The objective of this paper is to build up a LoRa-based smart agricultural management and monitoring system using Wireless Sensor Networks (WSNs) in rural areas, in order to replace the current tec...

An efficient LoRa-based smart agriculture management and monitoring system using wireless sensor networks

Towards health-aware energy management strategies in fuel cell hybrid electric vehicles: A review

ABSTRACT Intelligent Transport System (ITS) intentions to attain traffic efficiency by diminishing traffic difficulties. It supplies information like traffic issues, real-time traveling information, parking availability, etc., in advance to the users who are connected with the smart cities that ensure travelers’ safety and comfort. This ITS technique should merge with Electric Vehicles (EVs) because nowadays, EVs have become familiar in the last decade owing to the requirement to cut greenhouse gas emissions and fossil fuels. However, traffic jams caused by EVs driven to the charging stations (CSs) can result in the complex charging scheduling of EVs. Therefore, an effective algorithm is developed for optimal charging scheduling using the proposed Grey Sail Fish Optimization (GSFO). The proposed charging scheduling algorithm integrates Grey Wolf Optimizer (GWO) and Sail Fish Optimization (SFO). For each EV, the demand when charging is computed. The path used by the EV to travel to the charging station is determined by computing the path decision factor. In comparison to existing techniques, the proposed GSFO-based charging algorithm schedules EVs to charging stations based on the fitness function, and the performance was improved with a traffic density of 26.11 km, a distance of 0.0278 kW, and a power of 2.3377. To be more specific, the proposed GSFO improved when many vehicles were considered.

A novel intelligent transport system charging scheduling for electric vehicles using Grey Wolf Optimizer and Sail Fish Optimization algorithms

/pdf/a-novel-long-short-term-memory-networks-based-data-driven-11mgttew.pdf

A novel long short-term memory networks-based data-driven prognostic strategy for proton exchange membrane fuel cells

Abstract The problem of global warming, along with environmental concerns, has already led governments to replace fossil-fuel vehicles with low-emission electric vehicles (EVs). The energy crisis and environmental problems, such as global warming and air pollution, are essential reasons for the development of electric vehicles (EVs). Electric vehicles are one of the most fascinating and essential fields to emerge in recent years. According to the current report, electric vehicles are attempting to replace older, traditional automobiles. These vehicles not only help to reduce pollution but also to save natural resources. The presence of electric vehicles may cause several problems for the conventional electrical grid due to their grid-to-vehicle (G2V) and vehicle-to-grid (V2G) charging and discharging capabilities. With increased EV adoption, many power quality (PQ) issues in the electrical distribution system arise. With the penetration of EVs in distribution networks, power quality issues such as voltage imbalance, transformer failure, and harmonic distortion are expected to arise. The focus of this research is on exploring and reviewing the issues that the integration of EVs poses for electrical networks. The existing and future situations of electric vehicles’ integration, as well as new research on the subjects, have been reviewed in this paper. This study provides a thorough examination of power quality issues and their mitigating approaches. 

/pdf/electric-vehicle-integrations-impacts-on-power-quality-in-1qzf64qi.pdf

Electric vehicle integration’s impacts on power quality in distribution network and associated mitigation measures: a review

Due to development of latest technologies in the areas of communication and networking, the present businesses are moving to the digital world for effectiveness, convenience and security. Medical images require special safety and confidentiality because critical judgment is done on the information provided by medical images. Digital watermarking is an emerging technology to protect multimedia data for security purpose. This project suggests a comparative performance of digital image watermarking scheme using Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) separately and their performance has been measured by using metrics like PSNR, Quality Index and Elapsed time. Initially, the Medical image is decomposed using image transforms like DCT or DWT. Subsequently, the watermark embedding and extraction process are to be performed in frequency domain transform along with LSB substitution algorithm which is of spatial domain. The performance of the proposed watermarking method is explained with the aid of experimental results.

Effective watermarking algorithm to protect Electronic Patient Record using image transform

The predominant discrimination of an electric vehicle from the conventional gas vehicle is the use of suitable electric drive system. It introduces new elements such as inverters, electric motors, ...

Evaluation of electromagnetic intrusion in brushless DC motor drive for electric vehicle applications with manifestation of mitigating the electromagnetic interference

An intelligent parametric modeling and identification of a 5 kW ballard PEM fuel cell system based on dynamic recurrent networks with delayed context units

In the present modern world, most of the people are using the roadways for transportation purposes. The utilization of roadways increases by one side, on the other side the road accidents are also escalating. The current assessment shows that the reasons for the road accidents are not obeying the traffic rules, inappropriate usage of indicators while turning right or left while driving the vehicles and so on. In peak hours and in traffic times people are speeding up with their vehicle and forgot to use their indicator. This leads to an accident while sudden turning and braking without a proper indication. In order to overcome these types of difficulties, an automatic turning on/off bike indicators using offline GPS navigation system is proposed. The proposed system works in an offline mode and does not need any internet connectivity. By turning on the supply to the board, it will generate the hotspot and it will be connected with Wi-Fi in Mobile Phone. Then the destination is fixed in the mobile application. When turning is available in the way to destination before 100 meters of that turning, indicator will be automatically turned on and after that indicator will be automatically turned off. Thus the proposed work would help the people during the rush hours and also during the emergency situations to avoid accidents.

Automatic Turning ON/OFF Bike Indicator Using Offline GPS Navigation System

Comparative Study of Recurrent and Non Recurrent Neural Network Based Approach for Modeling of PEM Fuel Cell Powered Electric Vehicle

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