Blazingprojects Mobile App
📚 Over 50,000 Research Thesis
📱 100% Offline: No internet needed
📝 Over 98 Departments
🔍 Thesis-to-Journal Publication
🎓 Undergraduate/Postgraduate Thesis
📥 Instant Whatsapp/Email Delivery
Computer Science
Showing 1-0 of 1,827 Thesis
A Framework for Trustworthy AI Model Debugging and Validation...
Increasing deployment of complex AI systems across critical domains has amplified concerns about model reliability, transparency, and accountability, necessitat...
Smart City IoT Security Governance: A Case Study of City Councils in Scandinavia...
Smart City IoT security governance has emerged as a critical challenge for urban administrations deploying pervasive Internet of Things (IoT) infrastructures ac...
Comparative Analysis of Edge AI Frameworks in Real-Time Inference ...
Recent advances in edge computing have amplified the deployment of AI inference at the network edge, yet developers face a trade-off between latency, energy con...
Federated Learning for Real-Time Anomaly Detection in Smart Grids...
This study addresses the rising need for secure, scalable, and timely detection of anomalies in contemporary smart grids, where conventional centralized anomaly...
Empirical Evaluation of Edge Computing Offloading in Smart Homes...
The rapid growth of smart homes and the proliferation of latency-sensitive and compute-intensive applications have underscored the need for efficient edge compu...
Edge-Optimized Federated Learning for IoT Devices ...
Edge-Optimized Federated Learning for IoT Devices abstracts a practical, scalable approach to harness distributed data at the network edge while addressing reso...
A Unified Framework for Explainable Collaborative Machine Learning Systems...
The rapid adoption of collaborative machine learning (CML) across diverse domains has amplified the need for models that are not only accurate but also transpar...
Optimizing Edge AI for Rural Healthcare: A Case Study in Kenya...
The rapid expansion of telemedicine and digital health initiatives in Kenya’s rural regions has highlighted a persistent gap between centralized cloud-based A...
Comparative Analysis of Edge AI Frameworks for IoT Inference Performance...
This study addresses the escalating demand for efficient on-device inference in Internet of Things (IoT) environments by systematically comparing contemporary e...
Edge-Aware Federated Learning for IoT Networks with Heterogeneous Data...
Edge-Aware Federated Learning (EA-FL) is explored to address the challenges of training robust machine learning models in Internet of Things (IoT) ecosystems ch...
The Impact of AI-Assisted Debugging on Software Maintenance Efficiency...
The rapid adoption of AI-assisted debugging tools in software engineering promises to transform maintenance efficiency by accelerating fault localization, reduc...
Adaptive Edge-Cloud Mobile Apps Orchestration Framework ...
This study investigates the design, implementation, and evaluation of an adaptive edge-cloud orchestration framework for mobile applications to optimize perform...
A Unified Framework for Explainable Front-to-Back AI Pipelines...
This study addresses the escalating opacity of end-to-end AI systems by proposing a unified framework that integrates explainability across front-end data prepr...
Edge AI for Urban Traffic Signal Optimization: A City Council Case Study...
The rapid urbanization of metropolitan areas has amplified the inefficiencies in traditional traffic signal control, resulting in increased congestion, elevated...
Comparative Analysis of Edge AIFrameworks on Resource-Limited Devices...
The rapid proliferation of edge computing and on-device intelligence has intensified the need to evaluate how diverse AI frameworks perform within resource-cons...
Edge-Driven Federated Learning for Healthcare Data Privacy...
The increasing digitization of health records and the proliferation of edge devices in clinical environments heighten the risk of data breaches and compromise p...
Evaluating Edge AI for Real-Time Industrial Anomaly Detection...
Industrial manufacturing increasingly relies on edge AI to meet the demand for real-time anomaly detection while preserving data locality, reducing latency, and...
Edge-Optimized Federated Learning for Resource-Constrained IoT Networks...
Edge-Optimized Federated Learning (EOFL) addresses the critical challenge of deploying machine learning in resource-constrained IoT networks where data privacy,...
A Theory of Energy-Efficient Federated Learning Architecture and Protocols...
This study addresses the escalating energy and communication costs inherent in federated learning (FL) deployments, where heterogeneous devices contribute model...
Edge Computing for Smart Warehousing: A Case Study at GlobalLogistics Corp....
Edge computing-enabled smart warehousing promises reduced latency, improved real-time analytics, and resilient operations in logistics networks. As GlobalLogist...
Comparative Analysis of Edge AI Frameworks on Latency and Energy Use...
Edge AI has emerged as a critical paradigm for deploying intelligent services with low latency and reduced cloud dependency. The study addresses the practical c...
AI-Enabled Adaptive Network Security System for Real-Time Threat Detection...
The rapid proliferation of interconnected devices and digital infrastructures has elevated the complexity and scale of cyber threats, necessitating innovative a...
Evaluating the Effectiveness of AI-Powered Chatbots in Customer Service Satisfaction...
In the evolving landscape of digital customer interaction, AI-powered chatbots have become integral to service delivery, yet their actual efficacy in enhancing ...
Design and evaluation of a privacy-preserving distributed machine learning system...
The rapid proliferation of data-driven applications across sectors such as healthcare, finance, and government has heightened the need for effective, scalable, ...
A Framework for Adaptive Real-Time Cybersecurity Threat Detection Using Machine Lear...
The rapid evolution and increasing sophistication of cyber threats pose significant challenges to traditional cybersecurity measures, necessitating the developm...
Optimizing Cybersecurity Protocols in Financial Institutions through Machine Learnin...
In an era characterized by escalating cyber threats and increasing digitization within the financial sector, financial institutions are compelled to enhance the...
Comparative Analysis of Machine Learning Algorithms for Cybersecurity Threat Detecti...
Cybersecurity threats continue to evolve rapidly, posing significant risks to organizational integrity, data confidentiality, and operational continuity. Tradit...
Designing AI-Driven Cybersecurity Systems for Real-Time Threat Detection and Respons...
The increasing prevalence and sophistication of cyber threats pose significant challenges to traditional cybersecurity mechanisms, necessitating the development...
Assessing the Impact of User Interface Design on Mobile App Accessibility for Elderl...
The rapid proliferation of mobile applications has transformed communication, access to information, and service delivery; however, usability challenges persist...
Design and evaluation of an energy-efficient IoT sensor data compression scheme...
The proliferation of Internet of Things (IoT) devices in diverse application domains has underscored the critical need for efficient data transmission and energ...
