Wearable electrochemical sensors have advanced in two application domains seldom examined together: personalised medicine, where on-body and microneedle devices interrogate sweat, interstitial fluid, saliva and tears, and precision agriculture, where leaf patches, in-planta microneedles and soil electrodes track phytohormones, agrochemicals and nutrients. Following PRISMA 2020, we screened 1,687 Scopus records using a single pre-specified search string, reproduced in full in the Supplementary Information, and analysed 201 primary studies. Both literature rest on an almost identical technology stack flexible substrates, nanostructured electrodes, enzymatic, affinity, imprinted and ionophore-based recognition, and wireless readout yet only fourteen eligible studies span both fields. Applying a five-level validation taxonomy derived from technology-readiness and analytical method-validation practice, we find analytical performance excellent but deployment evidence scarce: 4.0% demonstrated field or free-living operation, 53% stopped at on-body or on-plant testing, and drift, biofouling and reference-method benchmarking were reported in 24%, 27% and 32% respectively. These three figures are reporting rates rather than measures of adequacy: they record whether an issue was addressed at all, not whether it was validated over the period for which the device is claimed to work. The bottleneck is no longer sensitivity but sustained, reference-anchored operation; we propose a five-item validation-reporting framework, which adds the duration of continuous operation to validation tier, drift, biofouling and reference-method benchmarking, to make deployment readiness comparable across domains.
Rajanidevi Merigala, Sandeep Boddu, Yesudasu Vasimalla, Mallellu Sai Prashanth, Saleh Chebaane, Norah A. M. Alsaif, Sana Ben Khalifa, Bhishma Karki
The senor quality on pathogenic bacteria monitoring employing Tellurium Dioxide (TeO 2)/Cadmium Gallium Sulfide (CdGa 2 S 4)-assisted surface plasmonic resonance (SPR) refractive index (RI) sensor. This proposed design is used the Kretschmann configuration with silver (Ag) for exciting the surface plasmons. A wavelength of 633 nm is used to analyze the sensor’s performance exploiting the transfer matrix method along with angular interrogation technique. Initially, we show the optimization Ag’s thickness by analyzing the better minimum reflectance and sensitivity performances. Later, the structure optimization is also exhibited by comparing the proposed structure’s performance with others that are made-up with the defined layers. Finally, the performance analysis was investigated for different 2D materials and found that maximum attained parameters are sensitivity of 285.538 ° / R I U, quality factor of 144.152 R I U − 1, figure of merit of 134.875 R I U − 1 and combined sensitivity factor of 133.896. These results have a significant improvement as compared with the existing work. Furthermore, a machine learning framework based on the Random Forest regression algorithm was developed to predict the sensor sensitivity and evaluate the influence of the structural parameters on the sensing performance.
Efficient monitoring and maintenance of streetlight infrastructure remain significant challenges in modern smart cities due to the high costs associated with manual inspections and distributed deployments. This paper presents a Centralized Mapping Architecture for Automated Streetlight Fault Detection via Wireless Sensor Mesh Networks. The proposed system utilizes solar-powered sensor nodes and a wireless mesh communication framework to provide real-time monitoring of streetlight clusters. By monitoring the electrical behavior of ten streetlights using a single sensor node, the architecture significantly reduces hardware requirements and deployment costs. The system is capable of detecting faulty bulbs, leakage currents, and ground faults while providing real-time GIS-based fault localization. Simulation results demonstrate fault detection accuracy above 97%, packet delivery ratios close to 99%, and approximately 90% reduction in sensing hardware compared to conventional approaches. The proposed architecture offers a scalable, energy-efficient, and cost-effective solution for smart streetlight management.
P. C. Himadri Reddy, M. S. Sunitha, Saravanan Chandrasekaran
Gas sensors are extremely important because of their broad application in industrial production and everyday life. However, many conventional gas sensors require high operating temperatures and are fabricated from non-biodegradable materials, leading to increased energy consumption and disposal concerns. To address these limitations, processable conducting materials with sensing properties coated on natural and biodegradable substrates are highly desirable. In this study, organically processable polyaniline was synthesized, coated on natural substrates such as banana bracts (BB), fish scales (FS), and paper and was used as the electrode for sensing toxic gases such as ammonia (NH 3), carbon monoxide (CO), and sulfur dioxide (SO 2). Organically processable polyaniline (PANI)-maleic acid (MA)-dioctyl sodium sulfosuccinate (PAMD) was synthesized by the chemical oxidative polymerization of aniline in the presence of MA dopant, dioctyl sodium sulfosuccinate (DSS) surfactant, and ammonium peroxydisulfate initiator. The integration of DSS along with the PANI chains was confirmed by Fourier-transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD) studies, and UV–visible (UV–VIS) spectroscopy. The PAMD dispersion coated on BB, FS, and paper substrates was exposed to different toxic gases, and the corresponding resistivity changes were monitored. Among the tested substrates, PAMD coated on FS substrate exhibited the highest gas-sensing response, showing good linearity toward NH 3, CO, and SO 2 detection. The sensor also demonstrated low detection limits, excellent repeatability, and retained a high percentage of its initial response after multiple sensing cycles, confirming its good reusability and long-term stability.
This paper presents a comparative design and performance evaluation of two straight micro gas chromatography (µGC) columns with circular and trapezoidal cross-sectional geometries for the chromatographic separation of acetone and ethanol under identical operating conditions. Two geometries were simulated in a computational program, COMSOL Multiphysics, considering helium as a carrier gas and PEG (Polyethylene glycol) as a stationary phase. Parameters such as column length (10–100 cm) and hydraulic diameter (50–600 µm) were considered for both geometries and evaluated in terms of retention time, number of theoretical plates (N), resolution (R s), and height equivalent to a theoretical plat (HETP). The findings show that there is a clear trade-off between efficiency and pressure drop for the two geometrical configurations considered. The straight column of circular cross section configuration results in lower efficiency, which can be noted from the lower theoretical plate number ranging from (0.5–3.9) × 10 3 plates, larger HETP value of 0.027–0.035 cm, and poor resolution R s < 1.25 at lower pressure drop (280–500) Pa and higher flow rate (approximately 0.5 m/s). However, the straight column of trapezoidal cross section shows better separation efficiency due to enhanced mass transfer, band broadening reduction, and a higher surface-to-volume ratio with better flow distribution. Though the performance is improved, this improvement is obtained at the expense of higher pressure drop (∼3.8 × 10 3 Pa) and lower flow rate (∼0.35 m/s). From the above considerations, it can be seen that the trapezoid shape is indeed a better geometry when compared to others in µGCs, especially when used for breath analysis.
