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Web Development

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.

(5.0) 2 reviews

81 learners

  • ludgi
토이프로젝트
객체인식
3시간 만에 완강할 수 있는 강의 ⏰
Next.js
yolo
Python
FastAPI
React

What you will learn!

  • 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

443

Learners

17

Reviews

8

Answers

4.2

Rating

7

Courses

안녕하세요, 주식회사 럿지의 대표입니다.


저는 스타트업, 금융권, 공공기관 등 다양한 분야에서 프로젝트를 진행하며,

개발뿐만 아니라 서비스를 직접 운영하는 경험을 쌓아왔습니다.

 

이 과정에서 팀원 및 프리랜서들과 협업하며 문제를 해결하고 프로젝트를 완성하는 능력을 길렀습니다.


특히, 단순히 개발자로서의 역할을 넘어서 자신의 서비스를 운영하고자 하는 꿈을 가진 분들께 더 많은 도움을 드릴 수 있다고 생각합니다.

 

완성의 즐거움과 성취감을 함께 경험하며 성장해 나가길 기대합니다. 감사합니다.

Curriculum

All

15 lectures ∙ (1hr 10min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

2 reviews

5.0

2 reviews

  • fairy floss님의 프로필 이미지
    fairy floss

    Reviews 1

    Average Rating 5.0

    5

    100% enrolled

    깊진 않지만 짧고 깔끔해서 좋네요 가볍게 듣기 재밌었어요 ㅎㅎ

    • ludgi
      Instructor

      감사합니다. 다음에도 재밌는 강의 준비하겠습니다.!😊

  • nowfire님의 프로필 이미지
    nowfire

    Reviews 1

    Average Rating 5.0

    5

    33% enrolled

    YOLOv11 을 보고 싶었어요. 설치 및 운용 과정을 영상으로 볼 수 있어서 매우 좋습니다. 강의 추천합니다.

    $8.80

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