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Building a Fire Detection System with Next.js and YOLOv11

Learn how to build a real-time fire detection system using Next.js, YOLOv11, and FastAPI.

(3.8) 6 reviews

127 learners

Level Basic

Course period Unlimited

  • ludgi
Next.js
Next.js
yolo
yolo
Python
Python
FastAPI
FastAPI
React
React
Next.js
Next.js
yolo
yolo
Python
Python
FastAPI
FastAPI
React
React

Reviews from Early Learners

Reviews from Early Learners

3.8

5.0

위즈온

60% enrolled

Good, very clean.

5.0

박민정

100% enrolled

I was able to learn YOLO, FAST API, Node.js, and React all in one course, so it was exactly what I needed. However, there was one piece of code that didn't work on Mac!!..

5.0

nowfire

33% enrolled

I wanted to see YOLOv11. It's very good to be able to watch the installation and operation process through video. I recommend this course.

What you will gain after the course

  • Training and Utilization of Fire Detection AI Model Using YOLOv11

  • FastAPI: Efficient Backend Setup Method

  • Next.js-powered web frontend dev with real-time alert system

  • Data Storage and API Building Using SQLite

  • Real Project-Based AI Model and Web Service Integration

  • Implementing Polling API Requests with TanStack Query

🚀 Learn a real-time fire detection system quickly and easily! 🔥

Does "Deep Learning + Web Development" sound too difficult?
But you don't have to delve deep into complex technologies; you can quickly learn the basics and build your own AI-based projects .

In this lecture, we will use technologies that are widely used in practice, such as Next.js, YOLO, FastAPI, and React.
It contains only the essential information, without unnecessary theories .

Fire detection AI model using YOLO
Build APIs quickly with FastAPI (Python)
Real-time data integration with Next.js + (react) + TanStack Query

We've structured this entire process so you can complete it in just an hour and a half !
For those who want to try it out lightly, we have prepared a simple yet efficient structure .

💡 Feel free to follow along, even without full-stack development experience!
💡 Complete a short and powerful practical project!

🔥 Now it's time to make it yourself! 🔥

🚀 Learn a real-time fire detection system quickly and easily! 🔥

🔥 "Isn't it easy to learn AI projects?"
This course is a short and efficient way to learn a real-time fire detection system using Next.js, YOLO, FastAPI, React, and Python .
You can learn core skills that can be applied immediately in practice while following along without any burden.

Using YOLO as a Fire Detection AI Model
Create a simple API server with FastAPI
Real-time data integration with Next.js & TanStack Query

📌 In particular, we've reduced unnecessary theories and structured it so that you can quickly learn only the important concepts so that you can apply them immediately in real life.
📌 The course is focused on practical training so that even beginners can easily follow along!

💡 By taking this course, you can learn these things!

  • How to Use the YOLO Object Detection Model in Practice

  • Build APIs simply and quickly with FastAPI

  • Implementing real-time data polling with Next.js and TanStack Query

  • A practice-oriented structure that you can follow quickly!

🔥 Make it yourself in just 1 hour and 30 minutes! 🔥

🔥 What makes this course different & key features

Short and practical lectures – These are lectures where you can learn right away through practice , without lengthy theoretical explanations.
Real-world projects using the latest stack – You can learn technologies applicable to real-world services using Next.js, YOLO, FastAPI, React, etc.
Get started right away, no setup required! – Don't waste time on configuration and complex concepts; quickly learn the basics and start practicing with code .
Just what you need! – Rather than an in-depth AI course, this course is designed to help web developers easily utilize YOLO and FastAPI .
No full-stack experience required! – Both front-end and back-end developers can easily follow along and experience AI-based projects.

🚀 Experience building a real-world AI-based fire detection system in a short period of time! 🚀

🎯 Who needs this course?

Anyone who wants to create a simple AI project using YOLO and FastAPI
Anyone who wants to learn real-time data integration using Next.js and TanStack Query
If you want to build an AI-based object detection system, but find the lectures too heavy, it will be burdensome.
Those who want to experience simple and lightweight AI + web projects that can be used in actual services
Front-end developers who want to experience projects utilizing back-end and AI models without any burden

🚀 This course isn't about complex AI theory. It's about creating short, easy-to-follow projects that can be applied immediately in real-world situations! 🚀

Learn about these things.

🚀 Fire Detection AI Model Using YOLO

🔥 Learn how to detect fire in images using the YOLO (You Only Look Once) model.
🔥 We also cover how to use pre-trained models and how to train your own models .

🚀 Build a backend API with FastAPI

🛠 Learn how to build a simple API server using FastAPI .
🛠 Let's build a backend that handles data requests and connects them to the YOLO model to return the detected data .

🚀 Real-time data integration with Next.js & TanStack Query

💡 Learn how to periodically request data (polling) using Next.js and TanStack Query .
💡 Implement a web dashboard that displays real-time detection logs on the front end .

🚀 Storing detection logs using SQLite

📂 Store detected fire data in SQLite and create an API to retrieve it .
📂 Learn how to manage data through simple CRUD APIs.

🚀 Implementing an alert system (audio & alarm messages)

🔊 Implement an audio alarm to sound when real-time detection occurs.
🔊 Learn how to get instant notifications on the web .

Things to note before taking the course

Notes before taking the course

🛠 Practice environment

  • The lecture is conducted in a Conda environment , so you can set up the Conda environment without having to install Python separately.

  • You can practice on both Windows and MacOS .

  • The development environment is carried out using the Cursor AI editor.

📌 Required installation programs

  • Conda (for managing Python virtual environments)

  • Node.js 22 or higher (for running Next.js)

  • Cursor AI (for writing and running code)

  • SQLite (for data storage, built-in DB, no separate installation required)

💡 The required environment settings will be explained in detail in the lecture, so please follow along without worry!

Learning Materials

  • The basic project is provided with the lecture and shared via GitHub link. You can download the necessary materials and use them for your practice. 😊

📌 Player Knowledge and Precautions

Basic Python Grammar
If you have ever used async/await asynchronous processing, it will be easier to understand!
Basic SQL knowledge (understanding basic CRUD operations such as SELECT and INSERT in a database)
Basic experience using Next.js and React (even complete beginners can follow along, but it will be easier if you know the basic concepts.)

💡 I'll explain it so you can follow along even if you lack the basics, but if you know the concepts above, you'll understand it even faster! 🚀

Recommended for
these people

Who is this course right for?

  • AI-based fire detection system DIYers

  • For those who want hands-on projects with YOLOv11 and FastAPI.

  • Those interested in front-end development using Next.js and TanStack Query

  • Individuals interested in full-stack projects integrating backend and frontend.

  • Those wishing to learn real-time data processing and alert system implementation.

Need to know before starting?

  • Basic Python and JavaScript (or TypeScript) syntax

  • Basic React or Next.js experience

  • REST API & HTTP Request/Response Basics

Hello
This is

631

Learners

30

Reviews

8

Answers

3.8

Rating

9

Courses

Hello, I am the CEO of Ludge Co., Ltd.


I have carried out projects across various sectors, including startups, the financial industry, and public institutions, and

I have gained experience not only in development but also in directly operating services.

Through these experiences, I have developed the ability to solve problems and complete projects by collaborating with team members and freelancers. In particular, going beyond the role of a simple developer, I have...

In this process, I have cultivated the ability to solve problems and complete projects by collaborating with team members and freelancers.


In particular, I believe I can be of even greater help to those who have a dream of running their own service, going beyond just the role of a developer.

I look forward to growing together as we experience the joy of completion and a sense of accomplishment. Thank you.

Curriculum

All

15 lectures ∙ (1hr 10min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

6 reviews

3.8

6 reviews

  • wezon0552님의 프로필 이미지
    wezon0552

    Reviews 2

    Average Rating 5.0

    5

    60% enrolled

    Good, very clean.

    • emfpdlzj님의 프로필 이미지
      emfpdlzj

      Reviews 6

      Average Rating 5.0

      5

      100% enrolled

      I was able to learn YOLO, FAST API, Node.js, and React all in one course, so it was exactly what I needed. However, there was one piece of code that didn't work on Mac!!..

      • fromnow님의 프로필 이미지
        fromnow

        Reviews 2

        Average Rating 5.0

        5

        33% enrolled

        I wanted to see YOLOv11. It's very good to be able to watch the installation and operation process through video. I recommend this course.

        • fairyfloss09091491님의 프로필 이미지
          fairyfloss09091491

          Reviews 1

          Average Rating 5.0

          5

          100% enrolled

          It's not too deep, but I like that it's short and neat. It was fun to listen to casually 😊😊

          • ludgi
            Instructor

            Thank you. I'll prepare another fun lecture next time! 😊

        • tae0x님의 프로필 이미지
          tae0x

          Reviews 16

          Average Rating 4.1

          1

          100% enrolled

          It's difficult to follow without basic prerequisite knowledge As you can see from the lecture duration, it's generally targeted at those who already know how to do it

          $8.80

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