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安全/防犯罪消防

市場調查報告書

商品編碼

2148215

人工智慧資料中心火災偵測和滅火系統的市場規模、佔有率和成長預測（2026-2032 年）

AI Data Center Fire Detection and Suppression Systems Market Size, Share & Growth Forecast (2026-2032)

出版日期: 2026年09月24日 | 出版商:

Knowledge Sourcing Intelligence | 英文 152 Pages | 商品交期: 最快1-2個工作天內

價格

簡介目錄

2026年，人工智慧驅動的資料中心火災偵測和抑制系統的市場規模估計為11億美元，預計到2032年將達到28.4億美元。這意味著在預測期內，複合年成長率將達到17.1%。

傳統的資料中心消防措施長期以來採用在整棟建築內安裝噴灌系統，並在關鍵機房內配備專用探測和滅火系統的方法。人工智慧基礎設施的普及進一步提升了這種多層防護方法的價值。現代資料中心的電力消耗量更高，佈線密度更大，每平方公尺的高價值設備密度也更高。此外，在氣流強勁的區域，粒狀物會被迅速稀釋並帶入回風通道，使得傳統的吸頂式煙霧偵測器難以偵測到煙霧。吸入式煙霧偵測系統透過管道網路主動採樣空氣來解決這個問題。這使得警報能夠比典型的被動式偵測更早觸發。防護架構因機房和危險因子而異。資料機房和伺服器機房通常會將超早期警報偵測系統與瓦斯滅火系統、預作用式噴灌或水霧滅火系統結合。電氣機房、不斷電系統(UPS) 機房和電池機房需要特別關注，因為電弧放電、電纜絕緣故障、電力電子設備問題或鋰離子電池熱失控都可能導致故障。監測電池氣體釋放情況有助於在出現可見煙霧或明火之前識別異常電池行為。這使得操作人員能夠在全面熱事故之前隔離設備、調整通風或啟動預防性控制措施。在發電機和變壓器安裝區域，根據燃料和油品帶來的危險，可能需要火焰偵測系統和水基滅火系統。滅火劑的選擇正變得越來越重要。當無殘留滅火和快速恢復運作至關重要時，氣體滅火系統仍然是一個有吸引力的選擇。負責人越來越重視滅火劑的環境影響、供應連續性、安裝空間需求和補給物流。 3M公司停止生產PFAS後，促使人們重新評估先前與FK-5-1-12供應相關的系統。惰性氣體、替代鹵代烴滅火劑和水霧技術在安裝空間、環境影響、釋放性能和對設備的影響方面提供了不同的組合。因此，大規模業者正在從在整個園區採用單一滅火技術轉向逐個房間採取保護策略。

市場促進因素

隨著資產集中度的提高，早期回應的價值也隨之增加。在人工智慧設施中，昂貴的加速器、網路設備和記憶體都集中在高密度機架式系統中。這意味著即使是局部火災也會造成更大的經濟損失。國際能源總署 (IEA) 報告稱，人工智慧專用資料中心的電力消耗量預計將在 2025 年成長 50%，並在 2025 年至 2030 年間成長兩倍。消防系統的收入成長並非與電力消耗量成長成正比。即使容量擴張幅度相同，需要保護的閒置頻段也會增加。避免長時間停機的重要性也促使人們需要提高設施最關鍵部分的防護等級。
鋰離子UPS和電池儲能系統（BESS）的部署帶來了獨特的預防性要求。在人工智慧資料中心，隨著鋰離子UPS平台和大規模電池能源儲存系統被廣泛應用於備用電源、負載平滑和電網連接，電池系統的重要性日益凸顯。國際能源總署（IEA）的分析顯示，到2030年，全球資料中心的電池儲能容量預計將達到20-25吉瓦。電池熱失控與典型的電氣火災有所不同，因為電池單元在點火前可能會釋放可燃性氣體，或者熱量可能在模組間傳播。這促使人們對廢氣檢測、熱監測、隔室隔離、滅火控制以及符合能源儲存系統防火測試和安裝要求的防護策略提出了更高的要求。
在氣流強勁的資料中心機房中，吸入式煙霧偵測系統的部署顯得格外重要。在人工智慧資料中心機房中，儘管液冷散熱能力有所提升，但空氣流動量仍然非常大。當煙霧被強勁氣流或封閉系統稀釋或改變時，傳統點式偵測器的效能可能會降低。西門子指出，吸入式煙霧偵測對於資料中心早期可靠警報至關重要。霍尼韋爾的VESDA平台基於連續空氣採樣技術，專為運作關鍵環境而設計。隨著設施規模的擴大和氣流模式的日益複雜，業主們擴大部署具有多採樣區域、回風監測以及機櫃和配電室局部檢測功能的系統，以縮短從火災發生到操作員響應的時間。
環境和供應鏈的變化正在重新定義滅火劑的選擇標準。滅火系統的產品系列正在經歷一場變革，而不僅僅是規模的擴大。 3M公司已於2025年底停止生產全氟烷基和多氟烷基物質（PFAS）。這迫使營運商和系統設計人員更加認真地考慮未來清潔滅火劑的供應、替代策略以及監管方向。惰性氣體系統、水霧滅火系統和替代化學滅火劑在安裝面積、噴射量和使用壽命方面各有不同。即使受保護的資料中心空間沒有擴大，這也催生了對現有系統進行維修和重新設計的需求。對於尋求可在多個司法管轄區運行的標準化系統的全球營運商而言，這是一個特別重要的挑戰。

市場限制因素

消防措施仍然高度依賴當地法律法規、保險公司要求、主管機關的解釋以及設施的具體風險接受度。這限制了全球園區間標準化的可能性。全區域氣體滅火系統需要良好的外殼氣密性和足夠的儲存空間。水基滅火系統可能會引發對電子設備損壞和火災後恢復的擔憂。電池保護在技術上仍然具有挑戰性，因為滅火可能無法立即阻止電池級熱失控。營運商也面臨滅火劑發展趨勢的變化，這會使長期服務規劃變得複雜。這些因素需要多層次的解決方案，但同時，設計、認證和試運行也比簡單的每兆瓦一個單元的模式要複雜得多。

促進因素
- 資產集中度增加和停機成本上升
- 鋰離子UPS和BESS的擴展
- 高氣流檢測的要求
- 滅火劑與向永續性的過渡
抑制因子
- 區域建築規範及主管機關之間的差異
- 消防劑供應和監管方面的不確定性
- 電池熱失控的複雜性
- 對現有設備進行改造以及對機殼的限制

第11章競爭格局

價值鏈
偵測預警平台
氣體滅火及清潔劑滅火
水霧系統與預作用系統
為資料中心提供一體化消防系統解決方案。
生命週期服務和遠端監控

第12章：公司簡介

Johnson Controls
Siemens
Honeywell
Minimax
Fike
Kidde Global Solutions
Viking Group
ORR Protection
Marioff
Securiton
Bosch Building Technologies
Hochiki
Nohmi Bosai
Halma/Apollo Fire Detectors
WAGNER Group
Fireaway/Stat-X
Firetrace International
Rotarex Firetec

第13章近期趨勢

第14章附錄

簡介目錄

Product Code: KSI-009261

The AI Data Center Fire detection and Suppression Systems Market is estimated at USD 1.10 billion in 2026 and is projected to reach USD 2.84 billion by 2032, representing a CAGR of 17.1% during the forecast period.

Conventional data-center fire protection has long combined building-wide sprinklers with specialized detection and suppression for critical rooms. AI infrastructure increases the value of that layered approach. Modern facilities contain more electrical power, denser cabling and a larger concentration of high-value equipment per square metre. High airflow can also make smoke harder to detect at conventional ceiling locations because particles are rapidly diluted and carried toward return-air paths. Aspirating Smoke Detection addresses this problem by actively sampling air through a pipe network. It can provide warning at a much earlier stage than ordinary passive detection. The protection architecture differs by room and hazard. Data halls and server rooms commonly combine very-early-warning detection with gaseous suppression, pre-action sprinklers or water mist. Electrical rooms, uninterruptible power supply rooms and battery spaces require additional attention because faults may involve arcing, cable insulation, power electronics or lithium-ion thermal runaway. Battery off-gas monitoring can identify abnormal cell behaviour before visible smoke or open flame. This allows operators to isolate equipment, adjust ventilation or trigger prevention-oriented controls before a full thermal event develops. Generator and transformer areas may require flame detection or water-based systems suited to fuel and oil hazards. Suppression-agent selection is becoming more strategic. Gaseous systems remain attractive where residue-free extinguishment and rapid return to service matter. Operators increasingly evaluate agent environmental profile, supply continuity, enclosure requirements and refilling logistics. 3M's completed PFAS-manufacturing exit has reinforced this reassessment for systems historically associated with FK-5-1-12 supply. Inert gases, alternative halocarbon agents and water-mist technologies provide different combinations of space requirement, environmental profile, discharge performance and equipment impact. Large operators are therefore moving toward room-specific protection strategies rather than one suppression technology across the entire campus.

Market Drivers

Higher asset concentration increases the value of early intervention. AI facilities concentrate expensive accelerators, networking and memory in dense rack-scale systems. This increases the financial consequence of even a localized fire event. The International Energy Agency reports that electricity consumption from AI-focused data centers increased 50% in 2025 and is projected to triple between 2025 and 2030. Fire-system revenue does not rise directly with electricity consumption. The same capacity expansion creates more protected white space, power rooms, battery rooms and ancillary infrastructure. The value of avoiding prolonged outages also supports higher protection intensity in the most critical parts of the facility.
Lithium-ion UPS and BESS deployment creates a separate prevention requirement. Battery systems are becoming more important as AI data centers use lithium-ion UPS platforms and larger battery energy storage systems for backup, load smoothing and grid interaction. IEA analysis indicates that 20 to 25 gigawatts of battery storage could be installed in data centers globally by 2030. Battery thermal runaway behaves differently from ordinary electrical fires because cells can release flammable gases before ignition and may propagate heat between modules. This increases demand for off-gas detection, thermal monitoring, compartmentalization, suppression controls and protection strategies aligned with energy-storage fire testing and installation requirements.
High-airflow data halls strengthen the case for aspirating smoke detection. AI data halls move very large volumes of air even as liquid cooling takes a larger share of heat removal. Traditional point detectors can be less effective where smoke is diluted or redirected by strong airflow and containment systems. Siemens identifies aspirating smoke detection as essential for early and reliable warning in data centers. Honeywell's VESDA platforms are designed around continuous air sampling for business-critical environments. As facilities become larger and airflow patterns more complex, owners increasingly deploy multiple sampling zones, return-air monitoring and localized cabinet or electrical-room detection to reduce the time between incipient combustion and operator response.
Environmental and supply-chain changes are reshaping suppression-agent selection. Fire suppression is entering a portfolio transition rather than a simple volume expansion. 3M completed its exit from PFAS manufacturing at the end of 2025. This forces operators and system designers to consider future clean-agent availability, replacement strategy and regulatory direction more carefully. Inert-gas systems, water mist and alternative chemical agents each have different footprint, discharge and lifecycle implications. This creates retrofit and redesign demand even where the protected data-center space itself has not expanded. It is particularly relevant for global operators seeking standardized systems that remain serviceable across multiple jurisdictions.

Market Restraints

Fire protection remains highly dependent on local code, insurer requirements, Authority Having Jurisdiction interpretation and facility-specific risk tolerance. This limits standardization across global campuses. Total-flooding gaseous systems require suitable enclosure integrity and storage space. Water-based systems can introduce concerns around electronics damage and post-event recovery. Battery protection remains technically difficult because suppression may control flames without immediately stopping cell-level thermal runaway. Operators also face a changing suppression-agent landscape, which can complicate long-term service planning. These factors favor layered solutions but also make design, qualification and commissioning more complex than a simple equipment-per-megawatt relationship.

Technology and Segment Insights

Suppression systems represent the largest revenue pool in 2026. Cylinders, agent storage, piping, valves, sprinkler or water-mist hardware, releasing controls and installation create substantial system value per protected area. Clean-agent and inert-gas systems are particularly important in server, electrical and control rooms where residue and recovery time matter. Pre-action sprinkler systems remain widely used for building-level protection. Water mist provides a lower-water alternative for selected spaces and fire scenarios.
Very-early-warning and battery off-gas detection form the fastest-growing system layer through 2032. Aspirating systems already have an established data-center role. Higher-density AI facilities and battery rooms increase the number of protected zones and the value of pre-ignition information. Battery off-gas sensing remains smaller in 2026 but can grow rapidly as lithium-ion UPS and facility-level storage become more common. Integrated fire-control platforms increasingly combine detection, suppression release, alarms, shutdown sequences and remote monitoring into one operational layer.
Clean-agent and inert-gas suppression form the largest high-value suppression category with strong growth. Their primary AI data center application is server rooms, electrical rooms and control spaces. Pre-action sprinkler systems form a large installed base with steady growth. Their primary application is building-wide fire control with reduced accidental discharge risk. Water-mist systems form a growing category with above-average growth. Their primary application is data halls, machinery and selected electrical areas. Aspirating smoke detection forms an established critical detection layer with strong growth. Its primary application is very-early warning in high-airflow spaces. Battery off-gas and thermal monitoring has a small 2026 base but is the fastest-growing category. Its primary application is UPS and BESS rooms and pre-thermal-runaway intervention. Fire alarm and releasing controls form a core integration layer with strong growth. Their primary application is coordinating alarms, suppression, shutdown and facility response.
The market is segmented by system type, detection technology, suppression technology, protected area, project type and geography. System types include fire detection systems, fire suppression systems, fire alarm and releasing controls, and engineering, installation and lifecycle services. Detection technologies include aspirating smoke detection, point smoke and heat detection, flame and thermal detection, and battery off-gas and thermal-runaway monitoring. Suppression technologies include clean-agent chemical suppression, inert-gas suppression, pre-action sprinkler systems, low- and high-pressure water mist, localized cabinet and equipment suppression, and other special-hazard systems. Protected areas include data halls and server rooms, UPS and battery rooms, electrical and switchgear rooms, generator and fuel areas, mechanical and cooling infrastructure, and modular and containerized AI infrastructure. Project types include greenfield AI factories, hyperscale and colocation expansions, AI-readiness retrofits, and sovereign and enterprise AI facilities.
Very-early-warning detection gains importance as high airflow can dilute conventional smoke signatures. Suppression systems remain the largest 2026 revenue pool across critical data-center spaces. Battery off-gas detection is the fastest-growing detection layer through 2032 worldwide. Water mist is expanding where operators seek lower water use and equipment damage. AI rack density increases the financial consequence of delayed detection and prolonged downtime. PFAS supply changes are accelerating reassessment of clean-agent portfolios and system design. Retrofit demand grows as existing facilities add batteries, liquid cooling and higher-density AI clusters.

Competitive and Strategic Outlook

The competitive landscape combines global building-technology groups, special-hazard fire-protection manufacturers and specialist data-center integrators. Johnson Controls, Siemens and Honeywell offer broad portfolios spanning detection, alarm controls, suppression and lifecycle services. Minimax and Fike compete strongly in special-hazard environments through gaseous suppression, water mist and data-center-specific protection designs. Kidde Global Solutions operates as a standalone fire-and-life-safety platform following the sale of Carrier's commercial and residential fire business to Lone Star Funds. It brings together Kidde, Edwards and related brands.
Specialist providers differentiate through technology depth and project execution. ORR Protection focuses heavily on data centers and combines design, installation, upgrades, inspection and remote monitoring. Securiton, Bosch, Hochiki and Apollo Fire Detectors compete in advanced fire detection and aspirating or point-sensing ecosystems. Marioff and Viking participate in water-mist and sprinkler protection. WAGNER Group provides oxygen-reduction and fire-prevention systems for selected critical environments. Fireaway's Stat-X condensed-aerosol technology participates in localized and special-hazard applications. Competitive advantage increasingly depends on early detection performance, battery-risk capability, suppression-agent availability, commissioning expertise and the ability to support globally standardized hyperscale designs.
North America is the largest market for AI data-center fire detection and suppression systems. The United States combines the world's largest concentration of hyperscale and neocloud investment with rapid expansion of lithium-ion UPS, battery storage and high-density electrical infrastructure. The region also has mature fire-code, insurer and commissioning practices that generally require layered protection rather than a single technology. As AI campuses scale into hundreds of megawatts, fire protection increasingly extends across multiple data halls, electrical buildings, battery rooms, substations, generator zones and modular infrastructure blocks.
The supplier ecosystem is broad. Johnson Controls provides pre-action sprinklers, water mist and clean-agent solutions. Honeywell supplies VESDA aspirating smoke detection and integrated fire controls. Siemens is expanding ASD+ and Sinorix suppression portfolios. Fike, Kidde Global Solutions and Minimax provide special-hazard suppression and detection. Specialist integrators such as ORR Protection design, install and service multi-technology systems for hyperscale operators. ORR states that it supports more than 80% of top hyperscale and enterprise data-center providers in the United States across more than 74 million square feet of protected data-center space. This illustrates the scale of specialist service demand.
Retrofit demand is important alongside greenfield construction. Many existing facilities are replacing valve-regulated lead-acid batteries with lithium-ion systems. They are adding higher-density power rooms, deploying liquid-cooled AI clusters and changing airflow patterns. These changes can require detector relocation, new aspirating zones, revised suppression-release logic, battery off-gas monitoring or requalification of enclosure integrity. Through 2032, North American demand is therefore expected to come from both new AI campuses and repeated safety upgrades within the installed data-center base.
Europe remains a significant market with strong emphasis on environmental performance, suppression-agent selection and high-quality engineered systems. Asia Pacific combines rapid capacity growth with substantial data-center construction in China, Japan, South Korea, Singapore, Malaysia, India and Australia. The Middle East is developing large greenfield AI campuses where integrated fire protection can be specified early in design. This allows advanced detection, inert-gas protection and centralized monitoring to be incorporated from the outset.
Recent developments confirm accelerating market activity. In August 2026, Siemens highlighted the shift toward earlier, more targeted fire detection and suppression for environments including data centers and lithium-ion battery installations. In June 2026, Johnson Controls published updated data-center fire-protection guidance covering acceptable damage thresholds, water mist, gaseous extinguishing and layered resilience planning. In June 2026, Siemens showcased ASD+ in the United States at NFPA 2026, targeting demanding applications including data centers and lithium-ion battery energy storage. In March 2026, Siemens published AI-data-center fire-protection guidance describing aspirating detection, total-flooding suppression and battery off-gas-driven prevention strategies. In March 2026, Johnson Controls published updated guidance on data-center fire protection, emphasizing very-early warning, clean-agent systems, pre-action sprinklers, water mist and lithium-ion thermal-runaway risk. In February 2026, Johnson Controls introduced its Five Ss framework for data-center fire suppression, balancing safety, space, speed, spend and sustainability. At the end of 2025, 3M completed its exit from PFAS manufacturing, reinforcing industry evaluation of alternative clean agents, inert gases and water-mist strategies.

Conclusion

The AI data center fire detection and suppression systems market is growing steadily as AI capacity expands and battery deployment increases. Growth is driven by higher asset concentration, lithium-ion UPS and BESS expansion, high-airflow detection requirements and the suppression-agent transition. Suppression systems form the largest revenue pool. Battery off-gas detection is the fastest-growing detection layer. Water mist is expanding where operators seek lower water use and equipment damage. North America leads spending. Europe, Asia Pacific and the Middle East are also expanding. Local code variability, agent supply uncertainty and battery thermal-runaway complexity remain the key restraints. The market is projected to grow from USD 1.10 billion in 2026 to USD 2.84 billion by 2032 at a CAGR of 17.1%.

Key Benefits of this Report

Insightful Analysis: Detailed market insights across regions, customer segments, policies, socio-economic factors, consumer preferences, and industry verticals.
Competitive Landscape: Understand strategic moves by key players to identify optimal market entry approaches.
Market Drivers and Future Trends: Assess major growth forces and emerging developments shaping the market.
Actionable Recommendations: Support strategic decisions to unlock new revenue streams.
Caters to a Wide Audience: Suitable for startups, research institutions, consultants, SMEs, and large enterprises.

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Report Coverage

Historical data from 2021 to 2024, Base year 2025, and Forecast years from 2026 to 2032
Growth opportunities, challenges, supply chain outlook, regulatory framework, and trend analysis
Competitive positioning, strategies, and market share evaluation, and trade analysis
Revenue growth and forecast assessment across segments and regions
Company profiling including strategies, products, financials, and key developments

1. Executive Summary

1.1. Market Opportunity and Key Findings
1.2. Fire-Risk Evolution in AI Data Centers
1.3. Principal Revenue Pools

2. Market Overview

2.1. Fire Risk across AI Data Center Infrastructure
2.2. High-Airflow Detection Challenges
2.3. Lithium-Ion UPS and BESS Fire Risk
2.4. Layered Fire Protection Architecture
2.5. Suppression-Agent Transition and Sustainability

3. Market Size and Forecast, 2026-2032

3.1. Global Market Revenue
3.2. Annual Growth Analysis
3.3. New-Build versus Retrofit Demand
3.4. Protection Content per Data Center Site

4. Market by System Type

4.1. Fire Detection Systems
4.2. Fire Suppression Systems
4.3. Fire Alarm and Releasing Controls
4.4. Engineering, Installation and Lifecycle Services

5. Market by Detection Technology

5.1. Aspirating Smoke Detection
5.2. Point Smoke and Heat Detection
5.3. Flame and Thermal Detection
5.4. Battery Off-Gas and Thermal-Runaway Monitoring

6. Market by Suppression Technology

6.1. Clean-Agent Chemical Suppression
6.2. Inert-Gas Suppression
6.3. Pre-Action Sprinkler Systems
6.4. Low- and High-Pressure Water Mist
6.5. Localized Cabinet and Equipment Suppression
6.6. Other Special-Hazard Systems

7. Market by Protected Area

7.1. Data Halls and Server Rooms
7.2. UPS and Battery Rooms
7.3. Electrical and Switchgear Rooms
7.4. Generator and Fuel Areas
7.5. Mechanical and Cooling Infrastructure
7.6. Modular and Containerized AI Infrastructure

8. Market by Project Type

8.1. Greenfield AI Factories
8.2. Hyperscale and Colocation Expansions
8.3. AI-Readiness Retrofits
8.4. Sovereign and Enterprise AI Facilities

9. Regional Market

9.1. North America
- 9.1.1. United States
- 9.1.2. Canada
9.2. Europe
9.3. Asia Pacific
9.4. Middle East and Rest of World

10. Market Dynamics

10.1. Drivers
- 10.1.1. Higher Asset Concentration and Downtime Cost
- 10.1.2. Expansion of Lithium-Ion UPS and BESS
- 10.1.3. High-Airflow Detection Requirements
- 10.1.4. Suppression-Agent and Sustainability Transition
10.2. Restraints
- 10.2.1. Local Code and AHJ Variability
- 10.2.2. Suppression-Agent Supply and Regulatory Uncertainty
- 10.2.3. Battery Thermal-Runaway Complexity
- 10.2.4. Retrofit and Enclosure Constraints