An Optimized & Data-Driven Approach for Real-Time Slot Allocation in Smart Parking SystemConference
This paper presents a robust, data-driven framework for intelligent urban mobility, focusing on real-time slot allocation in smart parking ecosystems. By integrating IoT-based sensor networks with optimized resource allocation algorithms, the system dynamically manages parking availability to minimize search time and reduce traffic congestion. The research utilizes real-time data analytics to predict occupancy patterns, providing […]
Advanced Handwritten Text Recognition and Analysis System
This paper introduces an advanced end-to-end framework for Handwritten Text Recognition (HTR) that effectively bridges the gap between traditional optical character recognition and modern deep learning. The system utilizes a novel fusion of Bidirectional Long Short-Term Memory (BiLSTM) networks and Convolutional Neural Networks (CNNs) to capture both complex spatial features and sequential dependencies in unsegmented […]
Transformative impact of explainable artificial intelligence: bridging complexity and trust
This research addresses the growing ‘black-box’ nature of AI by evaluating Explainable Artificial Intelligence (XAI) as a crucial bridge between model complexity and human trust. The paper provides a comprehensive analysis of model-specific, model-agnostic, and hybrid XAI methodologies across critical sectors like healthcare, finance, and industrial management. It highlights how transparency in decision-making can maximize […]
Hybrid Convolutional Neural Network for Robust Attack Detection in Wireless Sensor Networks
This paper proposes an intelligent hybrid intrusion detection model designed to secure Wireless Sensor Networks (WSNs) against evolving cyber threats in the IoT landscape. By integrating an Enhanced Black Widow Optimization (EBWO) algorithm with a Bidirectional Gated Recurrent Unit (BiGRU) and Attention Mechanism (ATTN), the framework achieves high-precision detection of malicious activities. The model effectively […]
BlockchaināAssisted Trust Framework for Increased Survivability in Internet of Vehicles
This paper introduces a decentralized trust framework that synergistically combines Blockchain technology with advanced trust models to enhance the security and survivability of the Internet of Vehicles (IoV). By utilizing an immutable distributed ledger, the framework ensures data integrity and protects vehicular networks against malicious entities broadcasting false event messages. The proposed model features a […]
A Systematic Review on Text Summarization: Techniques, Challenges, Opportunities
This comprehensive review provides a critical analysis of the evolution of Text Summarization (TS) techniques, ranging from early statistical methods to modern Transformer-based Large Language Models (LLMs). The paper meticulously evaluates the architectural differences between extractive and abstractive summarization, emphasizing the importance of linguistic coherence and factual accuracy. It identifies current research gaps, such as […]
Review on Applying Tier in Multi Cloud Database (MCDB) for Security and Service Availability
This review examines the application of tiered architecture in Multi Cloud Databases to enhance security and service availability. By distributing database functions across multiple cloud tiers, the approach improves fault tolerance, load balancing, and data protection. The study analyzes security mechanisms such as access control and encryption alongside availability strategies like redundancy and failover. These […]
A Noval Real-Time Map Matching Algorithm for Landmark & Uncertainty
This research introduces a novel real-time map matching algorithm that improves navigation accuracy by integrating landmark information and uncertainty modeling. The approach evaluates vehicle trajectories against road networks while accounting for sensor noise and positional ambiguity. By leveraging landmarks and confidence estimation, the algorithm delivers more reliable location tracking in complex urban environments. The proposed […]
Radar Transmogrification Technology: Support for Unmanned System
This study explores radar transmogrification technology as a support mechanism for unmanned systems operating in dynamic environments. By transforming radar signals into actionable intelligence, the approach improves detection accuracy, tracking reliability, and system coordination. The research highlights how radar-based communication enhances autonomy and situational awareness for aerial, ground, and marine unmanned platforms. These advancements strengthen […]
Inscribe the Exigency of Map Matching Performance for Curve Navigation on Road/Highways
This study analyzes the importance of map matching performance for accurate navigation on curved roads and highways. By evaluating how GPS trajectories align with complex road geometries, the research highlights challenges caused by sharp curves and signal deviations. Improved map matching techniques enhance positional accuracy, route consistency, and driving safety. The findings support advanced navigation […]