In this paper, we present an Internet of things (IoT)-based data collection system for the risk assessment of urinary stone formation, or urolithiasis, by the measurement and storage of four parameters in urine: pH, concentrations of ionized calcium (Ca²⁺), uric acid and total dissolved solids. The measurements collected by the system from patients and healthy individuals grouped by age and gender will be stored in a cloud database. These will be used in the training phase of an artificial intelligence (AI) machine learning process utilizing the logistics regression model. The trained model provides a binary risk assessment, indicating if the end user is either a stone-former or not. For system validation, standard chemical solutions were used. Preliminary results indicated a sufficient measurement range, falling within the physiological range, and resolution for pH (2.0–10.0, +/−0.1), Ca²⁺(0.1–3.0 mmol/l, +/−0.05), uric acid (20–500 ppm, +/−1) and conductivity (1.0–40.0 mS/cm, +/−0.1), exhibiting high correlation with standard instruments. We intend to deploy this system in few hospitals in Taiwan to collect the data of patients’ urine, with analysis aided by urologist assessments for the risk of urolithiasis. The modularized design allows future modification and expansion to accommodate other sensing analytes.

This paper presents a low power electrochemical interface circuit for amperometric sensors. The readout circuit with potentiostat design maintains a constant bias potential between the reference and working electrodes using one operational transconductance amplifier (OTA) and four MOS transistors. Redox currents from 1 to 50 μA can be measured by the readout circuit with maximum nonlinearity of plusmn1 percent over the aforementioned range. The micro instrument has been implemented in 0.35 μm TSMC CMOS technology that consumes only 600 μW of power and occupies a small area of 0.16 mm ² . Chip test results emulate the simulation results with good agreement and confirm the effectiveness of the designed system.

ZnO films with a thickness of ~200 nm were deposited on SiO₂/Si substrates as the seed layer. Then Zn(NO₃)₂-6H₂O and C₆H₁₂N₄ containing different concentrations of Eu(NO₃)₂-6H₂O or In(NO₃)₂-6H₂O were used as precursors, and a hydrothermal process was used to synthesize pure ZnO as well as Eu-doped and In-doped ZnO nanowires at different synthesis temperatures. X-ray diffraction (XRD) was used to analyze the crystallization properties of the pure ZnO and the Eu-doped and In-doped ZnO nanowires, and field emission scanning electronic microscopy (FESEM) was used to analyze their surface morphologies. The important novelty in our approach is that the ZnO-based nanowires with different concentrations of Eu³⁺ and In³⁺ ions could be easily synthesized using a hydrothermal process. In addition, the effect of different concentrations of Eu³⁺ and In³⁺ ions on the physical and optical properties of ZnO-based nanowires was well investigated. FESEM observations found that the undoped ZnO nanowires could be grown at 100 °C. The third novelty is that we could synthesize the Eu-doped and In-doped ZnO nanowires at temperatures lower than 100 °C. The temperatures required to grow the Eu-doped and In-doped ZnO nanowires decreased with increasing concentrations of Eu³⁺ and In³⁺ ions. XRD patterns showed that with the addition of Eu³⁺ (In³⁺), the diffraction intensity of the (002) peak slightly increased with the concentration of Eu³⁺ (In³⁺) ions and reached a maximum at 3 (0.4) at%. We show that the concentrations of Eu³⁺ and In³⁺ ions have considerable effects on the synthesis temperatures and photoluminescence properties of Eu³⁺-doped and In³⁺-doped ZnO nanowires.