A Cost-Effective SDR Platform for Performance Characterization of RFID Tags

2012 ◽  
Vol 61 (4) ◽  
pp. 903-911 ◽  
Author(s):  
Luca Catarinucci ◽  
Danilo De Donno ◽  
Riccardo Colella ◽  
Fabio Ricciato ◽  
Luciano Tarricone
2016 ◽  
Vol 4 (1) ◽  
pp. 33-41 ◽  
Author(s):  
Riccardo Colella ◽  
Luca Catarinucci ◽  
Luciano Tarricone

Radio-frequency identification (RFID) technology is a consolidated example of wireless power transfer system in which passive electromagnetic labels called tags are able to harvest electromagnetic energy from the reader antennas, power-up their internal circuitry and provide the automatic identification of objects. Being fully passive, the performance of RFID tags is strongly dependent on the context, so that the selection of the most suitable tag for the specific application becomes a key point. In this work, a cost-effective but accurate system for the over-the-air electromagnetic characterization of assembled UHF RFID tags is firstly presented and then validated through comparison with a consolidated and diffused measurement systems. Moreover, challenging use-cases demonstrating the usefulness of the proposed systems in analyzing the electromagnetic performance of label-type tags also when applied on different material or embedded into concrete structures have been carried out.


2005 ◽  
Vol 05 (01) ◽  
pp. 151-163 ◽  
Author(s):  
W. K. CHAN ◽  
Y. W. WONG ◽  
S. Y. KOH ◽  
V. CHONG

This paper describes the performance characterization of an axial blood pump that is developed in our laboratory. Using computational fluid dynamics (CFD), regions of flow separation and high shear stress were identified since they are of concern in the development of cardiac assist devices. CFD is an efficient and cost effective tool in assisting the designer to reduce the number of experimental trials needed. Preliminary CFD studies showed the existence of substantial backflow in the impeller passage. The impeller geometry was improved using CFD modeling. Regions of flow separation were eliminated while regions of scalar stress of up to 150 Pa were observed near to the impeller tip. The final prototype can deliver a flow rate of 5 L/min at a pressure head of 14 kPa when operating at a speed of 10,000 rpm. The model was fabricated using rapid prototyping techniques and performance characterization of the pump has demonstrated that the CFD prediction of the pump performance curve and the pressure developed along the impeller agrees reasonably well with experimental results.


Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 788
Author(s):  
Javed Sayyad ◽  
Paresh Nasikkar ◽  
Abhaya Pal Singh ◽  
Stepan Ozana

Solar energy is the most promising renewable resource with an unbounded energy source, capable of meeting all human energy requirements. Solar Photovoltaic (SPV) is an effective approach to convert sunlight into electricity, and it has a promising future with consistently rising energy demand. In this work, we propose a smart solution of outdoor performance characterization of the SPV module utilizing a robust, lightweight, portable, and economical Outdoor Test Facility (OTF) with the Internet of Things (IoT) capability. This approach is focused on the capacitive load-based method, which offers improved accuracy and cost-effective data logging using Raspberry Pi and enables the OTF to sweep during the characterization of the SPV module automatically. A demonstration using an experimental setup is also provided in the paper to validate the proposed OTF. This paper further discusses the advantages of using the capacitive load approach over the resistive load approach. IoT’s inherent benefits empower the proposed OTF method on the backgrounds of real-time tracking, data acquisition, and analysis for outdoor output performance characterization by capturing Current–Voltage (I–V) and Power–Voltage (P–V) curves of the SPV module.


2006 ◽  
Vol 1 (2) ◽  
Author(s):  
P. Literathy ◽  
M. Quinn

Petroleum and its refined products are considered the most complex contaminants frequently impacting the environment in significant quantities. They have heterogeneous chemical composition and alterations occur during environmental weathering. No single analytical method exists to characterize the petroleum-related environmental contamination. For monitoring, the analytical approaches include gravimetric, spectrometric and chromatographic methods having significant differences in their selectivity, sensitivity and cost-effectiveness. Recording fluorescence fingerprints of the cyclohexane extracts of the water, suspended solids, sediment or soil samples and applying appropriate statistical evaluation (e.g. by correlating the concatenated emission spectra of the fingerprints of the samples with arbitrary standards (e.g. petroleum products)), provides a powerful, cost-effective analytical tool for characterization of the type of oil pollution and detecting the most harmful aromatic components of the petroleum contaminated matrix. For monitoring purposes, the level of the contamination can be expressed as the equivalent concentration of an appropriate characteristic standard, based on the fluorescence intensities at the relevant characteristic wavelengths. These procedures are demonstrated in the monitoring of petroleum-related pollution in the water and suspended sediment in the Danube river basin


2018 ◽  
Vol 9 (1) ◽  
pp. 101-108 ◽  
Author(s):  
Shubhangi J. Mane-Gavade ◽  
Sandip R. Sabale ◽  
Xiao-Ying Yu ◽  
Gurunath H. Nikam ◽  
Bhaskar V. Tamhankar

Introduction: Herein we report the green synthesis and characterization of silverreduced graphene oxide nanocomposites (Ag-rGO) using Acacia nilotica gum for the first time. Experimental: We demonstrate the Hg2+ ions sensing ability of the Ag-rGO nanocomposites form aqueous medium. The developed colorimetric sensor method is simple, fast and selective for the detection of Hg2+ ions in aqueous media in presence of other associated ions. A significant color change was noticed with naked eye upon Hg2+ addition. The color change was not observed for cations including Sr2+, Ni2+, Cd2+, Pb2+, Mg2+, Ca2+, Fe2+, Ba2+ and Mn2+indicating that only Hg2+ shows a strong interaction with Ag-rGO nanocomposites. Under the most suitable condition, the calibration plot (A0-A) against concentration of Hg2+ was linear in the range of 0.1-1.0 ppm with a correlation coefficient (R2) value 0.9998. Results & Conclusion The concentration of Hg2+ was quantitatively determined with the Limit of Detection (LOD) of 0.85 ppm. Also, this method shows excellent selectivity towards Hg2+ over nine other cations tested. Moreover, the method offers a new cost effective, rapid and simple approach for the detection of Hg2+ in water samples.


Landslides ◽  
2021 ◽  
Author(s):  
Chiara Crippa ◽  
Elena Valbuzzi ◽  
Paolo Frattini ◽  
Giovanni B. Crosta ◽  
Margherita C. Spreafico ◽  
...  

AbstractLarge slow rock-slope deformations, including deep-seated gravitational slope deformations and large landslides, are widespread in alpine environments. They develop over thousands of years by progressive failure, resulting in slow movements that impact infrastructures and can eventually evolve into catastrophic rockslides. A robust characterization of their style of activity is thus required in a risk management perspective. We combine an original inventory of slow rock-slope deformations with different PS-InSAR and SqueeSAR datasets to develop a novel, semi-automated approach to characterize and classify 208 slow rock-slope deformations in Lombardia (Italian Central Alps) based on their displacement rate, kinematics, heterogeneity and morphometric expression. Through a peak analysis of displacement rate distributions, we characterize the segmentation of mapped landslides and highlight the occurrence of nested sectors with differential activity and displacement rates. Combining 2D decomposition of InSAR velocity vectors and machine learning classification, we develop an automatic approach to characterize the kinematics of each landslide. Then, we sequentially combine principal component and K-medoids cluster analyses to identify groups of slow rock-slope deformations with consistent styles of activity. Our methodology is readily applicable to different landslide datasets and provides an objective and cost-effective support to land planning and the prioritization of local-scale studies aimed at granting safety and infrastructure integrity.


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