Soil monitoring is emerging as a key factor to manage smart farming which has been recommended to have economical food safety and security. Among various development for example internet of things assisted farming, electrochemical sensing system are getting popularity via detecting one or multiple soil component effectively, efficiently, and selectively for soil quality assessment remotely via data sharing and site of location just like point-of-care soil heath care. Considering scenarios, this perspective is designed to describe state-of-the art electrochemical sensing technology developed for soil quality. The associated challenges, possible alternatives, and potential prospects are also discussed in this perspective.

To promote sustainability, this review explores: 1) the utilization of affordable high‐performance sensors that can enhance food safety and quality, plant growth, and disease management and 2) the Internet of Things (IoT)‐supported sensors to empower farmers, stakeholders, and agro‐food industries via rapid testing and predictive analysis based on sensing generated informatics using artificial intelligence (AI). The performance of such sensors is noticeable, but this technology is still not suitable to be used in real applications owing to the lack of focus, scalability, well‐coordinated research, and regulations. To cover this gap, this review carefully and critically analyzes state‐of‐the‐art sensing technologies developed for food quality assurance (i.e., contaminants, toxins, and packaging testing) and plant growth monitoring (i.e., phenotyping, stresses, volatile organic components, nutrient levels, hormones, and pathogens) along with the possible challenges. The following has been proposed for future research: 1) promoting the optimized combination of green sensing units supported by IoT to perform testing at the location, considering the remote and urban areas as a key focus, and 2) analyzing generated informatics via AI should also be a focus for risk assessment understanding and optimizing necessary safety majors. Finally, the perspectives of IoT‐enabled sensors, along with their real‐world limitations, are discussed.

Microfluidics is revolutionizing the way research on cellular biology has been traditionally conducted. The ability to control the cell physicochemical environment by adjusting flow conditions, while performing cellular analysis at single-cell resolution and high-throughput, has made microfluidics the ideal choice to replace traditional in vitro models. However, such a revolution only truly started with the advent of polydimethylsiloxane (PDMS) as a microfluidic structural material and soft-lithography as a rapid manufacturing technology. Indeed, before the “PDMS age,” microfluidic technologies were: costly, time-consuming and, more importantly, accessible only to specialized laboratories and users. The simplicity of molding PDMS in various shapes along with its inherent properties (transparency, biocompatibility, and gas permeability) has spread the applications of innovative microfluidic devices to diverse and important biological fields and clinical studies. This review highlights how PDMS-based microfluidic systems are innovating pre-clinical biological research on cells and organs. These devices were able to cultivate different cell lines, enhance the sensitivity and diagnostic effectiveness of numerous cell-based assays by maintaining consistent chemical gradients, utilizing and detecting the smallest number of analytes while being high-throughput. This review will also assist in identifying the pitfalls in current PDMS-based microfluidic systems to facilitate breakthroughs and advancements in healthcare research.

Biosensors hold great potential for revolutionizing personalized medicine and environmental monitoring. Their construction is the key factor which depends on either manufacturing techniques or robust sensing materials to improve efficacy of the device. Functional graphene is an attractive choice for transducing material due to its various advantages in interfacing with biorecognition elements. Graphene and its derivatives such as graphene oxide (GO) are thus being used extensively for biosensors for monitoring of diseases. In addition, graphene can be patterned to a variety of structures and is incorporated into biosensor devices such as microfluidic devices and electrochemical and plasmonic sensors. Among biosensing materials, GO is gaining much attention due to its easy synthesis process and patternable features, high functionality, and high electron transfer properties with a large surface area leading to sensitive point-of-use applications. Considering demand and recent challenges, this perspective review is an attempt to describe state-of-the-art biosensors based on functional graphene. Special emphasis is given to elucidating the mechanism of sensing while discussing different applications. Further, we describe the future prospects of functional GO-based biosensors for health care and environmental monitoring with a focus on additive manufacturing such as 3D printing.

A dual-modality microfluidic biosensor is fabricated using a mesoporous nanostructured cysteine–graphene hydrogel for the quantification of human cardiac myoglobin (cMb). In this device, the nanoengineered mesoporous L-cysteine–graphene (Cys–RGO) hydrogel performs the role of a dual-modality sensing electrode for the measurements conducted using differential pulse voltammetry and surface plasmon resonance (SPR) techniques. High surface reactivity, mesoporous structure and fast electron transfer combined with good reaction kinetics of the graphene hydrogel in this device indicate excellent performance for the detection of human cardiac myoglobin in serum samples. In electrochemical modality, this microfluidic chip exhibits a high sensitivity of 196.66 μA ng⁻¹ mL cm⁻² for a linear range of concentrations (0.004–1000 ng mL⁻¹) with a low limit of detection (LOD) of 4 pg mL⁻¹ while the SPR technique shows a LOD of 10 pg mL⁻¹ for cMb monitoring in the range 0.01–1000 ng mL⁻¹. The intra-assay coefficient of variation was less than 8% for standard samples and 9% for real serum samples, respectively. This Cys–RGO hydrogel-based microfluidic SPR chip allows real-time dynamic tracking of cMb molecules with a high association constant of 4.93 ± 0.2 × 10⁵ M⁻¹ s⁻¹ and a dissociation constant of 1.37 ± 0.08 × 10⁻⁴ s⁻¹, self-verification, reduced false readout, and improved detection reliability.