Night Vision (IR) Surveillance Cameras Market Size Report 2025

On Oct 14, Global Info Research released "Global Night Vision (IR) Surveillance Cameras Market 2025 by Manufacturers, Regions, Type and Application, Forecast to 2031". This report includes an overview of the development of the Night Vision (IR) Surveillance Cameras industry chain, the market status of Night Vision (IR) Surveillance Cameras Market, and key enterprises in developed and developing market, and analysed the cutting-edge technology, patent, hot applications and market trends of Night Vision (IR) Surveillance Cameras.

The global Night Vision (IR) Surveillance Cameras market size is expected to reach $ 35228 million by 2031, rising at a market growth of 13.2% CAGR during the forecast period (2025-2031).
In this report, we will assess the current U.S. tariff framework alongside international policy adaptations, analyzing their effects on competitive market structures, regional economic dynamics, and supply chain resilience.
Night vision surveillance cameras, as key devices in the field of security surveillance, are specialized cameras capable of monitoring and recording in low-light or completely dark environments. Their core operating principle involves utilizing special light-sensitive components and imaging technology to overcome light limitations, capturing and reproducing the visual information of target objects.
From a technical perspective, common night vision surveillance cameras are primarily divided into two categories: those based on infrared technology, which are further subdivided into active infrared and passive infrared. Active infrared cameras are equipped with infrared emitters that emit invisible infrared light to illuminate the shooting area, which is then captured by an image sensor to form an image. These cameras are widely used in civilian security and small commercial surveillance applications, providing clear nighttime surveillance footage at a relatively low cost. Passive infrared cameras primarily rely on detecting the infrared radiation emitted by objects themselves to form images, without requiring additional infrared light sources. They are commonly used in scenarios with extremely high requirements for concealment, such as military reconnaissance and forest fire monitoring. Their imaging is not affected by ambient light and can effectively identify the thermal characteristics of target objects.
Another type is the low-light night vision camera, which employs image enhancement technology to amplify weak light sources and achieve nighttime imaging. They can capture extremely faint light sources such as starlight or moonlight and convert them into clear, observable images. In scenarios where image quality is critical and the environment is not completely dark—such as nighttime surveillance at large transportation hubs like ports or airports—these cameras play a crucial role, providing detailed and realistic image information.
Market Drivers
Growing demand for security: Globally, whether in urban or rural areas, the importance of security is becoming increasingly apparent as population mobility increases and socio-economic activities become more frequent. Commercial and residential areas in cities need to ensure the safety of property and people at night. Installing night vision surveillance cameras can effectively deter criminal activity and provide crucial video evidence in the event of an incident. For example, in older neighborhoods with high rates of theft, the installation of night vision surveillance cameras has led to a significant decrease in crime rates and provided clear leads for police investigations, aiding in the swift apprehension of criminals. In rural areas, as agricultural modernization progresses, there is an increasing demand for nighttime security surveillance in farms and livestock facilities to prevent theft of livestock and damage to crops.
Advancing smart city construction: Smart city construction is being vigorously promoted in major cities around the world, with intelligent security being an important component. Night vision surveillance cameras, as the basic equipment for nighttime surveillance, are widely deployed in various corners of the city, including roads, bridges, public squares, and parks. By establishing a large-scale night vision surveillance network, city managers can monitor real-time nighttime activities, manage traffic flow, respond swiftly to emergencies, and ensure public safety. For example, in intelligent transportation systems, night vision surveillance cameras can identify vehicle trajectories and license plate numbers at night, assisting traffic authorities in optimizing traffic flow, handling accidents and violations, and enhancing the intelligence of urban transportation management.
Expansion into emerging application scenarios: Beyond traditional security applications, night vision surveillance cameras are increasingly being adopted in emerging fields. In the automotive sector, as autonomous driving technology advances, night vision surveillance cameras have become a critical sensor for driver-assistance systems. They can detect pedestrians, animals, and obstacles on the road in advance under nighttime or adverse weather conditions, providing the autonomous driving system with more comprehensive environmental information to enhance driving safety. For example, some high-end automotive brands have already made night vision surveillance cameras standard or optional equipment. When vehicles are traveling on dimly lit rural roads or sections without streetlights, the night vision system can promptly detect potential hazards, provide warnings to drivers, and prevent collisions. In the field of drones, night vision surveillance cameras enable drones to operate at night, making them suitable for tasks such as nighttime inspections, surveying, and rescue operations. In power line inspections, drones equipped with night vision surveillance cameras can inspect transmission lines at night, promptly identifying issues such as line faults or equipment overheating, thereby improving inspection efficiency and accuracy and reducing economic losses caused by power outages.
Intelligent Upgrades
AI Intelligent Recognition Technology Integration: Artificial intelligence (AI) technology will be deeply integrated into night vision surveillance cameras, enabling more powerful intelligent recognition capabilities. Through AI algorithms, cameras can accurately identify targets such as pedestrians, vehicles, and animals in complex nighttime environments and analyze and warn of their behavior. For example, when detecting abnormal wandering, running, or unauthorized entry into restricted areas at night, the cameras can immediately issue an alarm to notify relevant personnel, significantly improving monitoring efficiency and accuracy. In parking lot management, AI-enabled night vision surveillance cameras can automatically recognize vehicle license plate numbers and vehicle types, record entry and exit times, and implement automated parking fee management, enhancing the operational efficiency of parking lots.
Enhanced edge computing capabilities: To reduce data transmission pressure and latency while improving real-time processing capabilities, night vision surveillance cameras will continue to enhance their edge computing capabilities. Cameras with robust edge computing capabilities can perform real-time analysis and processing of collected video data locally, transmitting only critical alarm information and important video clips to backend servers. This reduces network bandwidth requirements and ensures the stability of the surveillance system. For example, in industrial production scenarios, night vision surveillance cameras can monitor the operational status of equipment on production lines in real time at the edge. By analyzing data such as equipment temperature and vibration through edge computing, they can promptly identify potential equipment failures and issue local alerts, preventing fault escalation caused by data transmission delays. This enhances production continuity and safety.
This report studies the global Night Vision (IR) Surveillance Cameras production, demand, key manufacturers, and key regions.
This report is a detailed and comprehensive analysis of the world market for Night Vision (IR) Surveillance Cameras and provides market size (US$ million) and Year-over-Year (YoY) Growth, considering 2024 as the base year. This report explores demand trends and competition, as well as details the characteristics of Night Vision (IR) Surveillance Cameras that contribute to its increasing demand across many markets.

Sample Report Request Night Vision (IR) Surveillance Cameras
https://www.globalinforesearch.com/reports/2944813/night-vision--ir--surveillance-cameras

Market segment by Type: IP Cameras、 Analog Cameras、 Others
Market segment by Application: Government & Utilities、 Transportation、 Commercial & Retail、 Office Building、 Campus & Stadiums、 Others
Major players covered:  Hikvision Digital Technology、 Dahua Technology、 Axis Communications、 Hanwha (Samsung)、 Bosch、 Schneider Electric (Pelco)、 Avigilon、 Panasonic、 Flir Systems、 Tiandy Technologies、 Sony、 Infinova Group、 Honeywell、 Joyware、 HanBang
Market segment by region, regional analysis covers: North America (United States, Canada and Mexico), Europe (Germany, France, United Kingdom, Russia, Italy, and Rest of Europe), Asia-Pacific (China, Japan, Korea, India, Southeast Asia, and Australia),South America (Brazil, Argentina, Colombia, and Rest of South America),Middle East & Africa (Saudi Arabia, UAE, Egypt, South Africa, and Rest of Middle East & Africa).

The content of the study subjects, includes a total of 15 chapters:
Chapter 1, to describe Night Vision (IR) Surveillance Cameras product scope, market overview, market estimation caveats and base year.
Chapter 2, to profile the top manufacturers of Night Vision (IR) Surveillance Cameras, with price, sales, revenue and global market share of Night Vision (IR) Surveillance Cameras from 2020 to 2025.
Chapter 3, the Night Vision (IR) Surveillance Cameras competitive situation, sales quantity, revenue and global market share of top manufacturers are analyzed emphatically by landscape contrast.
Chapter 4, the Night Vision (IR) Surveillance Cameras breakdown data are shown at the regional level, to show the sales quantity, consumption value and growth by regions, from 2020 to 2031.
Chapter 5 and 6, to segment the sales by Type and application, with sales market share and growth rate by type, application, from 2020 to 2031.
Chapter 7, 8, 9, 10 and 11, to break the sales data at the country level, with sales quantity, consumption value and market share for key countries in the world, from 2020 to 2024.and Night Vision (IR) Surveillance Cameras market forecast, by regions, type and application, with sales and revenue, from 2025 to 2031.
Chapter 12, market dynamics, drivers, restraints, trends and Porters Five Forces analysis.
Chapter 13, the key raw materials and key suppliers, and industry chain of Night Vision (IR) Surveillance Cameras.
Chapter 14 and 15, to describe Night Vision (IR) Surveillance Cameras sales channel, distributors, customers, research findings and conclusion.

Data Sources:
Via authorized organizations:customs statistics, industrial associations, relevant international societies, and academic publications etc.
Via trusted Internet sources.Such as industry news, publications on this industry, annual reports of public companies, Bloomberg Business, Wind Info, Hoovers, Factiva (Dow Jones & Company), Trading Economics, News Network, Statista, Federal Reserve Economic Data, BIS Statistics, ICIS, Companies House Documentsm, investor presentations, SEC filings of companies, etc.
Via interviews. Our interviewees includes manufacturers, related companies, industry experts, distributors, business (sales) staff, directors, CEO, marketing executives, executives from related industries/organizations, customers and raw material suppliers to obtain the latest information on the primary market;
Via data exchange. We have been consulting in this industry for 16 years and have collaborations with the players in this field. Thus, we get access to (part of) their unpublished data, by exchanging with them the data we have.

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