Implantable biosensors have evolved to the cutting-edge technology of personalized health care and provide promise for future directions in precision medicine. This is the reason why these devices stand to revolutionize our approach to health and disease management and offer insights into our bodily functions in ways that have never been possible before. This review article tries to delve into the important developments, new materials, and multifarious applications of these biosensors, along with a frank discussion on the challenges that the devices will face in their clinical deployment. In addition, techniques that have been employed for the improvement of the sensitivity and specificity of the biosensors alike are focused on in this article, like new biomarkers and advanced computational and data communicational models. A significant challenge of miniaturized in situ implants is that they need to be removed after serving their purpose. Surgical expulsion provokes discomfort to patients, potentially leading to post-operative complications. Therefore, the biodegradability of implants is an alternative method for removal through natural biological processes. This includes biocompatible materials to develop sensors that remain in the body over longer periods with a much-reduced immune response and better device longevity. However, the biodegradability of implantable sensors is still in its infancy compared to conventional non-biodegradable ones. Sensor design, morphology, fabrication, power, electronics, and data transmission all play a pivotal role in developing medically approved implantable biodegradable biosensors. Advanced material science and nanotechnology extended the capacity of different research groups to implement novel courses of action to design implantable and biodegradable sensor components. But the actualization of such potential for the transformative nature of the health sector, in the first place, will have to surmount the challenges related to biofouling, managing power, guaranteeing data security, and meeting today’s rules and regulations. Solving these problems will, therefore, not only enhance the performance and reliability of implantable biodegradable biosensors but also facilitate the translation of laboratory development into clinics, serving patients worldwide in their better disease management and personalized therapeutic interventions.

In the contemporary global landscape, diabetes is a concerning presence that contributes to noteworthy mortality rates. The etiology of this condition involves a subtle interaction between insulin deficiency and elevated blood sugar levels. Against this backdrop, the necessity for prompt, accurate, and continuous noninvasive monitoring of glucose concentrations becomes notably evident. The electrochemical flexible glucose biosensor was fabricated by immobilizing glucose oxidase (GOx) on ZnO nanoflakes, possessing a 20nm thickness, and synthesized on an Au-coated stretchable PET film. The sensitivity of the flexible biosensor was determined by 29.97μA/decade/cm², and the minimum detection limit was 1μM. The coefficient of determination was 97.76%, which is significantly linear.

Leakage of Liquefied Petroleum Gas and Liquified Natural Gas (LPG/LNG) produces hazardous and toxic impact on humans and other living creatures. The authors developed a system to monitor and control the gas leakage concentration. MQ-6 gas sensor is used for sensing the level of gas concentration in a closed volume. To monitor the consequences of environmental changes an IoT platform hosted by “Thingspeak” platform has been introduced. Both robust and cloud-forwarded controls have been applied to prevent uncontrolled leakage of those gases and auto-ignition. This type of system can be directly applied to the engine chamber/ fuel chamber of the modern marine vessels using dual fuel power cycle with LPG/LNG as secondary fuel-flamer. The results from the experiments clearly indicate satisfactory actuation speed and accuracy. The trials performed by the authors showed about 99% efficiency of signal transmission and actuation.

In the contemporary global landscape, diabetes is a prevalent and concerning presence that contributes to noteworthy mortality rates. The etiology of this condition involves a subtle interaction between insulin deficiency and elevated blood sugar levels which results in a complex metabolic disorder. The harmful consequences of this physiological abnormality become evident through the increased probability of kidney failure, heart attack, chronic liver diseases, and a pernicious ocular affliction leading to blindness. Against this backdrop, the necessity for prompt, accurate, and continuous monitoring of glucose concentrations with any form of flexible sensor becomes notably evident for type I and type II diabetes patients, pregnant women with diabetes, athletes, and high-risk persons. Sweat, an often-overlooked physiological excretion, is a reservoir of vital biological information due to its accessibility and analyzability. It is an advantageous matrix for glucose monitoring, surpassing blood, saliva, and tears. Its non-invasive nature offers a patient-friendly alternative to conventional blood sampling. The continuous, real-time nature of sweat extraction facilitates dynamic monitoring without the discomfort associated with invasive methods. This inherent advantage positions sweat as a promising matrix for glucose sensing, underscoring its potential as a valuable tool in diabetes management. It overcomes the limitations posed by other bodily fluids like saliva and tears in terms of accessibility, patient comfort, and reflective accuracy. The assimilation of nanomaterials into biosensing technologies heralds a paradigm shift, conferring heightened sensitivity upon these mechanisms. Noteworthy among these innovations are flexible wearable biosensors leveraging zinc oxide (ZnO) thin films, offering promising avenues for the discernment of glucose levels within sweat for healthcare monitoring. ZnO nanoflakes (ZnO-NFs) distinguish themselves by endowing flexible biosensors with unparalleled sensitivity, reliability, continuous monitoring capabilities, and non-invasiveness from zinc oxide nanoparticles incorporated graphene-carbon nanotube hybrid (GR-CNT-ZnO) and ergocalciferol-multi walled carbon nanotubes based (ERGOc-MWCNTd/Nf) traditional glucose sensors. The distinctive advantages of ZnO-NFs over bulk materials are multifaceted. Notably, the polarized (0001) plane orientation inherent in ZnO-NFs amplifies enzyme immobilization, thereby augmenting sensing performance. The elevated isoelectric point (9.5) of ZnO-NFs facilitates the immobilization of biomolecules, obviating the need for an ancillary binding layer. A single-step and efficacious sonochemical approach has been used to synthesize a thin layer of ZnO-NFs virtually on any substrate. The electrochemical flexible glucose biosensor was fabricated through the judicious immobilization of glucose oxidase (GOx) on ZnO nanoflakes, possessing a mere 20nm thickness and synthesized adeptly on an Au-coated stretchable polyethylene terephthalate (PET). The sensitivity of the flexible biosensor was determined by 29.97 μA/decade/cm² and the minimum detection limit is 100 μM. The coefficient of determination of the designed flexible electrode is found 97.76%, which is significantly linear. The designed PET/Au/ZnO-NFS/GOx flexible biosensors showed good repeatability for different sample concentrations. The enzymatic flexible sensor also showed good repeatability for three sample concentrations. The reproducibility data for two identical flexible sensors were found within the LoA of the Bland-Altman plot with a statistically significant p-value of 0.08 derived from the student t-test. Moreover, the flexible sensor exhibited notable repeatability, reproducibility, and remarkable stability conducive to the precise quantification of glucose. The application of this flexible wearable sensor has been validated through its utilization in human sweat samples, yielding results that align favorably with conventional methodology.

Zinc oxide Nanowires (ZnO-NWs) are promising biosensor materials and hold the key to overcoming challenges in the field. This chapter provides an introductory overview of biosensing technology, focusing on the fundamental principles and comparing ZnO-NWs with other nanostructures regarding the surface area, reactivity, electrical properties, charge transport behavior, optical, magnetic, and piezoelectric properties, and mechanical flexibility. Providing the synthesis and characterization methods, ZnO-NWs’ biosensing processes are also elaborated on surface modification for selectivity, integration with microfluidic systems, enhancing signal transduction, and connecting with biological elements like enzymes, antibodies, and DNA. The chapter also discusses the applications of ZnO-NWs-based biosensors in clinical diagnostics, environment monitoring, and agricultural and food safety. It investigates some case studies and challenges in practical deployments. It emphasizes how ZnO-NWs can address these challenges, such as stability, reproducibility, scalability, and integration with electronic devices. Adequate emerging trends that include the utilization of machine learning (ML) and artificial intelligence (AI) for the further enhancement of sensing performance and the prospects of ZnO-NWs in multifunctional sensor platforms are also presented, with an overview of how ZnO-NWs have been the focus for significant impacts on biosensing. Also presented in this chapter are potential breakthroughs and future research directions.

In this research, an automated yaw drive mechanism for a horizontal axis wind turbine was utilized to adjust the nacelle position to face the wind direction. Such wind turbine’s potential power extraction efficiency depends on the proper yaw control. In this study, a servo mechanized, automated control system has been developed and analyzed, applicable for small off-grid HAWT (Horizontal Axis Wind Turbine). To demonstrate the technical feasibility and superiority of the proposed solution, a mathematical model along with sensory calibration was developed and tested using an analog potentiometer. The system responses were recorded in an Internet of Things (IoT) server, and the mathematical model was validated by comparing the calibrated values with the experimental values, which showed about 97% accuracy. This system architecture uses a low-powered NodeMCU v.2 LoRa (Long Ranged) wireless controller for data transmission, and the ‘Thingspeak’ server, along with the MATLAB coding environment, has been utilized for data analytics and system response correction.