Optimizing Energy Supply for Full Electric Vehicles in Smart Cities: A Comprehensive Mobility Network Model DOI Creative Commons
Víctor Fernández Pallarés, Virgilio Pérez, Rosa Roig

и другие.

World Electric Vehicle Journal, Год журнала: 2024, Номер 16(1), С. 5 - 5

Опубликована: Дек. 27, 2024

The integration of Full Electric Vehicles (FEVs) into the smart city ecosystem is an essential step towards achieving sustainable urban mobility. This study presents a comprehensive mobility network model designed to predict and optimize energy supply for FEVs within cities. integrates advanced components such as Charge Station Control Center (CSCC), charging infrastructure, dynamic user interface. Important aspects include analyzing power consumption, forecasting demand, monitoring State (SoC) FEV batteries using innovative algorithms validated through real-world applications in Valencia (Spain) Ljubljana (Slovenia). Results indicate high accuracies SoC tracking (error < 0.05%) demand (MSE ~6 × 10−4), demonstrating model’s reliability adaptability across diverse environments. research contributes development resilient, efficient, frameworks, emphasizing real-time data-driven decision-making management.

Язык: Английский

Enhancing predictive maintenance in automotive industry: addressing class imbalance using advanced machine learning techniques DOI Creative Commons
Yashashree Mahale,

Shrikrishna Kolhar,

Anjali S. More

и другие.

Deleted Journal, Год журнала: 2025, Номер 7(4)

Опубликована: Апрель 12, 2025

Язык: Английский

Процитировано

0
Strategic Integration of Predictive Maintenance Plans to Improve Operational Efficiency of Smart Grids DOI
Shaman Bhat, Ashwin Kavasseri Venkitaraman

Опубликована: Июнь 28, 2024

Язык: Английский

Процитировано

1
Modeling of Microwave Antenna Systems DOI
Islam Islamov

Опубликована: Дек. 24, 2024

Язык: Английский

Процитировано

0
Development and Implementation of an ESP32 IOT-Based Smart Grid for Enhanced Energy Efficiency and Management DOI Creative Commons
Aliyu Sabo, Hamza Ozovehe Suleiman,

Yakubu Dahiru

и другие.

European Journal of Theoretical and Applied Sciences, Год журнала: 2024, Номер 2(3), С. 565 - 576

Опубликована: Май 1, 2024

The advent of the Internet Things (IoT) has ushered in transformative changes across diverse sectors, notably energy domain, spawning innovative concept smart grids. This research delves into development and deployment an IoT-based prototype grid system, aiming to augment efficiency, reliability, management. system integrates current voltage sensors, coupled with ESP32 microcontroller, enabling real-time monitoring, control, optimization electrical grid. Leveraging Google Firebase as a cloud service for storing data (current, voltage, power), includes architectural model simulating industrial, commercial, residential areas within city. features illumination controlled by three output relays linked via 2N222 transistor. A control interface, developed JavaScript React, interfaces server manage relay states. interface empowers distribution company remotely designate powered sections, mimicking scenarios like sectional maintenance or compulsory load shedding. collaborative effort mini-grid design underscores efficiency gains achieved through IoT implementation conventional systems, emphasizing time labor savings

Язык: Английский

Процитировано

0
Intelligent Fault Diagnosis in Industrial Machinery: Leveraging AI with LSTM Autoencoder for Enhanced Fault Detection DOI Creative Commons

Rupa Devi B,

G. Suseela,

Ranjith Kumar Painam

и другие.

Journal of Machine and Computing, Год журнала: 2024, Номер unknown, С. 931 - 942

Опубликована: Окт. 5, 2024

Machinery Fault Detection (MFD) is an important process in contemporary industrial systems, where it predicts possible physical failures before they lead to a serious problem. This uses multiple technologies monitor machine statuses (algorithms, data gathering systems and sensors) Using servo-motor driven actuator for deployment, the Locking Mechanism pre-assembled into OEM ATE will enable predictive failure mode identification (via monitoring warnings of operational parameters i.e., vibration, temperature or auditory signals in-built MFD systems) leading Prophylactic maintenance critical bottlenecks can occur. The dataset we used our study was collected from Kaggle called SpectraQuest Simulator (MFS) Alignment-Balance-Vibration (ABVT). We LSTM Autoencoder, KNN, SVM DNN analyzed data. Our Autoencoder model very accurate achieved precision, recall, accuracy F-score 99%. worked on large scale datasets. It help system detect faults predict their evolution over time, so you save costs increase production your factory. More research practical efficiency these models real-time across different settings create path towards improved scalable solutions.

Язык: Английский

Процитировано

0
Sustainable materials for corrosion-resistant energy harvesting: a conceptual framework for innovations in biodegradable solutions for nuclear applications DOI Creative Commons

Thompson Odion Igunma,

Adeoye Taofik Aderamo,

Olisakwe Henry Chukwuemeka

и другие.

Engineering Science & Technology Journal, Год журнала: 2024, Номер 5(10), С. 2911 - 2933

Опубликована: Окт. 16, 2024

The demand for sustainable materials in energy harvesting technologies has led to significant advancements, particularly the development of biodegradable solutions nuclear applications. This conceptual framework explores innovations corrosion-resistant that combine sustainability with enhanced performance systems. integration into applications presents an opportunity reduce environmental impact while maintaining efficiency and safety standards harsh conditions. review focuses on dual challenge corrosion resistance biodegradability, which are critical long-term operation environments. Traditional used reactors, such as stainless steels superalloys, often struggle disposal issues. By contrast, offer potential these challenges, recent providing sufficient radiation corrosive investigates properties polymers, composites, coatings have been adapted A central theme this is application nanostructured hybrid designed withstand extreme conditions within reactors. These exhibit self-healing passivation capabilities, contributing their resistance. also discusses various strategies optimizing materials, including surface treatments, alloying, coating techniques, enhance both durability. Moreover, highlights ongoing research bio-based scalability Although challenges remain ensuring consistent over extended periods, prospects integrating biodegradable, systems promising. In conclusion, outlines revolutionizing by addressing resistance, sustainability, material lifecycle management. Continued innovation field could transform technologies, driving shift toward greener, more systems.. Keywords: Sustainable Materials, Corrosion Resistance, Energy Harvesting, Biodegradable Solutions, Nuclear Applications, Nanostructured Bio-Based Composites.

Язык: Английский

Процитировано

0
Enhancing System Efficiency through AI, Edge Computing, and Resource Optimization in Modern Infrastructure DOI Open Access

Balusamy Nachiappan

International Journal of Innovative Science and Research Technology (IJISRT), Год журнала: 2024, Номер unknown, С. 1107 - 1112

Опубликована: Окт. 28, 2024

This paper explores innovative strategies for enhancing system efficiency in modern infrastructure by integrating artificial intelligence (AI), edge computing, and resource optimization techniques. As the complexity of systems increases, traditional methods often fall short addressing evolving demands operational reliability. By leveraging AI algorithms predictive analytics allocation, utilizing computing real-time data processing, organizations can significantly improve performance responsiveness. The study examines case studies that highlight successful implementations these technologies across various sectors, including monitoring, grid maintenance. Insights from this research provide a framework practitioners to adopt advanced methodologies, ultimately leading more resilient efficient systems.

Язык: Английский

Процитировано

0
Optimizing Energy Supply for Full Electric Vehicles in Smart Cities: A Comprehensive Mobility Network Model DOI Creative Commons
Víctor Fernández Pallarés, Virgilio Pérez, Rosa Roig

и другие.

World Electric Vehicle Journal, Год журнала: 2024, Номер 16(1), С. 5 - 5

Опубликована: Дек. 27, 2024

The integration of Full Electric Vehicles (FEVs) into the smart city ecosystem is an essential step towards achieving sustainable urban mobility. This study presents a comprehensive mobility network model designed to predict and optimize energy supply for FEVs within cities. integrates advanced components such as Charge Station Control Center (CSCC), charging infrastructure, dynamic user interface. Important aspects include analyzing power consumption, forecasting demand, monitoring State (SoC) FEV batteries using innovative algorithms validated through real-world applications in Valencia (Spain) Ljubljana (Slovenia). Results indicate high accuracies SoC tracking (error < 0.05%) demand (MSE ~6 × 10−4), demonstrating model’s reliability adaptability across diverse environments. research contributes development resilient, efficient, frameworks, emphasizing real-time data-driven decision-making management.

Язык: Английский

Процитировано

0