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Artificial Intelligence Final Year Topic: Design and Evaluation of Object Detection on Low-Cost Hardware

This Artificial Intelligence final year project examines balancing detection accuracy and inference cost on an available modest device through a bounded AI prototype with an explicit baseline and evaluation dataset.

Why choose this project topic?

A study of balancing detection accuracy and inference cost on an available modest device gives this topic a concrete purpose beyond simply adding an AI model. Comparing detection precision, latency and memory consumption helps a student demonstrate capability, inspect failure cases and explain where human review or a simpler method remains necessary.

How effectively can object detection on low-cost hardware support balancing detection accuracy and inference cost on an available modest device, evaluated using detection precision, latency and memory consumption?

Choose a feasible licensed or synthetic dataset and available compute budget, then agree a narrow evaluation for balancing detection accuracy and inference cost on an available modest device with your supervisor.

Proposed project objectives

  1. 01Define the task, evidence and evaluation assumptions for balancing detection accuracy and inference cost on an available modest device.
  2. 02Use a licensed object dataset, compare model sizes and quantisation settings and measure latency with repeated device-level runs.
  3. 03Measure detection precision, latency and memory consumption against a stated baseline and analyse failure cases.

A suggested research approach

Use a licensed object dataset, compare model sizes and quantisation settings and measure latency with repeated device-level runs. Check dataset permissions and keep evaluation examples separate from model development. Record model versions, prompts or training settings, then compare detection precision, latency and memory consumption using repeatable runs and retain incorrect outputs for a transparent limitations discussion.

What you will need

  • Licensed object images
  • Available test device
  • Model profiling tools

Keep your project scope clear

Measured performance depends on the specific device and does not establish safety for autonomous control. Generated project writing does not include a trained or deployed AI application.

Artificial Intelligence project chapter outline

Use this outline as a starting point. You can edit the chapter titles to match your department’s format during setup.

  1. Chapter 1Introduction
  2. Chapter 2Literature Review
  3. Chapter 3System Analysis and Design
  4. Chapter 4System Implementation and Testing
  5. Chapter 5Summary, Conclusion and Recommendations

Turn this topic into your own final year project.

Your title, department, research question and outline are ready. Add your institution, personalise the details and continue to your project workspace.

Generate the Complete Project Generation uses your word balance. Review the draft and supply your own verified research findings.