The AI-Based Fever Detection Camera Market Size is valued at USD 1.55 billion in 2023 and is predicted to reach USD 2.92 billion by the year 2031 at an 8.39% CAGR during the forecast period for 2024-2031.
Artificial intelligence (AI) powered cameras for detecting fevers are highly valuable instruments for improving public health and safety, particularly during periods of infectious disease outbreaks. By integrating thermal imaging with sophisticated artificial intelligence, these devices offer rapid, precise, and non-intrusive fever screening, aiding in the detection and isolation of potentially infectious persons prior to the transmission of sickness. The main objective of this system is to detect people who could be displaying symptoms of fever.
Due to the COVID-19 pandemic and the increasing awareness of the necessity of controlling infectious diseases, there has been a considerable rise in the demand for non-contact temperature screening in public areas, companies, and transit centres. AI-enabled thermal imaging cameras provide a dependable and effective solution for this requirement. The continuous progress in AI technology, enhancing the precision and efficiency of temperature measurements, continues to propel the market.
Nevertheless, the substantial upfront expenses linked to the implementation of AI-powered fever detection camera systems provide a noteworthy obstacle. The expenses encompass the expenditures for cameras, advanced software, installation, and routine maintenance. The cost burden associated with implementing these systems can be significant, posing challenges for small and medium-sized companies (SMEs) and organizations with restricted resources. Furthermore, the apprehensions regarding privacy and data security, considering the fact that these cameras handle delicate health information and the possibility of inaccurate results owing to external environmental variables, continue to impede the broad acceptance of these cameras.
The AI-Based Fever Detection Camera market is segmented on the basis of Type and End-user. Based on type, the market is segmented into Turret/Bullet Cameras and Handheld Cameras. By End-user, the market is segmented into Airports, Hospitals, Public Places, Enterprises/Factories, Banks, and Others (Schools, Residential Buildings, etc.).
The Turret/Bullet Cameras category is expected to hold a major share in the global AI-Based Fever Detection Camera market in 2023. It is predicted that the turret and bullet camera sectors have the highest market since these cameras eliminate the danger and expense associated with hiring staff members to use handheld equipment at entrances in order to assess individual temperatures. Most of the time, these cameras are installed in locations such as building entrances, airports, industries, and commercial facilities. They are often fixed on the wall. These cameras have a range of 8 to 30 feet, allowing them to scan.
The Public Places segment is predicted to grow rapidly in the global AI-Based Fever Detection Camera market. AI-powered thermal imaging cameras are mostly used in densely populated areas to detect individuals with elevated body temperatures. These cameras have the ability to scan anybody who enters, regardless of whether they are wearing a mask or not. These gadgets enhance the efficiency of operations at facilities and also alert the authorities in the event of detecting individuals with elevated body temperatures. They assist in segregating the individual from the masses. These cameras are anticipated to assist organizations, such as grocery shops and enterprises, in carrying out their important operations with less danger.
As the largest region, North America dominated the AI-based fever detection camera market, primarily due to numerous significant factors. The region's sophisticated healthcare infrastructure, robust health and safety standards, and pervasive use of cutting-edge technology significantly influence market growth. The market in North America is further fortified by substantial investments in public health and safety measures and the presence of prominent industry leaders. On the other hand, the Asia-Pacific region is anticipated to experience the most significant growth rate during the projection period. The burgeoning awareness of public health, the escalating government initiatives to improve healthcare systems, and the increasing demand for advanced surveillance technology in densely populated countries may all be contributing factors to the exponential expansion. Additionally, the numerous smart city initiatives and the substantial investments in technological advancements have a significant influence. Furthermore, the region's prior experiences with pandemics have heightened the importance of establishing robust health surveillance systems, thereby accelerating the adoption of fever detection cameras that employ artificial intelligence.
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Report Attribute |
Specifications |
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Market Size Value In 2023 |
USD 1.55 Bn |
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Revenue Forecast In 2031 |
USD 2.92 Bn |
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Growth Rate CAGR |
CAGR of 8.39% from 2024 to 2031 |
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Quantitative Units |
Representation of revenue in US$ Bn and CAGR from 2024 to 2031 |
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Historic Year |
2019 to 2023 |
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Forecast Year |
2024-2031 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Type And End-User |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; Southeast Asia; South Korea |
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Competitive Landscape |
Altoros, AnyConnect Private Limited, Athena Security, Inc., Australia PTY LTD., FLIR Systems, Inc., Hangzhou Hikvision Digital Technology Co., Ltd., Honeywell International Inc., Johnson Controls, Kogniz, Inc., Mantra Softech, Nippon Avionics Co., Ltd., Platinum CCTV, Scylla, and Vantage Security. |
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Customization Scope |
Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global AI-Based Fever Detection Camera Market Snapshot
Chapter 4. Global AI-Based Fever Detection Camera Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: By Type Estimates & Trend Analysis
5.1. By Type & Market Share, 2023 & 2031
5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following By Type:
5.2.1. Turret/Bullet Cameras
5.2.2. Handheld Cameras
Chapter 6. Market Segmentation 2: By End Users Estimates & Trend Analysis
6.1. By End Users & Market Share, 2023 & 2031
6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following By End Users:
6.2.1. Airports
6.2.2. Hospitals
6.2.3. Public Places
6.2.4. Enterprises/Factories
6.2.5. Banks
6.2.6. Others (Schools, Residential Buildings, etc.)
Chapter 7. AI-Based Fever Detection Camera Market Segmentation 3: Regional Estimates & Trend Analysis
7.1. North America
7.1.1. North America AI-Based Fever Detection Camera Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
7.1.2. North America AI-Based Fever Detection Camera Market Revenue (US$ Million) Estimates and Forecasts by End Users, 2024-2031
7.1.3. North America AI-Based Fever Detection Camera Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
7.2. Europe
7.2.1. Europe AI-Based Fever Detection Camera Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
7.2.2. Europe AI-Based Fever Detection Camera Market Revenue (US$ Million) Estimates and Forecasts by End Users, 2024-2031
7.2.3. Europe AI-Based Fever Detection Camera Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
7.3. Asia Pacific
7.3.1. Asia Pacific AI-Based Fever Detection Camera Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
7.3.2. Asia Pacific AI-Based Fever Detection Camera Market Revenue (US$ Million) Estimates and Forecasts by End Users, 2024-2031
7.3.3. Asia Pacific AI-Based Fever Detection Camera Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
7.4. Latin America
7.4.1. Asia Pacific AI-Based Fever Detection Camera Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
7.4.2. Latin America AI-Based Fever Detection Camera Market Revenue (US$ Million) Estimates and Forecasts by End Users, 2024-2031
7.4.3. Latin America AI-Based Fever Detection Camera Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
7.5. Middle East & Africa
7.5.1. Middle East & Africa AI-Based Fever Detection Camera Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
7.5.2. Middle East & Africa AI-Based Fever Detection Camera Market Revenue (US$ Million) Estimates and Forecasts by End Users, 2024-2031
7.5.3. Middle East & Africa AI-Based Fever Detection Camera Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
Chapter 8. Competitive Landscape
8.1. Major Mergers and Acquisitions/Strategic Alliances
8.2. Company Profiles
8.2.1. Altoros (California, United States)
8.2.2. AnyConnect Private Limited (Singapore)
8.2.3. Athena Security, Inc. (Austin, United States)
8.2.4. Australia PTY LTD. (Australia)
8.2.5. FLIR Systems, Inc. (Oregon, United States)
8.2.6. Hangzhou Hikvision Digital Technology Co., Ltd. (Hangzhou, China)
8.2.7. Honeywell International Inc. (North Carolina, United States)
8.2.8. Johnson Controls (Cork, Ireland)
8.2.9. Kogniz, Inc. (California, United States)
8.2.10. Mantra Softech (India) Pvt. Ltd. (India)
8.2.11. Nippon Avionics Co., Ltd. (Osaka, Japan)
8.2.12. Platinum CCTV (United States)
8.2.13. Scylla (California, United States)
8.2.14. Vantage Security (West Midlands, United Kingdom)
8.2.15. Other Prominent Players
AI-Based Fever Detection Camera Market By Type-
AI-Based Fever Detection Camera Market By End-user-
AI-Based Fever Detection Camera Market By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
