Intelligent Technologies for Research and Engineering

In a densely populated area with many users, adding a new wireless access point may not necessarily improve Wi-Fi performance. There are times when students must deal with poor download rates even with Access Points (AP) in every classroom. Cochannel interference is the root cause of several typical Wi-Fi issues. A discussion may be compared to Wi-Fi communication. The capacity to communicate and listen properly are both essential for effective communication. When two speakers are speaking in a similar tone, the conversational uncertainty is exacerbated. Wi-Fi broadcasts are the same way. The interference and drag performance might be worsened by two or more nearby APs using the same channel. This study suggests a smart antenna technology. When a smart antenna AP finds a nearby AP signal, it will automatically alter its pattern to minimise interference and provide quick and reliable transmission. The same principle applies when we cup our hands over our lips or ears to enable us to yell or listen more clearly. There are a lot of false positives in the typical approaches for WLAN node signal recognition. The optimal signal for a WLAN node is therefore identified using this study's proposed BPNN model, which uses the PFMDMM system for signal classification. This Decision-Making Model Using Parameterized Fuzzy Measures has been shown via experiments. A WLAN node's optimal signal may be more accurately predicted using a decision-making model based on preference-leveled evaluation functions. The precision of the signal identification and the anticipated findings were found to be almost identical to those obtained from real ground measurements. The test team mimicked cochannel interference, which would occur in a setting with plenty of APs, such as a workplace, hotel, or airport. The suggested smart antenna AP regularly outperformed other apps by an average of 75% greater coverage and unmatched performance.

The primary goal of this study is to provide a robust validation for biometric systems. When compared to unimodal biometrics, which use just one biometric feature, such as a unique finger print, facial feature, or palm print, multimodal validation provides a higher level of confirmation. In this paper, we use an individual's distinctive fingerprint as a watermark that is installed in the desired locations of the facial image of that individual that is captured with the aid of using a camera. This is accomplished by using a technique known as the Discrete Wavelet Transform (DWT). Between unwatermarked and watermarked face images, there is a significant serious level of visual relationship. Peak Signal-to-Noise Ratio (PSNR) and Mean Squared Error (MSE) procedures have been compared to and evaluated by the proposed watermarking strategy. 

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, longer propagations delay 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, 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 for increasing the network's dependability and connection while reorienting the AUV's movement direction.

The number of people using face masks has increased on public transportation, retail outlets, and at the workplace. All municipal entrances, workplaces, malls, schools, and hospital gates must have temperature and mask checks in order for people to enter. The paper's goal is to find someone who isn't wearing a face mask in order to control COVID-19. ConvNets may be used to recognize and classify images. The model depends on ConvNot 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 in regard to training data. MobilenetV2 correctly identifies the mask in “Mask” or “No Mask” video transmissions.

PH plays an important role in determining product quality in industries like various chemical, petrochemical, petroleum refineries, fertilizer, pharmaceutical, food industries, effluent treatment, and in many other organic and inorganic plants. For instance, in any industrial wastewater treatment plant, 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 ameasure 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. PHmeasurements 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 through 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 disposing water. 

Aedes albopictus is considered the primary threatening vector affecting public health. The process of identifying the specific transcripts for 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 a 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. 

The objective of the study was to identify a potential inhibitor for 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.

The focal point of this study is to recreate and plan a hybrid system consisting of a solar photovoltaic, a battery and a diesel generator and optimize the 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 obtained to meet the load demand based on input parameters which are obtained from a pilot survey and the main survey 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 is found that 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 ₹ 9.78M with initial capital and operating costs of ₹ 4.20M and ₹ 646,319 per year, respectively. The diesel fuel cost is obtained as ₹ 5,09,288 per year. Meanwhile, the electricity produced and consumption are also estimated as 1,09,040 kWh/year and 81,939 kWh/year, respectively, with an unmet load of 1.77% only.

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 be 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, it suggests that the technique is evaluated using (PSNR). In comparison with 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.

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 monitoring and stop 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 on 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.

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 multigigabit 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. 

This project 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 the entire module would be placed on a single device layer. They don't consider how a module's cells may be dispersed across many device levels to reduce the 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 a 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 submodules 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, a smaller solution area is used to arrange the 3D cells 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.

This chapter discusses the design and fabrication of biomimetic underwater robotic fish. 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 is provided. The innovative technology compromises the agility and performance of the robot that helps to achieve the real motion of the fish, making the robot competent for an aquatic-based design of the robot 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.

Agriculture is one of the backbones of our 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 system, because it maintains the moisture content present in the soil by 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.