The introduction of Industry 4.0, to improve Internet of Things (IoT) standards, has sparked the creation of 5G, or highly sophisticated wireless networks. There are several barriers standing in the way of 5G green communication systems satisfying the expectations for faster networks, more user capacity, lower resource consumption, and cost‐effectiveness. 5G standards implementation would speed up data transmission and increase the reliability of connected devices for Industry 4.0 applications. The demand for intelligent healthcare systems has increased globally as a result of the introduction of the novel COVID‐19. Designing 5G communication systems presents research problems such as optimizing resource usage, managing mobility, ensuring cost‐efficiency, managing interference, and maximizing spectral efficiency. The fast advancement of artificial intelligence (AI) in several domains yields improved performance in contrast to traditional methods. Hence, including AI in 5G standards would enhance performance by catering to diverse end‐user applications. Initially, we provide an overview of concepts such as Industry 4.0, the 5G standard, and recent developments in the sphere of wireless communications in the future. The goal is to use 5G technology to look at current research problems. We present a new architecture for Industry 4.0 and 5G‐compliant smart healthcare systems. We develop and run the proposed model to investigate the current 5G methods using the Network Simulator (NS2). The results of the simulation show that 5G resource management and interference management approaches already in use face challenges including performance trade‐offs.
This study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (
The Environmental Data Acquisition Telemetry System is a versatile, flexible and economical means to accumulate data from multiple sensors at remote locations over an extended period of time; the data is normally transferred to the final destination and saved for further analysis.
This paper introduces the design and implementation of a simplified, economical and practical telemetry system to collect and transfer the environmental parameters (humidity, temperature, pressure etc.) from a remote location (Rural Area) to the processing and displaying unit.
To get a flexible and practical system, three data transfer methods (three systems) were proposed (including the design and implementation) for rural area services, the fi
... Show MoreThe matter of handwritten text recognition is as yet a major challenge to mainstream researchers. A few ways deal with this challenge have been endeavored in the most recent years, for the most part concentrating on the English pre-printed or handwritten characters space. Consequently, the need to effort a research concerning to Arabic texts handwritten recognition. The Arabic handwriting presents unique technical difficulties because it is cursive, right to left in writing and the letters convert its shapes and structures when it is putted at initial, middle, isolation or at the end of words. In this study, the Arabic text recognition is developed and designed to recognize image of Arabic text/characters. The proposed model gets a single l
... Show MoreOver the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.
The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame
In this work, a simulated study was carried out for designing a novel spiral rectangular patch of microstrip antenna that is used in ultra-wideband applications by using a high frequency structure simulator software (HFSS). A substrate with dielectric constant of 4.4 and height 2.10 mm (commercial substrate height available is about 0.8-1.575 mm) has been used for the design of the proposed antenna. The design basis for enhancing bandwidth in the frequency range 6.63 - 10.93 GHz is based on increasing the edge areas that positively affect the antenna's efficiency. This design makes the designed antenna cost less by reducing the area of the patch. It has been noticed that the bandwidth of the antenna under this study is increasing to 4.30
... Show MoreVisible light communication (VLC) is an upcoming wireless technology for next-generation communication for high-speed data transmission. It has the potential for capacity enhancement due to its characteristic large bandwidth. Concerning signal processing and suitable transceiver design for the VLC application, an amplification-based optical transceiver is proposed in this article. The transmitter consists of a driver and laser diode as the light source, while the receiver contains a photodiode and signal amplifying circuit. The design model is proposed for its simplicity in replacing the trans-impedance and transconductance circuits of the conventional modules by a simple amplification circuit and interface converter. Th
... Show MoreThe sale of facial features is a new modern contractual development that resulted from the fast transformations in technology, leading to legal, and ethical obligations. As the need rises for human faces to be used in robots, especially in relation to industries that necessitate direct human interaction, like hospitality and retail, the potential of Artificial Intelligence (AI) generated hyper realistic facial images poses legal and cybersecurity challenges. This paper examines the legal terrain that has developed in the sale of real and AI generated human facial features, and specifically the risks of identity fraud, data misuse and privacy violations. Deep learning (DL) algorithms are analyzed for their ability to detect AI genera
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