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This review provides an overview of recent advances in electrochemical sensors for analyte detection in saliva, highlighting their potential applications in diagnostics and health care. The purpose of this paper is to summarize the current state of the field, identify challenges and limitations and discuss future prospects for the development of saliva-based electrochemical sensors.

The paper reviews relevant literature and research articles to examine the latest developments in electrochemical sensing technologies for saliva analysis. It explores the use of various electrode materials, including carbon nanomaterial, metal nanoparticles and conducting polymers, as well as the integration of microfluidics, lab-on-a-chip (LOC) devices and wearable/implantable technologies. The design and fabrication methodologies used in these sensors are discussed, along with sample preparation techniques and biorecognition elements for enhancing sensor performance.

Electrochemical sensors for salivary analyte detection have demonstrated excellent potential for noninvasive, rapid and cost-effective diagnostics. Recent advancements have resulted in improved sensor selectivity, stability, sensitivity and compatibility with complex saliva samples. Integration with microfluidics and LOC technologies has shown promise in enhancing sensor efficiency and accuracy. In addition, wearable and implantable sensors enable continuous, real-time monitoring of salivary analytes, opening new avenues for personalized health care and disease management.

This review presents an up-to-date overview of electrochemical sensors for analyte detection in saliva, offering insights into their design, fabrication and performance. It highlights the originality and value of integrating electrochemical sensing with microfluidics, wearable/implantable technologies and point-of-care testing platforms. The review also identifies challenges and limitations, such as interference from other saliva components and the need for improved stability and reproducibility. Future prospects include the development of novel microfluidic devices, advanced materials and user-friendly diagnostic devices to unlock the full potential of saliva-based electrochemical sensing in clinical practice.

Nanosensors have a wide range of applications because of their high sensitivity, selectivity and specificity. In the past decade, extensive and pervasive research related to nanosensors has led to significant progress in diverse fields, such as biomedicine, environmental monitoring and industrial process control. This led to better and more efficient detection and monitoring of physical and chemical properties at better resolution, opening new horizons in the development of novel technologies and applications for improved human health, environment protection, enhanced industrial processes, etc.

In this paper, the authors discuss the application of citation network analysis in the field of nanosensor research and development. Cluster analysis was carried out using papers published in the field of nanomaterial-based sensor research, and an in-depth analysis was carried out to identify significant clusters. The purpose of this study is to provide researchers to identify a pathway to the emerging areas in the field of nanosensor research. The authors have illustrated the knowledge base, knowledge domain and knowledge progression of nanosensor research using the citation analysis based on 3,636 Science Citation Index papers published during the period 2011 to 2021.

Among these papers, the bibliographic study identified 809 significant research publications, 11 clusters, 556 research sector keywords, 1,296 main authors, 139 referenced authors, 63 nations, 206 organizations and 42 journals. The authors have identified single quantum dot (QD)-based nanosensor for biological applications, carbon dot-based nanosensors, self-powered triboelectric nanogenerator-based nanosensor and genetically encoded nanosensor as the significant research hotspots that came to the fore in recent years. The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development.

The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development.

This is a novel bibliometric analysis in the area of “nanomaterial based sensor,” which is carried out in CiteSpace software.

Internet of Things (IoT) and artificial intelligence are two leading technologies that bought revolution to each and every field of humans using in daily life by making everything smarter than ever. IoT leads to a network of things which creates a self-configuring network. Improving farm productivity is essential to meet the rapidly growing demand for food. In this chapter, the authors have introduced a smart greenhouse by integration of two leading technologies in the market (i.e., Machine Learning and IoT). In proposed model, several sensors are used for data collection and managing the environment of greenhouse. The idea is to propose an IoT and Machine Learning based smart nursery that helps in healthy growing and monitoring of the seed. The structure will be a dome-like structure for observation and isolation of an egg with various sensors like pressure, humidity, temperature, light, moisture, conductivity, air quality, etc. to monitor the nursery internal environment and maintain the control and flow of water and other minerals inside the nursery. The nursery will have a solar panel from which it stores the electricity generated from the sun, a small fan to control the flow of air and pressure. A camera will also be equipped inside the nursery that will use computer vision technology to monitor the health of the plant and will be trained on the past data to notify the user if the plant is diseased or need attention.

This paper aims to report a prototype of a reliable method for rapid, sensitive bacterial detection by using a low-cost zinc oxide nanorods (ZnONRs)-based electrochemical sensor.

The ZnONRs have been grown on the surface of a disposable, miniaturized working electrode (WE) using the low-temperature hydrothermal technique. Scanning electron microscopy and energy dispersion spectroscopy have been performed to characterize the distribution as well as the chemical composition of the ZnONRs on the surface, respectively. Moreover, the cyclic voltammetry test has been implemented to assess the effect of the ZnONRs on the signal conductivity between −1 V and 1 V with a scan rate of 0.01 V/s. Likewise, the effect of using different bacterial concentrations in phosphate-buffered saline has been investigated.

The morphological characterization has shown a highly distributed ZnONR on the WE with uneven alignment. Also, the achieved response time was about 12 minutes and the lower limit of detection was approximately 103 CFU abbreviation for Colony Forming Unit/mL.

This paper illustrates an outcome of an experimental work on a ZnONRs-based electrochemical biosensor for direct detection of bacteria.

Sensing technology has been extensively researched and used due to its applications in industrial production and daily life. Due to inherent limitations of conventional silicon-based technology, researchers are now-a-days paying more attention to flexible electronics to design low-cost, high-sensitivity devices. This observational and analytical study aims to emphasis on carbon monoxide gas sensor. This review also focuses the challenges faced by flexible devices, offers the most recent research on paper-based gas sensors and pays special focus on various sensing materials and fabrication techniques.

To get the better insight into opportunities for future improvement, a number of research papers based on sensors were studied and realized the need to design carbon monoxide gas sensor. A number of parameters were then gone through to decide the flexibility parameter to be considered for design purposes. This review also focuses on the challenges faced by flexible devices and how they can be overcome.

It has been shown that carbon monoxide gas, being most contaminated gas, needs to be fabricated to sense low concentration at room temperature, considering flexibility as an important parameter. Regarding this parameter, some tests must be done to test whether the structure sustains or degrades after bending. The parameters required to perform bending are also described.

Due to inherent limitations of conventional silicon-based technology, now-a-days attention is paid towards flexible electronics to design low-cost, high-sensitivity devices. A number of research articles are provided in the literature concerning gas sensing for different applications using several sensing principles. This study aims to provide a comprehensive overview of recent developments in carbon monoxide gas sensors along with the design possibilities for flexible paper-based gas sensors. All the aspects have been taken into consideration for the fabrication, starting with paper characterization techniques, various sensing materials, manufacturing methodologies, challenges in the fabrication of flexible devices and effects of bending and humidity on the sensing performance.

The aim of this review is to present together the studies on textile-based moisture sensors developed using innovative technologies in recent years.

The integration levels of the sensors studied with the textile materials are changing. Some research teams have used a combination of printing and textile technologies to produce sensors, while a group of researchers have used traditional technologies such as weaving and embroidery. Others have taken advantage of new technologies such as electro-spinning, polymerization and other techniques. In this way, they tried to combine the good working efficiency of the sensors and the flexibility of the textile. All these approaches are presented in this article.

The presentation of the latest technologies used to develop textile sensors together will give researchers an idea about new studies that can be done on highly sensitive and efficient textile-based moisture sensor systems.

In this paper humidity sensors have been explained in terms of measuring principle as capacitive and resistive. Then, studies conducted in the last 20 years on the textile-based humidity sensors have been presented in detail. This is a comprehensive review study that presents the latest developments together in this area for researchers.

The development of chemical sensors based on nanostructures, such as nanotubes or nanowires, depends on the capability to reproducibly control the processing of the sensor. Alignment and consistent electrical contact of nanostructures on a microsensor platform is challenging. This can be accomplished using labor‐intensive approaches, specialized processing technology, or growth of nanostructures in situ. However, the use of standard microfabrication techniques for fabricating nanostructured microsensors is problematic. The purpose of this paper is to address this challenge using standard photoresist processing combined with dielectrophoresis.

Nanostructures are suspended in photoresist and aligned between opposing sawtooth electrode patterns using an alternating current (AC) electric field (dielectrophoresis). The use of photoresist processing techniques allow the burying of the nanostructures between layers of metal, thus improving the electrical contact of the nanostructures to the microsensor platform.

This approach is demonstrated for both multi‐walled carbon nanotubes and tin oxide nanowires. Preliminary data show the electrical continuity of the sensor structure as well as the response to various gases.

It is concluded that this approach demonstrates a foundation for a new tool for the fabrication of microsensors using nanostructures, and can be expanded towards enabling the combination of common microfabrication techniques with nanostructured sensor development.

This approach is intended to address the significant barriers of deposition control, contact robustness, and simplified processing to realizing the potential of nanotechnology as applied to sensors.

Emission reduction methodologies alone are not sufficient to mitigate the climatic catastrophes caused due to ongoing carbon emissions. Rather, a bidirectional approach is required to decarbonize the excess carbon in the atmosphere through carbon sequestration along with carbon reduction. Since the manufacturing sector contributes heavily to the ongoing carbon emissions, the purpose of this paper is to propose a framework for carbon emission reduction and carbon sequestration in the context of the manufacturing industry.

In this paper, life cycle assessment (LCA) is employed to track the carbon emission at each stage of the product development life cycle. The pre-requisite for this is the accurate evaluation of the carbon emissions. Therefore, IoT technologies have been employed for collecting real-time data with high credibility to perceive environmental impact caused during the entire life cycle of the product. The total carbon emission calculation is based on the bill of material (BOM)-based LCA of the product to realize the multi-structure (from parts and components to product) as well as multi-stage (from cradle to gate) carbon emission evaluation. Carbon sequestration due to plantation is evaluated using root-shoot ratio and total biomass.

A five interwoven layered structure is proposed in the paper to facilitate the real-time data collection and carbon emission evaluation using BOM-based LCA of products. Further, a carbon neutral coefficient (CNC) is proposed to indicate the state of a firm’s carbon sink and carbon emissions. CNC=1 indicates that the firm is carbon neutral. CNC >1 implies that the firm’s carbon sequestration is more than carbon emissions. CNC <1 indicates that the firm’s carbon emission is more than the carbon sink.

The paper provides a novel framework which integrates the real-time data collection and evaluation of carbon emissions with the carbon sequestration.

Miniaturized smart sensors that can perform sensitive and selective real-time monitoring of target analytes are tremendously valuable for various sensing applications. So, the purpose of this paper is to provide details of sensors based on selective nanocoatings by combining trinitrotoluene (TNT) receptors bound to conjugated polydiacetylene (PDA) polymers with single-walled carbon nanotube field-effect transistors (CNTFETs) for detecting explosives TNT.

Following an introduction, this paper describes the way of creating an FET with CNTs, which are functionalized by the peptide based on TNT molecule recognition elements and PDA, to offer a system which has the capability of answering the presence of related target molecules (TNT). Finally, brief conclusions are drawn.

Single-wall nanotubes and reduced graphene oxide are interesting materials for creating biosensors of FETs at nanoscale because of unique electrical, mechanical, geometrical and biocompatible properties. Therefore, this sensor is designed and manufactured, and the results of applying TNT to sensor show good sensitivity and selectivity response.

In this timeframe of history, sensors based on CNTFET are required for different uses, including clinical diagnosis technologies, environmental tests and bioterrorism recognition technologies, that correspond to the military conflicts and terrorism. So, CNTFET sensor design provides real-time detection of TNT explosives.