The last decade has witnessed extensive research in the field of healthcare services and their technological upgradation. To be more specific, the Internet of Things (IoT) has shown potential application in connecting various medical devices, sensors, and healthcare professionals to provide quality medical services in a remote location. This has improved patient safety, reduced healthcare costs, enhanced the accessibility of healthcare services, and increased operational efficiency in the healthcare industry. The current study gives an up-to-date summary of the potential healthcare applications of IoT- (HIoT-) based technologies. Herein, the advancement of the application of the HIoT has been reported from the perspective of enabling technologies, healthcare services, and applications in solving various healthcare issues. Moreover, potential challenges and issues in the HIoT system are also discussed. In sum, the current study provides a comprehensive source of information regarding the different fields of application of HIoT intending to help future researchers, who have the interest to work and make advancements in the field to gain insight into the topic.

The colorimetric analysis of food has gained much popularity in the last few decades. The present study reports the development of a low‐cost food color quality testing and process monitoring system. The proposed device consists of a hardware and a software (Color Magic) combination, which may allow the hardware to be used either for quality testing or process monitoring applications. In the quality‐testing mode, the software captures the image of the food products through the imaging system. Subsequently, the software processes the acquired image and computes color parameters in RGB (red, green, blue), CIELAB, and HSI (hue, saturation, intensity) color spaces. The software also synthesizes and displays the perceived color information in the display panel. The datalog of the sample color information can be sent to the user. Further, a separate software (Color Process), which is installed in a central server, was developed to implement a wireless star network topology for multi‐node process monitoring. The “Color Process” software allows users to acquire color information from multiple hardware. The software monitors the Hue from all the devices. It alerts the user via email if the Hue is beyond the range in any of the nodes. Finally, the device was tested for quality testing and process monitoring applications using colored placards and apple slices. The implementation of the wireless sensor network (WSN) in designing the multi‐node process monitoring makes the proposed device a unique system. This further would allow the device to be used for process monitoring at multiple remote locations.

Precise conductance measurements of solutions of tetrabutylammonium bromide (Bu 4 NBr), sodium tetraphenylborate (NaBPh 4 ), and sodium bromide (NaBr) in N,N-dimethylformamide have been reported at (308.15, 313.15, 318.15, and 323.15) K. The conductance data have been analyzed by the 1978 Fuoss conductance-concentration equation in terms of the limiting molar conductance (Λ 0 ), the association constant (K A ), and the association diameter (R). The limiting ionic conductances have been estimated from an appropriate division of the limiting molar conductivity of the "reference electrolyte" Bu 4 NBPh 4 . Slight association was found for all these salts in this solvent medium. The limiting molar conductances of electrolytes as well as single-ion conductivity values increase appreciably with temperature.

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Technology has become an integral part of everyday lives. Recent years have witnessed advancement in technology with a wide range of applications in healthcare. However, the use of the Internet of Things (IoT) and robotics are yet to see substantial growth in terms of its acceptability in healthcare applications. The current study has discussed the role of the aforesaid technology in transforming healthcare services. The study also presented various functionalities of the ideal IoT-aided robotic systems and their importance in healthcare applications. Furthermore, the study focused on the application of the IoT and robotics in providing healthcare services such as rehabilitation, assistive surgery, elderly care, and prosthetics. Recent developments, current status, limitations, and challenges in the aforesaid area have been presented in detail. The study also discusses the role and applications of the aforementioned technology in managing the current pandemic of COVID-19. A comprehensive knowledge has been provided on the prospect of the functionality, application, challenges, and future scope of the IoT-aided robotic system in healthcare services. This will help the future researcher to make an inclusive idea on the use of the said technology in improving the healthcare services in the future.

The current study deciphers the processing of different proportions of white flour and whole wheat flour (100:0, 75:25, 50:50: 25:75, and 0:100) into a pizza base using yeast-based fermentation. The bread making using the yeast system resulted in significant changes in the characteristics of bread, ranging from the porous structure development to the crumb cellular structure modifications. An increase in the proportions of whole wheat flour resulted in the formation of golden yellow pizza bases. The lightness of the crust was decreased, whereas the yellowness index was increased as the whole wheat flour contents were increased. The pore size of the pizza base was decreased while the pore density was increased as the whole wheat flour content was raised within the bread. The microscopic study also showed the formation of porous structures on the bulk of the pizza base. The texture analysis of the bread also suggested an increase in the formation of the rigid network structure when the amount of whole wheat flour was increased. The springiness, cohesiveness, and resilience were comparable for all the prepared samples. On the other hand, the values for hardness, gumminess, and chewiness showed an increasing trend with the increase in the whole wheat flour content. The impedance of the samples decreased when there was an increase in the whole wheat flour content. Overall, the pizza base that was developed with 50% whole wheat flour and 50% white flour ratio displayed acceptably firm yet sufficient viscoelastic properties for human consumption.

The effect of coffee (caffeinated) on electro-cardiac activity is not yet sufficiently researched. In the current study, the occurrence of coffee-induced short-term changes in electrocardiogram (ECG) signals was examined. Further, a machine learning model that can efficiently detect coffee-induced alterations in cardiac activity is proposed. The ECG signals were decomposed using three different joint time–frequency decomposition methods: empirical mode decomposition, discrete wavelet transforms, and wavelet packet decomposition with varying decomposition parameters. Various statistical and entropy-based features were computed from the decomposed coefficients. The statistical significance of these features was computed using Wilcoxon’s signed-rank (WSR) test for significance testing. The results of the WSR tests infer a significant change in many of these parameters after the consumption of coffee (caffeinated). Further, the analysis of the frequency bands of the decomposed coefficients reveals that most of the significant change was localized in the lower frequency band (<22.5 Hz). Herein, the performance of nine machine learning models is compared and a gradient-boosted tree classifier is proposed as the best model. The results suggest that the gradient-boosted tree (GBT) model that was developed using a db2 mother wavelet at level 2 decomposition shows the highest mean classification accuracy of 78%. The outcome of the current study will open up new possibilities in detecting the effects of drugs, various food products, and alcohol on cardiac functionality.

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