Preface

The book on Intelligent Technologies for Research and Engineering covers new research findings from academics. The book contains research from active researchers who are involved in the cooperation between businesses and a variety of intelligent technologies, such as those that may be used in the production and distribution of industrial goods, factory automation, and other fields. The theory, design, development, testing, and evaluation of all intelligent technologies relevant to different areas of industry and its infrastructure are the main topics of this book. All computational intelligence techniques applicable to industry, intelligent data science techniques applicable to business and management, intelligent network systems applicable to industrial production, intelligent technologies applicable to smart agriculture, and intelligent information systems for agriculture are some of the topics covered. Significant advancements in intelligent systems have occurred as a result of the exponential growth of modern technologies. As a result, there is more potential for advancements and new uses.

A vital source of academic content on the creation, deployment, and integration of intelligent applications across several sectors is the journal, Developments and Trends in Intelligent Technologies and Smart Systems. This book is ideally suited for researchers, engineers, computer scientists, academics, students, and professionals interested in the most recent applications of intelligent technologies, highlighting a variety of cutting-edge topics like enterprise modelling, remote patient monitoring, and service-oriented architecture. Moreover, The latest advances in the field of solidification research and the problems posed by the community in the 21st century in terms of processing and analysis have been discussed.

On behalf of the editors, we would like to offer our appreciation to everyone who took part. First and foremost, the authors, whose excellent work is at the core of the book, and we gratefully congratulate all those involved and wish them great success. We would like to take this time to thank our family and friends for their support and encouragement while we worked on this book. First and foremost, we offer all credit and respect to our almighty Lord for his bountiful grace, which enabled me to finish this book successfully. We would like to express our gratitude to the writers for their contributions to this edited book. We would also like to thank Bentham Science Publishers and its whole team for facilitating the work and providing us the opportunity to be a part of this work.

The content of this book is summarized as follows:

In Chapter 1, it has been discussed that adding a new wireless access point, especially in a busy user environment does not always boost Wi-Fi performance. There are situations where, even with Access Points (AP) in every classroom, students still have to cope with slow download speeds. These common Wi-Fi complications are caused by co-channel interference. Wi-Fi communication is a bit like a conversation. A good communicator not only depends on the ability to speak but also on how well he or she listens. The conversational confusion is compounded when two speakers are using a similar tone. The same holds true for Wi-Fi transmission. Two or more neighboring APs operating on the same channel can increase interference and drag down performance. This paper proposes a smart antenna technology, when a smart antenna AP detects a neighboring AP signal, it will automatically change its pattern to reduce interference and show fast and reliable transmission. It is just like cupping our hands around our mouths or ears to let ourselves shout more loudly or listen more clearly. The normal methods for signal detection for WLAN nodes have many false positives. Therefore, this study proposes a BPNN model that uses a PFMDMM system for signal classification to identify the best signal for a WLAN node. The experimental results show that this Decision-Making Model using a Parameterized Fuzzy Measures Decision-Making Model Based on Preference Leveled Evaluation Functions for signal classification can better predict the best signal for a WLAN node. It was found that the estimated results and the signal detection accuracy are almost the same as in actual ground measurements. The test team simulated co-channel interference just like we would encounter in a school, office, hotel or airport where many APs operate on the same channel. The proposed smart antenna AP consistently delivered the best throughput outperforming other aps by an average of 75% superior coverage and unbeatable performance.

In Chapter 2, the fundamental point of this paper is to give staggered validation in biometric frameworks. Multimodal validation gives more degree of confirmation than unimodal biometrics, which utilizes only one biometric information, for example, unique finger impression or face or palm print. In this paper, we are utilizing a unique finger impression of an individual as a watermark which is installed in the chosen surface areas of the face picture of that individual which is caught utilizing a camera. A strategy called Discrete Wavelet Transform (DWT) is utilized for this reason. There is a serious level of visual relationship among unique and watermarked face pictures. The exhibition of the proposed watermarking strategy has been assessed and contrasted with procedures like Peak Signal-with Noise Ratio (PSNR) and Mean Squared Error (MSE).

In Chapter 3, Today, underwater communication has become a hot issue in research on both undersea and deep-sea navigation, as well as in autonomous underwater vehicle management, and acoustic communication has been accounted for due to its flexibility and lower degree of attenuation. However, owing to influencing elements such as channel time changing circumstances, bandwidth measurements, delay longer propagations, and the greatest degree of Doppler spread, pressure conditions, and salinity level, establishing acoustic communication in real-time is much more difficult. With a new monitoring era of global physical entities and based on the efficient energy-efficient awareness and depth, a new agent-based multipath routing protocol has been proposed in this work including underwater sensor nodes and underwater gateways with an autonomous underwater vehicle (AUV). The clustering head in the impacted region of sensor nodes will gather and aggregate data using mobile agent-initiated routing algorithms for identifying numerous pathways, as well as parameters including hope counting, delay propagation, nodal energy, and channel quality. In this paper, an agent-based dynamic AUV traversal method is developed to increase the network's dependability and connection while reorienting the AUV's movement direction

In Chapter 4, the number of people using face masks has increased on public transportation, retail outlets, and the workplace. All municipal entrances, workplaces, malls, schools, and hospital gates must have temperature and mask checks in order for people to enter such places. The paper's goal is to find someone who is not wearing a face mask in order to control COVID-19. Conv Net may be used to recognize and classify images. The model depends on Conv Net to assess whether or not someone is wearing a mask. It is possible to identify an image's face by utilizing a face identification algorithm. These faces are then processed using Conv Net face mask detection. If the model is able to extract patterns and characteristics from photographs, it will be categorized as either “Mask” or “No Mask”. With an accuracy rate of 99.85 percent, Mobile Net V2 is the most accurate when it comes to training data. MobilenetV2 correctly identifies the mask in “Mask” or “No Mask” video transmissions.

In Chapter 5, PH plays an important role in determining product quality in industries like various chemical, petrochemical, and petroleum refineries, fertilizer, pharmaceutical, and food industries, effluent treatment, and many other organic and inorganic plants. For instance, in any industrial wastewater treatment plant, the PH is monitored and controlled by manipulating the acid or base stream, which is a strong acid or strong base. Modern treatment plant involves physical and chemical precipitation/flocculation along with biological treatment in-aerators/trickle filters, membranes, etc, where the control of PH is the key factor for efficient treatment. In chemistry, PH is a measure of the acidity or basicity of an aqueous solution. Pure water is said to be neutral, with a pH close to 7.0 at 25 degree Celsius. Solutions with a PH less than 7 are said to be acidic and solutions with a PH greater than 7 are basic or alkaline. PH measurements are important in medicine, biology, chemistry, agriculture, forestry, etc. By PH control, we mean to maintain the PH value during continuous operation at a specific desired value by manipulating the alkaline flow rate. Usually in most industrial applications, the desired value is chosen to be around 7. This is the safest value for portable water, utility water used in industry, or waste-disposed water.

In Chapter 6, Aedes albopictus is considered the primary threatening vector for affecting public health. The process of identifying specific transcripts in enhancing the growth factor in Aedes albopictus is the initiation towards the development of a therapeutic marker. It implicates the identification of a particular antagonist. The approach was on the reference-based analysis of the whole transcriptome to reveal the differentially expressed pattern of transcripts. Further research requires the mathematical modeling of gene regulation and differential expression.

In Chapter 7, the objective of the study was to identify a potential inhibitor for a bifunctional protein in Microcystisaeruginosa. The in-silico modeling of the Protein using the “TBM” module of “Galaxy Seok Lab” extended the execution of virtual screening using MTi open screen. Finally, the protein-ligand interaction was studied using LIGPLOT software for “Bifunctional Protein” in “Microcystis aeruginosa.” The virtual screening revealed 7176 compounds from the drug library, and the “best fit” screening resulted in 1500 compounds. Among the 1500 compounds, the molecule MK-3207 showed a better affinity towards the bifunctional Protein with -11.3Kcal/mol binding energy.

In Chapter 8, the focal point of this study is to recreate and plan a hybrid system consisting of solar photo-voltaic, battery, and diesel generator and; to determine its optimized configuration into an off-grid hybrid structure to meet the electricity demand of an institutional area situated in Jaipur, Rajasthan, India. Various configurations have different specifications that are obtained to meet the load demand based on input parameters which are obtained from the pilot survey and main survey as well at a particular location. Various costing parameters such as per unit of cost and net present cost are estimated with the condition of meeting the maximum load demand. The HOMER (Hybrid Optimization Model for Electric Renewable) software is used for different simulation processes and finally, it has been found that the solar PV-battery-diesel generator hybrid system is an economical system to meet the electricity demand in which the cost of energy is obtained as 13.83 and Net Present Cost is 9.78 M with initial capital and operating costs of 4.20 M and 646,319 per year, respectively. The diesel fuel cost is obtained as 5,09,288 per year. Meanwhile, the electricity production and consumption are also estimated to be 1,09,040 kWh/year and 81,939 kWh/year with an unmet load of 1.77% only, respectively.

In Chapter 9, one of the most important issues in Wireless Multimedia Sensor Networks is the energy efficiency of object detection and image transmission. In-node object detection and tracking algorithms have been proposed in recent WMSN approaches. However, with a little effort, the WMSN will able to detect the presence and absence of objects in images. For the WMSN, a new approach for the above technique is suggested in this research. Instead of sending a whole image, this technique sends image parts. It ensures energy saving inside the node and minimum picture content which is transferred to the sink node. On the basis of in-node reconstructed and energy consumption picture PSNR, it is suggested that the technique is evaluated using (PSNR). In comparison to existing state-of-the-art methodologies, simulation results demonstrate that the suggested methodology saves 95 percent of node energy with a received picture PSNR of 46 dB.

In Chapter 10, the purpose of this study is to discover anomalies and malicious traffic in the Internet of Things (IoT) network, which is critical for IoT security, as well as to keep a watch on and stop the undesired traffic flows in the IoT network. For this objective, a number of researchers have developed several machine learning (ML) approach models to limit fraudulent traffic flows in the Internet of Things network. On the other side, due to poor feature selection, some machine learning algorithms are prone to misclassifying mostly damaging traffic flows. Nonetheless, further study is needed into the vital problem of how to choose helpful attributes for accurate malicious traffic identification in the Internet of Things network. As a solution to the problem, an Artificial Neural Network (ANN) model is proposed. The Area under Curve (AUC) metric is used to employ the cross-entropy approach to effectively filter features using the confusion matrix and identify effective features for the chosen Machine Learning algorithm.

In Chapter 11, a mixed signal quadrature demodulator was suggested in this study. In 90 nm CMOS technology, to get the desired frequency range, a quadrature VCO is employed. The fast speed is achieved with a three-bit ADC. Unused ADC construction components have been removed to conserve energy and space. Outputs obtained are used to meet the power needed in the mixed signal demodulator designed for multi-gigabit applications. QVCO, baseband AGC, frequency synthesizers, and IQ mixers are all part of the demodulator. This displays the highest level of integration while using the least amount of electricity. To sample the symbols at optimal SNR, the baseband modem included a mixed signal timing recovery loop based on the Gardner timing error detector.

In Chapter 12, this paper focuses on wire length reduction throughout the 3D floor layout stage. The 3D cell layout stage is part of the floor planning process. Previously, it was expected that an entire module would be placed on a single device layer. They do not consider how a module's cells may be dispersed across many device levels to reduce cable length. Each of the device layers is assigned to one of the cells that make up a module (a 2D module is converted into 3D module). To place cells in three dimensions, several constraints are used. The placement-aware constraints are a set of constraints that determine whether a 2D module may be turned into a 3D module. The vertical alignment of identical sub-modules owing to the same planar placement requirement is referred to as vertical constraint. The size of the solution will be reduced as a result of this. A 3D floor design module packing method is proposed by the author. Calculating the wire length and taking into consideration the feasibility requirement for a smaller solution area, 3D cells are arranged in an initial set of floor layouts. After finding the best floor design, the modules are packed using a packing algorithm, and the technique is finished. A placement-aware 3D floor design method is the name of the approach, which is developed in C++ and operates on Fedora Linux.

In Chapter 13, the design and fabrication of biomimetic underwater robotic fish are covered. A robot fish is a type of bionic robot that looks and moves like a real fish. Two motors, an Arduino microcontroller, Bluetooth, and a pump are required to complete the underwater robotic fish project. Motors are employed for quick forward and rotating motion, and the pump assembly aids in deep-water diving. In addition, sensors assist the robot in making intelligent judgments such as obstacle detection, direction shift, and so forth. Additionally, essential information such as live streaming, pressure, and temperature are provided. The innovative performance of the robot helps achieve the real motion of the fish, making the robot competent for the aquatic-based design that helps to reduce the complex structure without applications such as underwater exploration, oceanic supervision, pollution level detection, and military detection. This project is also beneficial.

In Chapter 14, it has been discussed that agriculture is one of the backbones of Indian economy. India is primarily an agricultural country. It plays an important role in the development of our nation. This project proposes an automatic irrigation; it maintains the moisture content present in the soil by an automatic irrigation system. This setup uses a capacitive soil moisture sensor v1.2 that measures the exact amount of soil moisture. It monitors soil properties such as temperature, humidity, soil moisture, and motor status. These parameters are measured using a soil moisture sensor, a DHT11 sensor, which is controlled by a NodeMCU that acts both as a microprocessor and as a server. It is possible to remotely control many farm operations from any part of the world through IoT.