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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.

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This paper presents a new approach to hyperspectral signature analysis, called Spectral Derivative Feature Coding (SDFC). It makes use of gradient changes in adjacent bands to characterize spectral variations so as to improve spectral discrimination and identification. In order to evaluate its performance, two binary coding methods, SPectral Analysis Manager (SPAM) and Spectral Feature-based Binary Coding (SFBC) are used to conduct comparative analysis. The experimental results demonstrate the proposed SDFC performs more effectively in capturing spectral characteristics.

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.

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Cloud computing technology has revolutionized the field of data management as it has enhanced the barriers of storage restrictions and high-cost establishment for its users. The benefits of the cloud have paved the way for its extensive implementation in large enterprises. However, the data in the cloud have succumbed to various security threats, and its privacy issues remain one of the biggest and topmost concerns for the data owners. Several techniques, such as Attribute-based Encryption (ABE), have been proposed by several researchers to preserve the privacy of the data. However, the issue of security still looms largely over the cloud. In the present work, we introduce the novel encryption model called “Advanced Encryption Standard–Cipher-text-Identity and Attribute-based Encryption” (AES–CP–IDABE) to preserve data privacy along with its access control. In the proposed scheme, the data have been double encrypted initially through the ABE, along with the attributes and the identity of the user. Secondly, the Advanced Encryption Standard (AES) is used to encrypt the encrypted data and provide it to the authorized users. The user access control is established using the digital signature with the help of user ID and security keys. Additionally, the set up includes Denial-of-Service (DoS) detection through IP address monitoring and control. The proposed scheme has also been evaluated for its performance in the communication between the user and the data owner, along with the user’s execution time. From the outcome, it is evident that the proposed scheme was more effective than the existing scheme of ABE over execution, encryption, and decryption time. Additionally, the performance over DoS detection and impact of attribute numbers for the proposed scheme was also studied to prove its effectiveness.