; MANTENUTO P.Depari, Alessandro; Flammini, Alessandra; Sisinni, Emiliano; DE MARCELLIS, A.; Ferri, G.; Mantenuto, P

A new 0.35μm CMOS electronic interface for wide range floating capacitive and grounded/floating resistive sensor applications

6nononenoneDE MARCELLIS A.; FERRI G.; MANTENUTO P.; DEPARI A.; FLAMMINI A.; SISINNI E.DE MARCELLIS, A.; Ferri, G.; Mantenuto, P.; Depari, Alessandro; Flammini, Alessandra; Sisinni, Emilian