Long Short-Term Memory Model Final Year Projects with Source Code

Byadmin Final Year Projects

Long Short-Term Memory Model Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These Long Short-Term Memory Model projects give practical experience and help complete final-year submissions. All projects follow IEEE standards and each project includes source code, project thesis report, presentation, project execution and explanation.

Long Short-Term Memory Model Final Year Projects

  1. A Privacy-Preserving Learning Method for Analyzing HEV Drivers Driving Behaviors
    This project focuses on analyzing how electric and hybrid vehicle drivers behave while driving. Instead of using cameras or GPS that can reveal personal information, it collects data directly from the car’s onboard system. The system uses advanced deep learning models to learn driving patterns and predict risky behavior. When a risky behavior is detected, the car dashboard shows an alert, helping improve safety while keeping driver privacy protected.
  2. Modeling of Blockchain Assisted Intrusion Detection on IoT Healthcare System Using Ant Lion Optimizer With Hybrid Deep Learning
    This project focuses on making healthcare IoT systems more secure. It uses blockchain to protect sensitive medical data and detects unauthorized access using smart algorithms. The system combines advanced deep learning methods with optimization techniques to improve accuracy in spotting intrusions. Tests show it works better than existing methods for keeping IoT healthcare systems safe.
  3. Toward Design of Internet of Things and Machine Learning-Enabled Frameworks for Analysis and Prediction of Water Quality
    This project focuses on monitoring and predicting water quality using smart sensors and machine learning. Sensors collect data on temperature, pH, turbidity, and dissolved solids from a canal in Pakistan. Machine learning models then analyze this data to predict water quality levels and classify water conditions. The study shows that some models, like MLP for prediction and Random Forest for classification, give very accurate results.
  4. Fault Detection for Medium Voltage Switchgear using a Deep Learning Hybrid 1D-CNN-LSTM Model
    This project focuses on detecting faults in medium voltage switchgear, which controls and protects electrical power systems. The researchers developed a new model that learns patterns in the switchgear data over time and frequency. The model can accurately identify different types of faults, including arcing, mechanical issues, and corona. This approach helps improve the safety and reliability of power systems.
  5. AI-Based Epileptic Seizure Detection and Prediction in Internet of Healthcare Things A Systematic Review
    This project studies how brain signals can help doctors detect and predict epileptic seizures. It reviews many research papers that use computer methods to understand these signals. The study looks at techniques like machine learning and deep learning to improve seizure monitoring. It also discusses current challenges and suggests directions for future research.
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Long Short-Term Memory Model Project Synopsis & Presentation

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