Nowadays, the integration of fast Electric Vehicle (EV) charging station with microgrid becomes very challenges due to non-linear behavior of load unit. These charging unit produce harmonic distortions which reduce the power quality. To ensuring the stable voltage and current profile as per IEEE standard while connecting Grid-to-Vehicle (G2V) has becomes challenging issue. In this paper, an efficient off board 3P3L4W (Three-Phase Three-Level Four-Wire) T-Type Vienna Rectifier (TTVR) for fast EV charging stations with suppressed Total Harmonic Distortion (THD) level and power quality enhancement is presented. TTVR interfaced with Improved Instantaneous real and reactive power (IIPQ) control strategy to maintain low switching losses, enhanced steady state and dynamic load response. Hence, this proposed Fuzzy Logic Controller based IIPQ control strategy has been employed to maintain constant DC-Link voltage and capacitor voltage VC1, VC2. This method is validated by using MATLAB and experimental validation also carried with 15KW laboratory prototype using digital signal peripheral Interface controller (dsPIC30F4011), Rapid Hyper-fast Recovery Glass (RHRG30120) power diodes and Silicon Carbide Metal-Oxide-Semiconductor Field-Effect Transistors (SiC MOSFETs IRFP260) switches to maintain high switching stress and low ON-State losses. The average THD value obtained is close to 2.5% which implies power quality enhancement, battery charging efficiency and highlighting the feasibility and adaptability of the proposed system for energy conversion and advanced EV charging station infrastructure development.

In modern days, health monitoring plays a vital role in monitoring the patients' health. It is advised that hospitals integrate health monitoring systems into their existing medical infrastructure so that doctors can monitor the vital signs of their patients. The Internet of Things (IoT), recently undergone technological improvements, which interconnects everything to one another and subsequently regarded as new technology. The data taken from the patient needs internet connections to transmit, but not all patients can access good internet connectivity. With these modern technologies, the healthcare sector improves on rapidly with new innovations. With the help of edge technologies like wearables, wireless networks, and other remote instruments, health technologists and professionals have created a great, affordable healthcare monitoring system for people dealing with a variety of conditions. IoT based health monitoring systems are used to collect and exchange patient data from hospital sensors. Here, this study use temperature sensor, pulse sensor, tilt sensor and flex sensors. All these sensors are combined in a single kit of Raspberry pi Pico W. When an input is drawn from the patients all the needed data will be obtained by using these sensors. Specially it also be used for bedridden patients which help in monitoring their movement.

Rainy weather conditions are challenging issues for many computer vision applications. Rain streaks and rain patterns are two crucial environmental factors that degrade the visual appearance of high-definition images. A deep attention network-based single-image deraining algorithm is more famous for handling the image with the statistical rain pattern. However, the existing deraining network suffers from the false detection of rain patterns under heavy rain conditions and ineffective detection of directional rain streaks. In this paper, we have addressed the above issues with the following contributions. We propose a multilevel shearlet transform-based image decomposition approach to identify the rain pattern on different scales. The rain streaks in various dimensions are enhanced using a residual recurrent rain feature enhancement module. We adopt the Rain Pattern Absorption Attention Network (RaPaat-Net) to capture and eliminate the rain pattern through the four-dilation factor network. Experiments on synthetic and real-time images demonstrate that the proposed single-image attention network performs better than existing deraining approaches.

The concerned workers ensure that vehicles are parked in the appropriate spaces. Employees must repeatedly poll their coworkers via personal surveys or the company's internal phone system to ensure that everything is correct. If there is an available parking space, the driver will manually move the vehicle there, regardless of any obstacles. If there is no available space, the car must return and try again later. The proposed intelligent parking system, if implemented, would solve all parking problems. This will take less time and fuel than other options. Intelligent parking solutions will fundamentally alter automobile-centric cities. It may make parking more convenient by bringing order to the chaos. People are always concerned that finding a parking spot will take too long, particularly in densely populated cities. This study focuses on developing a new system in which residents in high-traffic areas can earn extra money by renting out their unused parking spaces to those in need. This strategy could help malls to manage parking more effectively during peak shopping hours. A customer can save time by reserving a parking space ahead of time.

A new topology of photovoltaic (PV) based transformerless dynamic voltage restorer (TDVR) with high gain DC-DC boost converter is proposed to mitigate voltage sag and swell, interruptions, and unbalanced outages in single-phase grid. The proposed PV-DVR high DC-DC boost converter is comprised of one MOSFET switch and three inductors with second order generalized integrator (SOGI) based unit vector template (UVT) control to enhance the effectiveness of the system for grid-connected renewable applications. The high voltage (HV) gain is achieved by this proposed converter through its soft-switching ability and coupled inductor arrangement with continuous conduction mode (CCM). In the proposed high gain DC-DC converter, the MOSFET IRFP260 power switch is preferably used for low voltage stress and also minimum on-state resistance. The mathematical analysis of the proposed converter is also discussed in this paper. The proposed converter is interfaced with an SOGI-PLL controller with input voltage (24 V), output voltage (230 V), and power rating as 250 W with less number of both passive and active switches. Moreover, to validate the performance and advantage of the proposed converter, the system was simulated by using MATLAB-SIMULINK and laboratory 250 W prototype results are presented to show the effectiveness of the design to limit the voltage sag - 0.1 pu and swell - 1.9 pu and also THD% level within in ceiling limit prescribed in IEEE STD at the load side.

Battery monitoring system for E-vehicles is an emerging area in the field of automobiles and electricity. In India, there haven’t been any existing system for monitoring batteries on a large scale. It hasn’t moved from a personal project to a large-scale application. Apart from this there are existing methodologies which rent the batteries to the user as such and rely entirely on the timely payment made by the user in person. A battery supervision scheme is an automatic system that prospers a rechargeable battery, for example by shielding the battery from functioning exterior its benign operational area, monitoring its state, scheming inferior statistics, commentary that data, monitoring its situation, confirming it and / or complementary it. The BMS will also order the reviving of the battery by readdressing the improved energy back into the battery pack. It is used rummage-sale only for dealing the charging and discharging of battery. With our proposed system, the battery management system can be integrated with the monitoring structure which is capable of both managing, monitoring and logging the data to an online database. This system monitors the battery parameters like voltage, current, temperature, power and state of charge. These parameters are then sent and stored in a database via internet which is then shown to the user by means of an android app. When sufficient dataset is available in the database, intelligent machine learning algorithms can be used to predict the life cycle of the battery and give suggestions to the user regarding the time and duration of each charge cycle, the health of the battery and many more. If implemented in battery rental companies, the battery can only be charged when the rent is paid by the user on time.

Currently humans are employed for temperature screening and mask identification in public places to prevent the spread of COVID-19. We have temperature testing systems for all scanning entrances, but manual temperature scanning has numerous drawbacks. The staff isn’t well-versed in the use of temperature scanners. When reading values, there is space for human error. People are often allowed entry despite higher temperature readings or the lack of masks. For large crowds, a manual scanning device is ineffective. Hence there arises a need to have an automatic system that checks for temperature and mask. We propose a fully automated temperature scanner and entry provider system to solve this issue. The system uses a contactless temperature scanner and a camera to capture image. If a high temperature or the absence of a mask is observed, the scanner is connected to a gate like structure that prevents entry. To monitor the entire process, the device uses a temperature sensor and camera connected to a Raspberry Pi system. The main theme of this paper is to automate the entire covid scanning process for reducing risk of spread COVID-19 in highly crowded places such as malls, schools and colleges.

The aim of this Research is to Propose a System to measures the leakage current in the industries Which leads to power wastage and causes insufficient power supply.This Research's need is saving the leakage current from the industries, which will be recycled and giving back to the station as a source.The main Objective of this Research is saving leakage current from the industries.First the leakage current and earth current will measured using sensor and the measured current will be linearised and filtered.Then the recycled current will be stored in the battery when the storage unit reaches its maximum level it will sending back to the sub station to reuse the current. Even in this 21st century many of the several places suffer power cuts and also many small scale industries are affected because of the power wastage. This Research provides a solution for power wastage by recycling the wasted current and also this Research, it has setup to find any fault in earthing will be detected. By implementing this method, we can able to reduce the massive wastage of power.

A reliable and secure routing protocol for Wireless Sensor Networks should be easy to maintain, reliable and cost-efficient. In this paper, we propose a hybrid routing algorithm using Ant Colony Optimization and Minimum Hop Count scheme. The proposed hybrid methodology provides an optimal routing path that ensures balanced and minimal energy consumption. The hybrid algorithm is unique in maintaining network topology, balancing network load and searching for the optimal route. The proposed algorithm with the WSN model is implemented in C++ and the simulation output proves our algorithm to outperform other similar routing algorithms.The proposed work indicates animprovement in network lifetime, success rate in finding the best solution and rate of convergence. The existing techniques are reviewed and their strengths and weaknesses are diagnosed and compared with our proposed hybrid methodology that integrates the strengths of both the algorithms.

Electrical Vehicles are being made mandatory in many countries and India hopes to accomplish this feat by 2030. Out of the many problems like charging infrastructure, range anxiety, cost, the main hurdle to be considered is the raw materials required for the battery. The 2W segment looks promising in India compared to other markets owing to a lot of reasons. Few major players have introduced electric models in the 4W segment and many are expected to release new ones in the coming months. It is also seen that incentives from the Government have boosted the sales in many countries and the same is being done in India. This paper focuses on the supply chain of the batteries, Energy required for the complete transition to EV and also discusses cyclic economy in the EV industry which could churn out a lot of opportunities and reduce the cost of the vehicles. The paper also specifies the challenges being faced currently and also emphasizes ways in which the problem becomes an opportunity in a side-by-side basis.

Virtual power plant (VPP) is one of the developing concepts for integrating of renewable energy source (RES) photovoltaic (PV), air turbines (WT), or integrated heat and power generators as a single energy plant, coordinated and constructed. This paper proposes quick search optimization algorithm based monitoring and control of the virtual power station in the distribution network. The proposed algorithm is used to manage electrical power in the distribution network to reduce the purchased power of the network. This objective is achieved through optimal selection of renewable-based distributed generators, control of load and optimization of energy storage components. In these proposes, two main renewable energy sources of wind power and solar power are integrated with grid to manage the energy in VPP. In this, quick search algorithm is used for forecasting the generate power from windmill and solar cell based on wind circulation and earth temperature, respectively, and also calculating power demand which depends on the load condition. The MATLAB software is used to model the VPP and the performance analysis of generating power of sources and power demand of load.

In the today Internet era, protection of digital content during transmission is an indigent. Alphanumeric watermarking is a resolution to the copyright defense than the endorsement of information into the system. In exhibit watermarking calculation, wellbeing of such watermarking process is moderately low. For expanding the soundness, an approach is presented, which is contourlet change with neuro-fuzzy-based watermark inserting process. The conventional approaches having loss during data recovery, this situation will be resolved using proposed watermarking scheme and also increase the security of watermarked image. The proposed color image watermarking scheme binary image is embedded over the shading image which utilizes contourlet and converse contourlet calculation for preprocessing of an image and neuro-fuzzy calculation to implant the bits in the green plane of an image. After completing the watermarking process, the results are analyzing using the quality assessment metrics like Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) etc., It is implemented using MATLAB R2013 software. The developed MATLAB code is converted into Hardware Description Language (HDL) and then implemented for Virtex-5 L110T Field Programmable Gate Array (FPGA) kit.

In the today Internet era, protection of digital content during transmission is an indigent. Alphanumeric watermarking is a resolution to the copyright defense than the endorsement of information into the system. In exhibit watermarking calculation, wellbeing of such watermarking process is moderately low. For expanding the soundness, an approach is presented, which is contourlet change with neuro-fuzzy-based watermark inserting process. The conventional approaches having loss during data recovery, this situation will be resolved using proposed watermarking scheme and also increase the security of watermarked image. The proposed color image watermarking scheme binary image is embedded over the shading image which utilizes contourlet and converse contourlet calculation for preprocessing of an image and neuro-fuzzy calculation to implant the bits in the green plane of an image. After completing the watermarking process, the results are analyzing using the quality assessment metrics like Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) etc., It is implemented using MATLAB R2013 software. The developed MATLAB code is converted into Hardware Description Language (HDL) and then implemented for Virtex-5 L110T Field Programmable Gate Array (FPGA) kit.

This paper presents a PV based high level hybrid multilevel inverter. SEPIC converter is the technologically advanced converter derived from the buck-boost converter. The proposed scheme is used in the SEPIC-converter to eradicate the output ripples and well enhance the output voltage level. Cascaded H Bridge and Neutral point clamped (NPC) inverter topologies are combined to obtain 127 level of output voltage using reduced number of switches and DC sources. To increasing the voltage level, Total Harmonic Distortion (THD) can be reduced and hence reduction in size of the filter. Simulation work is done using MATLAB and then to verify the performance of suggested scheme.