You will get fire and smoke detection system with 100% accuracy
Project details
you will get a high-performance YOLO-based model for fire and smoke detection. This system is designed to integrate directly with your existing CCTV footage. It performs 24/7 real-time detection, accurately identifying and localizing the very first visual signs of fire or smoke from any surveillance camera feed. This capability is ideal for robust safety monitoring, providing the critical early alerts needed for rapid response. My solution is a vital upgrade for any smart security system with 100% accuracy, and unwavering reliable performance.
Machine Learning Tools
Keras, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, TensorFlowWhat's included $500
These options are included with the project scope.
$500
- Delivery Time 1 day
- Number of Revisions 1
- Number of Model Variations 1
- Number of Scenarios 2
- Model Validation/Testing
- Model Documentation
About Muhammad
Full-Stack Data Scientist | End-to-End ML System Development
Sialkot, Pakistan - 10:48 am local time
Many AI projects fail to deliver value because they get stuck in the prototype phase or become unmanageable. My comprehensive skill set bridges the gap between data science and software architecture. I begin with a rigorous requirements analysis, architecting systems using Domain-Driven Design (DDD) to ensure the code is modular, testable, and perfectly aligned with your business logic. This approach prevents technical debt and ensures your system can scale and evolve.
I offer strategic leadership and hands-on development across the full AI project lifecycle:
✅ Phase 1: Strategy & Design (DDD): Collaborative requirements gathering, feasibility analysis, and creation of comprehensive system architecture and design documents (Use Cases, ERDs, DDD Bounded Contexts).
✅ Phase 2: Data & Model Development: Data pipeline engineering, feature engineering, and the development, training, and validation of state-of-the-art machine learning, deep learning (CNNs), and Generative AI (GANs) models.
✅ Phase 3: Full-Stack Application & Deployment: Building the necessary back-end infrastructure and REST APIs for model deployment, and developing front-end dashboards for user interaction.
✅ Phase 4: Testing & Maintenance: Authoring and executing rigorous test plans to ensure system reliability and performance, and establishing MLOps best practices for ongoing model monitoring.
Technical Toolkit:
Full-Stack Capabilities: Python (Flask/Django), SQL/NoSQL Databases, REST APIs, Docker, AWS
ML/DL Expertise: TensorFlow, PyTorch, Keras, Scikit-learn, OpenCV, GANs
Project Management: Agile Methodologies, System Design (UML), Domain-Driven Design (DDD)
If you need a partner who can take ownership of your entire AI project and deliver a polished, production-grade solution, let's connect. I am ready to help you build something truly impactful from the ground up.
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Trained Model
I will give you trained YOLO model for fire and smoke detection. You just have to plug it in any CCTV feed. It would give its results afterward