Sensors International最新文献

Fluorescent probes play a crucial role in analytical chemistry and biological imaging, offering selective detection of metal ions. Herein, we present the synthesis and characterization of a novel rhodamine-based fluorescent probe, RbHC (Rhodamine B Helicin), which was obtained through the condensation of rhodamine B hydrazide and helicin in ethanol. The probe demonstrates remarkable selectivity and anti-interference capabilities towards Cu²⁺ and Fe³⁺ ions in 80% acetonitrile solution. Spectral titration analysis revealed a linear relationship between the intensity and the concentration of Cu²⁺/Fe³⁺. The formation of complex between Cu²⁺/Fe³⁺ and RbHC was confirmed to be 1:1, and it was further confirmed by ESI mass spectroscopy and DFT calculations. The coordination with Cu²⁺/Fe³⁺ caused the opening of RbHC's spirolactam ring, resulting in distinct color change and red fluorescence emissions. Moreover, RbHC exhibits high stability and water solubility under both acidic and neutral conditions, enabling its application in the imaging of plant tissues. Besides, the absorption intensity of RbHC–Cu²⁺ increased significantly when exposed to sunshine and 365 nm UV radiation, indicating that it might be used as a potential indicator for measuring outdoor UV intensity.

In this modern era, maintaining a sustainable environment is pivotal and hence, a detailed review on gas sensors for quantification of toxic environmental pollutants is critical. In this paper, an extensive review on advancements in gas sensors developed using graphene-metal sulfide composites is discussed. Although graphene is an intriguing material with high sensitivity for determination of gases at low concentrations, its poor selectivity is a hindrance towards fabrication of high-performance gas sensors. Hence, hybrid nanocomposites prepared by embedding graphene and its derivatives with various metal sulfides including molybdenum sulfide (MoS₂), tin sulfide (SnS₂), tungsten sulfide (WS₂), cadmium sulfide (CdS) etc. were utilized in gas sensor fabrication with enhanced sensing capabilities. Related investigations revealed that gas sensors using graphene-metal sulfide nanohybrids could be effectively used in detection of individual molecules of toxic gas including NO_x, NH₃, H₂S, SO_2, HCHO, CO₂, CO, CH₄, C₃H₆O and so on at very low concentrations with good sensitivity and selectivity. A comparative evaluation of various performance parameters revealed that toxic gases were determined with a limit of detection and concentration as low as 0.6 ppb and 0.05 ppm respectively, using graphene-metal sulfide based gas sensors. This review reflects the fact that advancements in material synthesis has led to improvement in gas sensing performances as evidenced from the comparatively better performance metrics reported in recently published articles which utilized hybrid nanocomposites as sensing material.

The integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies is transforming precision agriculture by enhancing crop monitoring and management. This review explores cutting-edge methodologies and innovations in modern agriculture, including high-throughput phenotyping, remote sensing, and automated agricultural robots (AgroBots). These technologies automate tasks such as harvesting, sorting, and weed detection, significantly reducing labor costs and environmental impacts. High-throughput phenotyping leverages remote sensing, spectral imaging, and robotics to collect data on plant traits, enabling informed decisions on fertilization, irrigation, and pest management. DGPS and remote sensing offer precise, real-time data essential for soil condition assessment and crop health monitoring. Advanced image segmentation techniques ensure accurate detection of plants and fruits, overcoming challenges posed by varying lighting conditions and complex backgrounds. Case studies like the PACMAN SCRI project for apple crop load management and Project PANTHEON's SCADA system for hazelnut orchard management demonstrate the transformative potential of AI and IoT in optimizing agricultural practices. The upcoming integration of 5G and future 6G mobile networks promises to address connectivity challenges, promoting the widespread adoption of smart agricultural practices. However, several research gaps remain. Integrating diverse datasets, ensuring scalability for small and medium-sized farms, and enhancing real-time decision-making need further investigation. Developing robust AI models and IoT devices for varied agricultural conditions, creating user-friendly interfaces for farmers, and addressing privacy and security concerns are essential. Addressing these gaps can enhance the effectiveness and adoption of AI and IoT in precision agriculture, leading to more sustainable and productive farming practices.

Internet of Things (IoT) networks rely on wireless sensors for data collection and transmission, making them vulnerable to security threats that undermine their Quality of Service (QoS). The Routing Protocol for Low-Power and Lossy Networks (RPL) is crucial for efficient data transmission in IoT networks, but its performance can be significantly degraded by attacks such as Rank, Sinkhole and Wormhole attacks. These threats disrupt network integrity by manipulating routing information, attracting traffic through malicious nodes and tunneling data to malicious endpoints. This paper presents a novel machine learning-based framework to enhance RPL's security and QoS. Our approach integrates a random forest model for precise traffic classification, a reinforcement learning module for dynamic and adaptive routing, and a modified RPL objective function that incorporates classification outcomes into routing decisions. Simulations demonstrate that our framework significantly improves network throughput, reduces latency, and enhances packet delivery ratios while maintaining low jitter. Furthermore, it achieves a high detection rate, minimal false positives, and swift response to security incidents, thereby robustly securing the RPL protocol and enhancing QoS in IoT-enabled wireless sensor networks. The findings of this research offer substantial contributions to the field, providing a comprehensive solution to strengthen RPL against prevalent security threats.

The significance of a more convenient and sustainable power transfer has been more crucial recently with the increasing need for low power electronic devices and their applications in internet of things (IoT). Wireless power transfer (WPT) technologies can conveniently transmit power to sensor and electronic devices deployed in hard-to-reach locations and therefore improving their convenience and mobility. On the other hand, low power wide area networks (LPWANs) provide low-power consumption, low bandwidth interaction between IoTs and the cloud, all which are traits of low-cost solutions for long range communication. Conversely, due to these devices’ locations (hard-to-reach/hazardous), it is a challenge to sustainably charge them and for the power sources or their mechanisms to last for longer term. This review analyses recent work on LPWANs and low power WPT with strong focus on the main challenges and key solutions that would allow for their integration in IoT applications. Challenges facing WPT systems such as end-device power intake, transmission power loss, power regulation, and coil/loop misalignment are highlighted in reference to recent research, recommending various challenge-mitigating techniques. Furthermore, for LPWAN end-devices, energy profiling of such devices is discussed through recent work aiming to optimise their power consumption. Specifically, we discuss factors affecting LPWAN end-devices’ power consumption which comprises the spreading factor, communication range and bit-rate. Also, comparison analysis is performed to highlight the superiority of wireless sensors/power transfer, in terms of cost, reliability, environmental impact and scalability Essentially, it is necessary to realise the potential of these two techniques (WPT and LPWAN), as their integration can advance various fields like structural health monitoring (SHM), precision agriculture, healthcare, and environmental monitoring.

A facile method for trivalent chromium (Cr³⁺) ion determination using optical silver nanoparticles capped carbon dots (Ag@CDs) was developed. The optical responses via absorption and fluorescence of Ag@CDs in the presence of Cr³⁺ ion were detected. The nanocomposite showed maximum absorption wavelength at 406.0 nm, while emission wavelength appeared at 526.0 nm when excited at 406.0 nm. Optimal conditions for the Ag@CDs activity on Cr³⁺ ion detection were at pH 6, volume ratio between Ag@CDs and Cr³⁺ ion of 1.0:4.0, and reaction time of 20 min. The linearity range of the detection was 0.1–10.0 mg/L. In the absorption mode, the limit of detection (LOD) and limit of quantification (LOQ) were 0.10 mg/L and 0.31 mg/L, respectively. The fluorescence mode of detection showed LOD and LOQ of 0.06 mg/L and 0.18 mg/L, respectively. The dual-mode sensor was applied for Cr³⁺ ion quantification in dietary supplement samples because it is an essential micronutrient and widely used as supplement products. The recovery study of the spiked sample extracts was in the range of 96.86–103.05 %. The results showed good agreement with those from a conventional method of atomic emission spectrometry. The optical changing mechanism of the nanocomposite could be explained by the electron transfer from Ag@CDs to Cr³⁺.

The uncontrolled use of ciprofloxacin (CIP) has led to increased resistance in patients and potential health issues such as kidney disorders, digestive disorder, and liver complications. This study addresses these concerns by introducing an innovative electrochemical sensor utilizing a screen-printed electrode (SPE) enhanced with a novel rGO-SnO₂ nanocomposite for the precise monitoring of CIP concentration. Through square wave voltammetry (SWV), this sensor demonstrates unparalleled sensitivity and accuracy in determining CIP levels. These analyses validated the superior performance of the SPE/rGO-SnO₂ electrode, revealing CIP potential range of 0.85–1.50 V with irreversible oxidation reaction and an exceptional signal-to-background (S/B) ratio of 1.91, surpassing the 1.21 ratio achieved by the SPE/rGO electrode. The SPE/rGO-SnO₂ electrode also exhibited the highest active surface area (0.0252 cm²), facilitating faster transfer electron. Crucially, the SPE/rGO-SnO₂ electrode exhibited an impressively low limit of detection (LOD) at 2.03 μM within a concentration range of 30–100 μM for CIP, setting a new benchmark for sensitivity (9.348 μA/μM) in CIP detection. The %RSD value was less than 5 % indicating that this modified electrodes exhibit good precision and stability. The real-world applicability of this developed methods was exemplified through its successful implementation in the analysis of river water and milk, achieving remarkable recovery rates of 101.2 % and 97.7 %, respectively. Consequently, the SPE modified with rGO-SnO₂ nanocomposite emerges as a highly promising and effective tool for precise and sensitive CIP measurement, offering unparalleled performance metrics and opening avenues for enhanced environmental and health monitoring.

Graphene and its derivatives have become essential materials in modern biomedical research due to their positive impact on various applications. Moreover, the integration of graphene-based materials with microfluidics technology has opened up new possibilities. The novelty of the current review is considering comprehensive analysis of the transformative impact of graphene and its derivatives in biomedical applications, particularly highlighting the integration with microfluidics technology. While many studies have focused on individual applications of graphene, this review uniquely present a holistic view of its potential across various biomedical fields, including drug delivery, gene delivery, tissue engineering, and photothermal treatment, detection, sensor with respect to conventional and microfluidics techniques. In this review, we analysed published research to unveil the increasing interest in graphene's potential applications in healthcare and medicine, as well as its prospects for further exploration. We explore the fundamental concepts of graphene, its properties, and its latest applications in medical implants and biological fields within the context of microfluidics and conventional prospects. The review also addresses the challenges and limitations of these materials and their promising future, recognizing that graphene research is still in its early stages compared to commercial applications.

Air pollution is a significant problem in big cities due to the rapid increase of anthropogenic activities and severe traffic congestion. Therefore, real-time and micro tools for air monitoring are urgently necessary for fast and better policy decision-making. The current city air monitoring tool is typically static and serves a macro area. This study introduces technology development to integrate the air quality sensor with the satellite-based navigation receiver. This study used a carbon dioxide (CO₂) MH-Z19C sensor and real-time kinematic global navigation satellite system (RTK GNSS) U-Blox F9P with GNSS Trimble NetR9 receiver. The field air quality monitoring (CO₂ observed in ppm) and the movement velocity (vehicle speed observed in km/h) were recorded on two main roads of Jakarta by using a survey vehicle. The study compares the observation results of the non-integrated system (NIS) and integrated technology system (IS). The two systems generated the CSV database (CO₂ and vehicle speed); however, IS generated the automatic synchronized and error-free data output. The statistical regression analysis of CSV data (CO₂ and vehicle speed) between the NIS and IS reported significant results, which means both are reliable. Still, the NIS did not require manual synchronization, with some possibility of error. The R square values show a significant gap (speed 0.99 over CO₂ 0.144), indicating that IS needs further development as the CO₂ data varies due to technicality. The finding presents that integrating the CO₂ sensor and GNSS receiver generates a more effective time synchronization process and a reliable error removal technique in developing the CSV data. This finding is a significant reference in developing the integrated satellite-based receiver system with external environmental sensors.