The technological improvement in the field of physics, chemistry, electronics, nanotechnology, biology, and molecular biology has contributed to the development of various electrochemical biosensors with a broad range of applications in healthcare settings, food control and monitoring, and environmental monitoring. In the past, conventional biosensors that have employed bioreceptors, such as enzymes, antibodies, Nucleic Acid (NA), etc., and used different transduction methods such as optical, thermal, electrochemical, electrical and magnetic detection, have been developed. Yet, with all the progresses made so far, these biosensors are clouded with many challenges, such as interference with undesirable compound, low sensitivity, specificity, selectivity, and longer processing time. In order to address these challenges, there is high need for developing novel, fast, highly sensitive biosensors with high accuracy and specificity. Scientists explore these gaps by incorporating nanoparticles (NPs) and nanocomposites (NCs) to enhance the desired properties. Graphene nanostructures have emerged as one of the ideal materials for biosensing technology due to their excellent dispersity, ease of functionalization, physiochemical properties, optical properties, good electrical conductivity, etc. The Integration of the Internet of Medical Things (IoMT) in the development of biosensors has the potential to improve diagnosis and treatment of diseases through early diagnosis and on time monitoring. The outcome of this comprehensive review will be useful to understand the significant role of graphene-based electrochemical biosensor integrated with Artificial Intelligence AI and IoMT for clinical diagnostics. The review is further extended to cover open research issues and future aspects of biosensing technology for diagnosis and management of clinical diseases and performance evaluation based on Linear Range (LR) and Limit of Detection (LOD) within the ranges of Micromolar µM (10⁻⁶), Nanomolar nM (10⁻⁹), Picomolar pM (10⁻¹²), femtomolar fM (10⁻¹⁵), and attomolar aM (10⁻¹⁸).

Using a simple drop-casting technique, we successfully fabricated a sensitive electrochemical sensor based on the composite of reduced graphene oxide (RGO) and multiwalled carbon nanotubes (MWCNT) deposited on the surface of a glassy carbon electrode (GCE) for individual and simultaneous measurements of hydroquinone (HQ), dopamine (DA), and uric acid (UA). The nanocomposite of RGO/MWCNT was further characterized in terms of its structural properties, surface morphology, and topography using Raman, FT-IR spectroscopy, SEM, HRTEM, and AFM. Then, the proposed sensor for simultaneous measurement of HQ, DA, and UA based on RGO/MWCNT-modified GCE was investigated for its electrochemical behavior and electroanalytical performances using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), and differential pulse voltammetry (DPV). In addition, the composition ratio between RGO and MWCT was 1 : 1 showing the highest electrochemical response for simultaneous detection of HQ, DA, and UA. Owing to the synergistic effect between RGO and MWCNT leading to excellent conductivity properties, the proposed sensor exhibited improved electrochemical response at pH 7 toward the oxidation processes of HQ, DA, and UA on the surface of modified electrode. The proposed sensor demonstrated three well-defined anodic peaks of these analytes with their linear concentrations ranges of 3.0–150.0 μM for HQ, 4.0–100.0 μM for DA, and 2.0–70.0 μM for UA. The limit of detection values for the simultaneous detection of HQ, DA, and UA were found as follows 0.400 ± 0.014, 0.500 ± 0.006, and 0.300 ± 0.016 μM, respectively. The additional features of this proposed sensor are high reproducibility and stability for the simultaneous detection of HQ, DA, and UA with negligible interference effect from interferents such as Mg²⁺, K⁺, Cl⁻, ascorbic acid, and glucose. An acceptable percentage of recovery was also shown by this sensor for simultaneous measurements of HQ, DA, and UA using 6 samples of human urine. In summary, the RGO/MWCNT nanocomposite has been shown to be a promising platform for rapid, simple, and reliable determination of simultaneous measurements of HQ, DA, and UA in practical applications.

Thermal air oxidation enhances the adsorption capacity of steam-activated carbon coconut shell (SACCS) on MB removal and recovers the adsorption ability of the spent SACCS treated at 350 °C.

Despite the fact that COVID-19 is no longer a global pandemic due to development and integration of different technologies for the diagnosis and treatment of the disease, technological advancement in the field of molecular biology, electronics, computer science, artificial intelligence, Internet of Things, nanotechnology, etc. has led to the development of molecular approaches and computer aided diagnosis for the detection of COVID-19. This study provides a holistic approach on COVID-19 detection based on (1) molecular diagnosis which includes RT-PCR, antigen–antibody, and CRISPR-based biosensors and (2) computer aided detection based on AI-driven models which include deep learning and transfer learning approach. The review also provide comparison between these two emerging technologies and open research issues for the development of smart-IoMT-enabled platforms for the detection of COVID-19.