This paper presents the best modeling and control strategies for a grid-connected hybrid wind-solar power system to maximize energy production. For variable wind speeds, determine the optimal power point using fuzzy logic control, adopt an adaptive hill climb searching method, and compare it with an optimal torque control method for large inertia wind turbine (WT). The role of fuzzy logic controller (FLC) is to adjust the hill climbing search (HCS) technique's step-size according to the operating point. The doubly-fed induction generator (DFIG) control system has two subsystems: rotor-side and grid-side converters. The active and reactive power have been indirectly regulated by adjusting the current on the d-q axis. The rotor side converter (RSC) controllers are responsible for controlling the WTs rotational speed to achieve the maximum power output. The grid side converter (GSC) manages the voltage at the DC link and keeps a unity power factor between the grid and GSC. Optimal hybrid power point tracking technique for use with photovoltaic systems in both constant and variable shade circumstances, based on particle swarm optimization (PSO) and perturb and observe (P&O). The optimal power point tracking (OPPT) approach is compared to three other methods: PSO, P&O, and hybrid P&O-PSO. The model has a total capacity of 2.249 MW, with wind capacity of 2 MW and solar capacity of 0.249 MW, and its efficiency is analyzed.

Computer-assisted diagnosis (CAD) is preferred for cancer identification across the globe, which relies on computerized image processing. The creation of previous CAD instruments involved a semi-automated approach that employed traditional deep learning techniques. Such techniques are not well versed with CAD instruments in terms of accuracy. Therefore, the given manuscript presents a convolutional neural network normalized architecture embedded with Bayesian optimization and long short-term memory (CNN-BO-LSTM) for the identification of liver cancer. Early pre-processing is done on the input magnetic resonance imaging (MRI) scan images to improve clarity. Next, we used dynamic binary classification to apply the accurate and region of interest (ROI) extracting approach. It is followed by automatic retrieval of CNN-based appearances from the ROI approach. For classification purposes, LSTM is used, which categorizes the images as benign or malignant. The proposed design’s testing outcomes, which combine characteristics with CNN-based ROI extraction and LSTM classification, surpassed the current state-of-the-art techniques.

The clustering strategy is the most effective and efficient way to preserve energy in the Wireless Sensor Network (WSN). However, the cluster heads in the hierarchical clustering approach use the majority of the energy that is required to carry out the operations. These operations include receiving the data from the sensor nodes, aggregating it, and then eventually transmitting it to the base station. When choosing the appropriate cluster head, you can play a significant part in reducing the amount of energy that is consumed by the WSN and, as a result, extending its lifespan. A technique for the selection of energy-efficient cluster heads that is based on the particle swarm optimization method is proposed in this study (PSO-EECH). For the method that has been proposed to measure the amount of energy used, we need to take into account the cluster distance, the distance between each sensor node and the nodes that are nearby, and the amount of residual energy that is left in sensor nodes. The aforementioned structure is also capable of doing cluster building, in which the non-cluster head node can follow its CH based on the determined weight function. The proposed PSO-EECH approach has been put through extensive testing, and the results have shown that it possesses a high degree of accuracy in every scenario. The outputs of the proposed algorithm are compared with those of other clustering-based algorithms already in existence, and the conclusions of this comparison have reported that our method outperforms the other existing methods.

Traffic might be a situation in shipping in which it has massive crowds, slows the rate of motorcars or indeed it'll increases.Business Avenue multiplied fleetly because point callers call for is inconceivable also the interplay among the motorcars reduces the rate of the point callers and latterly consequences in point callers traffic.To conquer similar occasions in gift script, clever point callers control contrivance may be initiated and we are in have a look at to discover a way to make point callers untied city.By combining a CCTV image with a photograph, this device makes it possible to track the location of callers' cautions and the air of moving vehicles.Processing CCTV images and identifying the various motorcars on the road helps.It makes it possible to reduce motor vehicle fuel consumption and point caller traffic on the road.Detectors are used to determine the variety and speed of motor vehicles.The obtained data may be sent to Variable Communication Subscriber (VMS) Boards by coordinating the CCTV cameras and detectors.Road users receive statistics about point callers thanks to this board.It makes it possible to change and reroute the main roadways so that waiting times are reduced.Even if the ready time is shortened, petrol is consistently consumed.Hence, inside reduction callers traffic may be dropped and offer point callers untied terrain.As we're facing a fast increase in our country's crowd, clever point callers control contrivance affords humans to have an easy transportation community which could discover a manner to attain their holiday spot snappily and make their adventure advanced ever.

The correct information may only sometimes be effectively conveyed by images due to various factors, such as excessively bright or dark lighting and low or high contrast. As a result, picture improvement has become an essential part of digital image processing. This proposed method aims to develop an algorithm for improving photos captured in dark environments. This letter presents a new picture-enhancing approach that combines median and Gabor filtering using the wavelet domain with histogram equalization working over a spatial domain. The proposed method in this paper combines spatial and transformed domains for image enhancement and has been simulated using MATLAB. The simulation results of two different photos show that the suggested approach extends the histogram over a wide range of grayscale, offering a superior improvement to the original image. The novel proposed algorithm aims to improve image quality and visibility, making identifying essential details within the image easier. Further, the proposed technique's success is manifested by examining the produced photos' contrast and brightness. The findings reveal that the suggested technique beats the other strategies for improving low-contrast photos.

Abstract Presently, there are many more commercial applications for thermoelectric Peltier coolers, notably portable air/water refrigerators, electronics cooling processes, thermal management systems in medical applications, and others. Thus, the goal of this project is to develop an experimentally-based optimisation procedure for powered by sunlight peltier-based air conditioners and heaters for use in hospitals that are capable of running continuously. This enables patients to cook meals in the heating element and keep drugs in the cold compartment inside the cooler, both functions being incorporated into one model while also reducing the device’s dimensions and requirement for space. In this study, a model that employs perturb and observe (P&O) approaches applied to solar systems under constant and partially shady circumstances was powered by the Maximum Power Point Tracking (MPPT) methodology. Additionally, the Internet of Things modules offer user and autonomous management, while the entire system is tracked and shown on an OLED. An appropriate number of modules also reduces the expense per cooling unit for Peltier coolers and warmers.

Deployment of small cells over the existing cellular network is an effective solution to improve the system coverage and throughput of fifth generation (5G) mobile communication networks. The arrival of the 5G mobile networks have demonstrated the importance of advanced scheduling techniques to manage the limited frequency spectrum available while achieving 5G transmission requirements. Cellular networks of the future necessitate the formulation of efficient resource allocation schemes that mitigate the interference between the different cells. In this research work, we formulate an optimization problem for heterogenous networks (HetNets) for resource allocation to maximize the system throughput among the cell center users (CCUs) and cell edge users (CEUs). We solve the optimization problem by effective utilization of the weight factors distribution for resource allocation. A novel Utility-based Resource Scheduling Algorithm (URSA) optimizes the resource sharing among the users with better delay budget of each application. The designed URSA ameliorates fairness along with reduced cross layer interference for real and non-real time applications. Performance of the URSA has been evaluated and compared most relevant state of art algorithms using the matlab based simulators. Furthermore, simulation results validate the superiority of the proposed scheduling scheme against conventional techniques in terms of throughput, fairness, and spectral efficiency.

Numerous cattle calves do not return to the sheds after grazing because they become disoriented, resulting in the loss of that specific cattle. If the cattle calves are not counted before and after grazing, it is impossible for the person to manually count them. Cattle calves are sensitive to a range of illnesses/diseases, most of them may reduce the production and quality of milk products and, if not discovered early, could even result in the cattle's death. Diseases have an influence on-farm production, therefore ends up in low production, low income, and low quality. This research work provides a methodology where different sensors and image processing techniques are used to monitor the health of the cattle and alert the user regarding its health condition, also an automated counting system is implemented to count the total number of cattle in the shed.

Objective: The conventional Ad Hoc On-Demand Distance Vector (AODV) routing algorithm, route discovery methods pose route failure resulting in data loss and routing overhead. In the proposed method, needs significant low energy consumption while routing from one node to another node by considering the status of node forwards the packet. So that while routing it avoids unnecessary control overhead and improves the network performance. Methods: Particle Swarm Optimization (PSO) algorithm is a nature- inspired, population-based algorithm. Particle Swarm Optimization (PSO) is a Computational Intelligence technique which optimizes the objective function. It works by considering that every member of the swarm contributes in finding the ideal solution by keeping a track of their own best known location and the best-known location of the group and keeps updating them whenever there is a change and hence minimizes the objective fitness function. The fitness function which we considered here is the Node lifetime, Link Lifetime and available Bandwidth. If these parameters are with good then status of node will be strong and hence routing of packet over those nodes will reduce delay and improves network performance. Result: To verify the feasibility and effectiveness of our proposal, the routing performance of AODV and PSO-AODV is compared with respect to various network metrics like Network Lifetime, packet delivery ratio and routing overhead and validated the result by comparing both routing algorithm using Network Simulator 2. The results of the PSO-AODV has outperformed the AODV in terms of low energy, less end to end delay and high packet delivery ratio and less control overhead. Conclusion: Here we proposed to use Particle Swarm Optimization in order to obtain the more suitable parameters for the decision making. The existing AODV protocol was modified to make a decision to recover from route failure; at the link failure predecessor node implementing PSO based energy prediction concept and using weights for each argument considered in the decision function. The fitness values for each weight were found through PSO basic form. We observed that the PSO showed satisfactory behaviour improvement than the performance of AODV for all metrics on the investigated scenarios.

Nowadays sleeping disorder is common among the people who work in metropolitan cities due to stress, pollution which often cause difficulty during sleeping. Diagnosing patients who have obstructive sleep apnea requires lab-based polysomnography, but over the years now more gadgets are available for sleep test. Today's technology has made life easier by offering many intelligent solutions to every problem in society, but when it comes to Sleeping Obstructive Disorder(SOD) still its in the initial stage. With the growing population for every year the number of patients are also increasing day by day. Hence a solution is required to automatically monitor and control the health status of a person. Hence, we proposed an IOT based Sleep Monitoring Device that has features like a fast WiFi module with local storage. The cardiac information is measured with the use of electro-resistive sensors and an accelerometer. In an effort to fix these problems, we've invented a new IOT-ready sleep monitoring gadget, which takes use of a new way of measuring cardiac and respiratory data with polymer-based innovation, and lets us record ECG and accelerometer results with only one lead. The NODEMCU allows the transfer of data in real time using a wireless internet connection, and it does so in line with industry standards.

World energy consumption is expanding at a breakneck pace. This rise in demand raises concerns about the global energy crisis and its associated environmental risks. Sustainable energy sources hold the key to resolving these concerns. Solar energy is widely regarded as one of the most abundant sources of sustainable energy, as it is both abundant and cost-free. Photovoltaic (PV) cells on solar panels are utilized to transform solar energy into uncontrolled electrical energy. These nonlinear solar photovoltaic cells have very poor efficiency. As a result, it becomes critical to optimize the output of solar photovoltaic cells by tracking their Maximum Power Point Tracking (MPPT). One of these MPPT approaches is Perturb & Observe (P&O). MPPT schemes' performance under rapidly changing weather and climate circumstances is crucial. This occurs in two circumstances: fast changes in solar irradiance and partial shading from clouds, etc. Additionally, it becomes necessary to study the performance of MPPT systems under different loading conditions. The objective of this article is to discuss the standard P&O MPPT scheme's behavior under increased solar irradiation circumstances and under different load conditions. The enhanced MPPT system is incorporated in a DC-DC converter's control circuit. MATLAB/Simulink is used for the simulated investigation.

The traffic management system is one of the important areas in any country for easy travel. In India, communication innovation in the social insurance sector has not yet been sufficiently updated to improve its administrative nature. With the increasing use of communication technology, many countries have implemented electronic card systems. Currently, there is no electronic traffic management system in India other than Digi locker. The goal of this proposed smartcard framework is to improve the efficiency and accessibility of driver and government document verification services. Using the smart card, all driver data, vehicle details, vehicle history, and past vehicle violations can be viewed by authorized parties through one website. Our proposed concept communicates the benefits of secure shipping to India using advances in data and correspondence. Digital profiling enables better tracking and more standardized documentation of drivers and vehicles, potentially reducing errors

Several problems faced by the visually impaired people were addressed over the past 3 decades. It includes transportation, text to voice conversion, alarm, and usage of the internet. There exist still several areas, where support and help for the visually impaired people are dependent on others. Among them is accessing the daily essential needs is of prime concern. Design and implementation of the visual system are proposed in this paper to help and support visually impaired people using Artificial Neural Networks (ANNs). Here deep learning technique is used for the identification of the objects and the distance of the object is measured using an ultrasonic sensor. The proposed methodology suits better for the conversion of the visual scenarios into voice messages along with the distinct location of the objects. The accuracy of the proposed visual model depends on the data sets used in the ANN algorithm. As the depth of the training data set increases, the performance of the prototype also increases with reduced processing delay in identifying the objects. OpenCV platform is used along with the python programming language to navigate through the surrounding.

In recent years there has been increase in development of human pursuing robots which can be used as daily life support robots. The primary goal is to design and fabricate a robot that not only tracks the target but also moves according to it. For implementing this project, a barcode was used as target that robot needs to follow. OpenCV provides an interface to capture live stream with camera. In order to detect the barcode, a program is written in python which is interfaced with OpenCV library. After capturing a video from the camera, it converts it into gray scale video and display it frame by-frame. After detecting the barcode from the video frame, black and white lines of an image is detected and the centroid will be calculated. Based on the position of the centroid, commands are given to the robot to move accordingly. Ultrasonic sensor is used to avoid collision between the robot and obstacles. As a result, the robot pursues the target and it can be used as an assisting system for handicapped people for carrying luggage or can be used in airports, railway stations as a luggage carrier.

Agriculture is the main livelihood source for 58% of the population of India. The Indian food industry is on the verge of massive growth, which each year increases its contribution to world trade in food because of its immense potential for added value. Particularly, in the food-processing industry which contribute to 16% of total GDP and 10% of exports. In this paper monitor agricultural land and displaying the parameters that has been sensed through Wireless Sensor Network (WSN). If anyone wants to include technology in agriculture, he should be aware of agriculture process. In this proposed work, we monitor the agriculture field at a distance by using XBee technology. We have connected various sensors to monitor field and depending on sensor values necessary actions will be taken. Main advantage of proposed work is consumption of power will be very less to communicate over other wireless communication technologies.

The purpose of this project is to provide a handsfree and hassle-free shopping experience to the user in the supermarket who suffers from the problems such as having chaotic time moving the baskets, overcrowding at one place for a certain product on sale, theft, spending a very long time standing in the queue in the counter for bill payment, etc. The project follows the user as per the command given in the smartphone application provided along with the smart shopping basket and installed on his phone. Customer will receive the total net amount of the bill he has to pay in the same application. The basket consists of the Bluetooth module to connect with the user's smartphone through which the basket's movements are commanded over. The basket also avoids coming in contact with any obstacles that it faces by taking deviation while following its user using ultrasonic sensors. Each product the user puts inside the basket is read using RFID technology, where each data is sent to the supermarket's server for a total billing of items the user wishes to buy. The total bill amount is sent to the user installed application so that customer can use any online payment applications available to complete his payment.

A novel method of Multiple lines of e-courts for various sports application controlled by Light Emitting Diode strips was proposed and experimentally analysed which accurately displays the court lines for the selected game. Here, an aurdino based microcontroller is used which supervises the work of the block chain and RFID tag which serves as an electronic key for accessing the sport court. The distinct court rule lines are shown for various sports like basketball, badminton, volleyball and kabaddi are set up and stored in the Application through which one can select particular court of interest. In this paper, we propose an efficient system design by providing security and quick access to multiple games at the same location. The designed module projects a series of lines in one touch onto the surface and also further transforms a basketball court to a volleyball court in seconds hence it utilize the space efficiently with multi-purpose single sporting space. This novel idea replaces the traditional court marking complexity for various games under single roof. The usage of various sensors like pressure sensor, IR sensors were utilized for monitoring the score points which offers added assistance to referees. Hence the idea is novel and the design concept is demonstrated and verified. This electronic court rule line system not only helps sportsmen and referees, but also connects them with audiences.

Quality of water may be an advanced exploration and production fundamental concept. The water quality is based on so many factors. Water infection is surely one of the essential crucial fears for the green globalization. With a view to deliver safe and secure water, real-time quality has to be monitored. The current system comprises a sensor network which is utilized to gauge both physical and synthetic boundaries of the water that are temperature, PH, turbidity, water glide sensor can be measured. These measured values from the sensors are processed via the Arduino UNO controller. Finally, the sensor values may be regarded using Wi-Fi module. This paper presents a cost efficient system for real time quality monitoring using Internet of Things (IoT).

Water is a most important natural resource available for mankind. We have to utilize in very economical way because of increase in the population, urbanization or many more factors. In agricultural sector water plays vital role in production, if we supply water in unsystematic way to the crops which leads to waste of water and also it effects on crop yield. The paper aims at using a scientific way of irrigation system which is based on moisture content of the soil. To implement this smart irrigation system we have used Arduino microcontroller and few sensors, these sensors will monitor the moisture content in the soil, based on the moisture level water pump will turn on or off this leads to optimal usage of water in a scientific way, and also we are monitoring the temperature and humidity of agricultural (using temperature and humidity sensors) field same information will be sent to the user mobile or to the system using GSM and IoT technology, IR sensors are also used to detect any intruder entering to the crop field. This scientific way helps the formers to reduce the manpower, reduces the physical monitoring the crop fields and also increases the production in the agricultural sectors.