Smoking Detection System

1. Background

In construction sites and mining areas, fire safety is always the top priority. Many materials stored on site—such as insulation and flammable goods—can easily ignite from a single cigarette, leading to devastating loss of life and property.

Although smoking is strictly prohibited in these environments, some workers still take chances and hide from manual inspections. Manual monitoring by security personnel is limited and cannot cover all areas 24/7. Therefore, an automated, intelligent image recognition system is essential to detect smoking behaviors in real time and ensure site safety.

2. Product Overview and Workflow

2.1 Product Overview

FuweeVision’s AI Smoking Detection System is an intelligent video analytics solution based on deep learning and big data technology. It replaces manual supervision with automated image recognition to detect unsafe behaviors in real time.

The system uses existing on-site cameras—no additional hardware required—and can issue immediate alerts both at the control room and at local points when a violation occurs. It provides a fast, reliable, and cost-effective solution for safety management.

2.2 Workflow

1. Front-end cameras stream real-time video to the system server.

2. The AI detection module continuously analyzes the video stream.

3. When smoking behavior is detected, the system automatically captures evidence, stores snapshots, and triggers alerts at the control room or on-site alarm devices.

3. System Features and Technical Parameters

3.1 Smoking Detection

• Automatically detects smoking behavior by recognizing both hand gestures and cigarette smoke near the mouth.

• Detects violations even when workers partially turn away from the camera.

• Works in various lighting and weather conditions.

• Custom detection zones can be defined for precise monitoring.

• Recognition accuracy: >95%.

3.2 Alert Function

• When smoking or other unsafe behaviors are detected, the system can trigger real-time audio or visual alerts at monitoring centers or directly at the worksite (via IP speaker or light signal).

• Supports event snapshots and alarm logs for later review.

3.3 Technical Specifications

• Supports RTSP video stream input (Hikvision, Dahua, Uniview, and other major brands).

• Compatible with both live video and still image analysis.

• Fully automatic operation—no manual intervention required.

• Detection frequency adjustable based on server performance.

• Processing capacity: 4–50 channels per server depending on hardware specs.

• Recognition accuracy: ≥95%.

4. Hardware and Operating Environment

5. Application Scenarios

FuweeVision’s Smoking Detection and Safety Management System is widely used in:

• Construction sites – buildings, subways, bridges

• Mines – coal, iron, non-ferrous metals

• Industrial plants – steel, aluminum, power generation

• Warehouses & logistics centers

• Public facilities – airports, stations, tunnels

The solution can also be integrated with Fire & Smoke Detection, Hard Hat Detection, and Unauthorized Access Detection for complete site safety coverage.

6. Project References

FuweeVision systems have been successfully deployed in multiple large-scale safety monitoring projects, including:

• Shenzhen Metro Line 14 Construction Project

• Beijing Anzhen Oriental Hospital Smart Construction Site

• Xi’an International Football Center Project

• Yantai Penglai International Airport Phase II

• Alibaba DAMO Academy Safety Management Project

• Xuchang Sports & Exhibition Center Phase I

• Hangzhou Railway Engineering Project

• China Railway Construction South Division (Wanqingsha Phase II)

• Xinjiang Agricultural Resources Video Upgrading Project

• Xiaoshan Airport Expansion

• Hubei Yangtze Power Smart Safety Management System

• Daqing Drilling Platform Safety Monitoring Project

• Zhuhai Zhonghai Times Huanyu Project

• Dayuan Business Core F6 Project

• Tangshan High-Tech Zone Safety Monitoring Project

7. Advantages

• Real-time AI recognition — no manual supervision required

• High accuracy with deep learning models

• Supports existing cameras — no additional hardware cost

• Local or remote alarm options

• 24/7 automatic operation with CPU-only processing

• Easy to install, maintain, and scale

• Integrates with fire, PPE, and intrusion detection modules

8. Related Products

• Hard Hat Detection

• Fire & Smoke Detection

• Unauthorized Access Detection

• Phone Usage Detection

• High-Altitude Work Safety Monitoring