Research Article
Reimagining the Parking Experience: Seamless EV Charging in Multi-Level Garages for the Future
Kanishka Sharma*
Issue:
Volume 12, Issue 4, August 2024
Pages:
62-70
Received:
17 April 2024
Accepted:
25 June 2024
Published:
26 September 2024
DOI:
10.11648/j.jeee.20241204.11
Downloads:
Views:
Abstract: The rapid growth of the electric vehicle (EV) market demands a significant overhaul of current parking infrastructure. This paper explores the future of multi-level parking garages with a particular focus on integrating efficient and seamless EV charging solutions. Traditional parking structures are increasingly inadequate for the evolving needs of EV drivers, presenting numerous limitations. This study begins by dissecting these limitations, highlighting the inadequacies in accommodating the rising number of EVs and the inefficiencies in current charging setups. We then analyze state-of-the-art charging technologies, examining their potential to address these challenges. These include wireless charging pads, retractable charging units, and bi-directional charging systems, which promise not only to enhance user convenience but also to support grid stability and offer cost benefits through demand-response programs. Companies like WiTricity and Parkopedia are pioneering these technologies, indicating a clear industry trend towards innovation. Finally, we propose a visionary model for multi-level parking garages, designed to meet the diverse requirements of future EV users. This model features advanced automation, smart parking management, and integrated charging solutions that collectively create a user-friendly and efficient environment. By anticipating and addressing the future needs of EV drivers, this vision aims to revolutionize the way we think about parking infrastructure, making it more adaptable, resilient, and sustainable. Through this comprehensive analysis and futuristic proposal, the paper seeks to contribute to the ongoing discourse on urban infrastructure development in the age of electric mobility, providing a blueprint for the next generation of parking solutions.
Abstract: The rapid growth of the electric vehicle (EV) market demands a significant overhaul of current parking infrastructure. This paper explores the future of multi-level parking garages with a particular focus on integrating efficient and seamless EV charging solutions. Traditional parking structures are increasingly inadequate for the evolving needs of...
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Research Article
UNNIGSA: A Unified Neural Network Approach for Enhanced Stutter Detection and Gait Recognition Analysis
Ravikiran Reddappa Reddy*,
Santhosh Kumar Gangadharaih
Issue:
Volume 12, Issue 4, August 2024
Pages:
71-83
Received:
20 July 2024
Accepted:
2 September 2024
Published:
26 September 2024
DOI:
10.11648/j.jeee.20241204.12
Downloads:
Views:
Abstract: Stuttering, also known as stammering, is a speech disorder characterized by involuntary disruptions or disfluencies in a person's flow of speech. These disfluencies may include repetitions of sounds, syllables, or words; prolongations of sounds; and interruptions in speech known as blocks. This paper introduces Unified Neural Network for Integrated Gait and Speech Analysis (UNNIGSA), methodology that synergizes stutter detection (SD) and gait recognition through a unified neural network architecture. UNNIGSA is engineered to address two distinct yet interrelated challenges: the accurate detection of stuttering for enhanced beneficial interventions and the precise identification of individuals based on gait analysis. The system integrates a global attention mechanism to meticulously highlight salient features within speech patterns, thereby improving the accuracy of stutter classification and offering a potential leap forward in speech therapy practices. Additionally, UNNIGSA incorporates novel data processing techniques to manage the class imbalance prevalent in stuttering speech datasets, resulting in significantly enhanced performance over existing models. The methodology also extends the functionality of automatic speech recognition (ASR) systems, fostering greater inclusivity for individuals with speech disorders and enabling their more seamless interaction with virtual assistant technologies. Overall, UNNIGSA sets a new standard in the domains of speech disorder treatment and biometric identification, offering innovative solutions to long-standing challenges and paving the way for more inclusive and secure applications.
Abstract: Stuttering, also known as stammering, is a speech disorder characterized by involuntary disruptions or disfluencies in a person's flow of speech. These disfluencies may include repetitions of sounds, syllables, or words; prolongations of sounds; and interruptions in speech known as blocks. This paper introduces Unified Neural Network for Integrated...
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