Artificial Intelligence Techniques Final Year Projects with Source Code

Byadmin Final Year Projects

Artificial Intelligence Techniques Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These Artificial Intelligence Techniques 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.

Artificial Intelligence Techniques Final Year Projects

  1. A Network Intrusion Detection System for Building Automation and Control Systems
    This project focuses on improving security for building automation systems, like smart lighting and HVAC controls. The researchers designed a network intrusion detection system that can detect attacks across different building system protocols, not just one. They built and tested a working version for KNX, a common building automation protocol, using a real installation to show it works. The system aims to make smart buildings safer from cyber threats.
  2. A Survey on Artificial Intelligence-Based Acoustic Source Identification
    This project focuses on identifying sources of sound, like machinery noise or environmental sounds, using computers. Traditionally, experts had to analyze sound patterns manually, which is hard when there is a lot of data. The study reviews how artificial intelligence can help automatically recognize these sound sources. It also looks at applications in areas like healthcare, manufacturing, and underwater monitoring.
  3. Application of Artificial Intelligence Techniques for BrainComputer Interface in Mental Fatigue Detection A Systematic Review
    This project reviews how mental fatigue, which affects both the mind and body, can be detected using brain-computer interfaces and artificial intelligence. The study analyzed research from 2011 to 2022 and identified gaps in using these systems for automated mental fatigue monitoring. It also explains the challenges, AI techniques, and future directions for improving detection and practical implementation. The goal is to guide better and faster methods to recognize and manage mental fatigue.
  4. Trust Management in Vehicular Ad-Hoc Networks Extensive Survey
    This project surveys how modern smart transportation systems use vehicles that communicate with each other to improve safety, traffic flow, and comfort. It focuses on Vehicular Ad hoc Networks (VANETs) and explores how technologies like cloud computing, AI, and blockchain make these networks more reliable and secure. The study reviews existing methods for managing trust and security in VANETs and highlights current challenges and future research directions.
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