Microbolometer Market Size

Global Microbolometer Market size was valued at USD 415.01 Million in 2023 and is poised to grow from USD 445.16 Million in 2024 to USD 757.20 Million by 2032, growing at a CAGR of 7.3% in the forecast period (2025-2032).

The global microbolometer market growth is driven by the increasing demand for advanced thermal imaging, thermometry, and fever detection systems in a variety of industries. The principal reason is the augmented application of infrared cameras in observation systems, particularly industrial security and intelligent cities. The city of Chicago, for instance, used vanadium oxide (VOx)-based thermal imaging cameras on its public transportation system in 2024 for real-time heat signature monitoring for infrastructure diagnosis, security, and anti-vandalism.

In addition, the defense and aerospace industries continue to invest in high-performance thermal systems for night vision and target acquisition. Due to their portability and ease of application in field inspections and maintenance of equipment, small thermal scanners are also increasingly in demand. Amorphous silicon (a-Si) and vanadium oxide (VOx) remain the most widely used materials in the fabrication of microbolometers; a-Si provides a lower-cost option, whereas VOx is used for high-end applications because of its excellent sensitivity.

What Advantages Do AI-Driven Microbolometers Offer Across Industries?

The application of AI is increasingly becoming more innovative to improve the abilities of thermal imaging systems based on microbolometers. Equipment is now able to conduct real-time analysis, pattern detection, and predictive diagnosis with the integration of AI algorithms and temperature sensors. This facilitates wiser, quicker, and automated decision-making.

AI-driven microbolometer cameras, for instance, were installed in public buildings as part of a major European smart city initiative in 2025. The cameras could detect anomalies and manage crowds by monitoring behavioral patterns alongside detecting heat patterns.

AI-driven thermal imaging is applied in companies for predictive maintenance, which minimizes downtime and enhances safety by detecting overheated equipment prior to failure. In addition, AI enhances the performance of surveillance systems and thermal scopes by providing more precise object classification and tracking in military uses. Therefore, AI is not only making microbolometers better but also widening the scope of uses for them, so that thermal imaging becomes more intelligent, efficient, and industry independent.