市場調查報告書
商品編碼
1466010
自然災害檢測物聯網市場:按組件、技術、應用和最終用戶分類 - 2024-2030 年全球預測Natural Disaster Detection IoT Market by Component, Technology, Application, End-User - Global Forecast 2024-2030 |
※ 本網頁內容可能與最新版本有所差異。詳細情況請與我們聯繫。
預計2023年自然災害檢測物聯網市場規模為66.8億美元,預計2024年將達84.5億美元,2030年將達373.2億美元,複合年成長率為27.85%。
使用物聯網(IoT)進行自然災害偵測是指應用互連的配備感測器的設備來收集和傳輸資料,以偵測、監控和應對自然災害。這些物聯網設備將部署在地震、海嘯、颶風、洪水和野火等自然災害易發地區,為早期預警和快速反應提供必要的即時資料。自然災害檢測物聯網市場的成長受到感測器和機器對機器通訊技術進步、氣候變遷導致的世界自然災害數量增加、脆弱地區的都市化以及政府對災害的投資的影響備災基礎設施。此外,用於預測分析的人工智慧 (AI) 和機器學習 (ML) 的整合,以及物聯網平台中雲端運算的日益採用,都進一步刺激了需求。然而,一些限制和挑戰阻礙了市場的成長,包括物聯網基礎設施的初始設置成本高、感測器和設備的維護和更新、對資料隱私和安全的擔憂以及不同技術之間的標準化需求。此外,擴展物聯網基礎設施、建立強大的低延遲通訊網路以進行即時警報以及開發人工智慧主導的預測模型是當前準確預測災害事件的機會。加強社區復原力的官民合作關係以及部署邊緣運算來處理更接近源頭的資料也有越來越大的潛力來加快回應時間。此外,我們正在研究和開發提高即時資料分析的準確性,建立自適應學習系統以應對不斷變化的威脅場景,並探索區塊鏈技術以實現災難期間安全可靠的資料共用,我們希望您能關注。更多關於這一點。提高公眾意識提升並促進有關技術採用的教育計劃可以進一步促進市場滲透和擴張。
主要市場統計 | |
---|---|
基準年[2023] | 66.8億美元 |
預測年份 [2024] | 84.5億美元 |
預測年份 [2030] | 373.2億美元 |
複合年成長率(%) | 27.85% |
對硬體的依賴增加,包括 24/7 組件監控、即時更新和自然災害自動警報
自然災害檢測物聯網硬體包括有形組件和設備,例如物聯網感測器、致動器、電腦晶片、電纜和智慧型設備,用於實現連接和檢測環境變化。提供複雜演算法和長期資訊保留所需的處理能力和資料歸檔功能。資料傳輸設備確保感測器與中央資料中心之間的無縫連接和通訊,促進資訊的快速中繼。電力供應和能源儲存系統對於穩定運作至關重要,特別是在受自然災害影響的偏遠地區或電力短缺的地區。感測器和探測器是一線組件,負責捕獲指示潛在災害的環境資料和訊號,用戶界面和通知系統使資訊獲取民主化,並吸引相關人員和公眾參與,從而能夠及時向公眾發出警告和警報,並促使立即採取行動。
自然災害偵測物聯網市場提供快速監控潛在風險並向使用者發出警報的服務。這些服務通常包括 24/7 監控、即時更新、自動警報和視覺化儀表板,以幫助即時追蹤與即將發生的自然災害情況相關的途徑和狀態。軟體解決方案通常提供一個集中檢測系統,向指揮中心發送警報。自然災害偵測物聯網軟體透過整合人工智慧和機器學習等先進技術,可以提供更準確的結果。自然災害管理當局可以透過為特定區域配備感測器設備、微控制器和各種檢測和分析環境條件的軟體應用程式來實現更好的控制。通訊和網路軟體建立了強大的感測器資料傳輸通道,並確保不同設備和平台之間的互通性,從而在發生危機時實現即時警報和協調。資料分析和管理軟體處理大量的環境資料,並使用先進的演算法來檢測模式、預測事件並支援決策,從而縮短回應時間並減少誤報。地理資訊系統 (GIS) 軟體在地圖上直覺地表示資料,整合了地形、人口和基礎設施資訊層,這些資訊對於規劃、風險評估和實施有效的疏散策略至關重要。
科技:更多採用人工智慧(AI)來提高對自然災害的了解
先進計算和巨量資料分析對於處理大量環境資料至關重要。這些技術對於解釋感測器資料和天氣模式以及提供預測見解以預防自然災害的影響至關重要。高效能運算系統可以管理來自物聯網網路的大量資料吞吐量,這對於近即時分析至關重要。人工智慧 (AI) 和機器學習 (ML) 技術使系統能夠理解歷史資料並隨著時間的推移改進預測,從而徹底改變自然災害檢測領域。人工智慧和機器學習 (ML) 技術可以透過識別自然災害領先的典型模式來協助災害預測,並為當局提供可操作的見解以降低風險。物聯網廣泛依賴行動和通訊技術將資料從感測器傳輸到執行分析的伺服器。即使在最不利的條件下,這些技術對於確保無縫資訊流至關重要。衛星、行動電話網路和無線通訊系統(包括 5G)都是實現即時資料傳輸的基礎設施的一部分。
檢測惡劣天氣條件的應用程式普及
基於物聯網的即時地震檢測系統可在地方、國家和全球層面使用。每個城市都可以部署地震探測系統,所有地震探測設備都可以利用物聯網平台進行即時監控。自然災害管理機構正在使用新興的基於物聯網的自動洪水檢測和預防系統來提供持續的監測和預警。同樣,這些基於物聯網的系統用於監測極端乾旱狀況。火災警報系統中的物聯網技術使用溫度、火焰和煙霧感測器來偵測火災案例,並即使在偏遠地區也能提供早期回應警報。持續監測天氣狀況並進行相應更新的持續多年的天氣監測技術透過物聯網技術的整合得到了增強。山體滑坡的即時監測是具有挑戰性的研究領域之一,也可以透過無線感測器網路進行監測,以做出關鍵和緊急回應。
最終用戶:政府增加對自然災害檢測物聯網系統的投資,以實現快速有效的回應
政府機構正在使用這種自然災害檢測物聯網系統來快速有效地回應。各國政府正在增加對新天氣監測技術的投資,以追蹤自然狀況。執法機構主要利用物聯網系統進行災難偵測,例如疏散計畫、災後取證分析以及緊急情況下維護公共秩序。他們的要求通常集中在行動性、快速部署能力和安全通訊通道。私人公司可以使用自然災害偵測物聯網系統來保護資產、遵守法規並確保員工安全。這些公司正在尋找經濟高效且易於整合到其業務流程中的解決方案。消防員和護理人員等救援人員需要可攜式、耐用且易於使用的物聯網解決方案。他們優先考慮幫助定位受害者、評估結構完整性以及在救援行動期間即時監測環境條件的設備。
區域洞察
在亞太地區,日本地震、東南亞海嘯、印度颶風等天災的發生率不斷上升,帶動了消費者對自然災害偵測物聯網解決方案的需求。日本正在策略性地利用物聯網和地震儀的先進組合進行預警。該地區先進感測器技術和通訊專利不斷湧現,而中國在研發投資方面處於領先地位。隨著美洲專注於應對颶風、龍捲風和野火,美國公司正在挑戰與智慧家庭無縫整合並提供即時警報的災難偵測和緩解物聯網工具的極限。加拿大由於其多樣化的氣候而面臨挑戰,並專注於物聯網以應對野火和洪水。美國緊急災難管理署(FEMA) 綜合公共預警系統是政府投資利用物聯網進行廣泛災害預警的典型例子。此外,歐洲、中東和非洲地區的應對措施取決於其多樣化的區域和氣候條件,並且技術投資堅持科學嚴謹性和永續性。中東地區重點關注防治沙漠化以及投資物聯網來預測沙塵暴和管理水資源短缺,反映了該地區對乾旱氣候的適應。在非洲,重點是可負擔且可部署的物聯網系統,以應對乾旱、洪水和蝗蟲群,非洲聯盟非洲災害風險資金籌措支持減少災害風險的技術,其中包括物聯網計畫。
FPNV定位矩陣
FPNV定位矩陣對於評估自然災害偵測物聯網市場至關重要。我們檢視與業務策略和產品滿意度相關的關鍵指標,以對供應商進行全面評估。這種深入的分析使用戶能夠根據自己的要求做出明智的決策。根據評估,供應商被分為四個成功程度不同的像限:前沿(F)、探路者(P)、利基(N)和重要(V)。
市場佔有率分析
市場佔有率分析是一種綜合工具,可以對自然災害檢測物聯網市場中供應商的現狀進行深入而詳細的研究。全面比較和分析供應商在整體收益、基本客群和其他關鍵指標方面的貢獻,以便更好地了解公司的績效及其在爭奪市場佔有率時面臨的挑戰。此外,該分析還提供了對該行業競爭特徵的寶貴見解,包括在研究基準年觀察到的累積、分散主導地位和合併特徵等因素。詳細程度的提高使供應商能夠做出更明智的決策並制定有效的策略,從而在市場上獲得競爭優勢。
1. 市場滲透率:提供有關主要企業所服務的市場的全面資訊。
2. 市場開拓:我們深入研究利潤豐厚的新興市場,並分析其在成熟細分市場的滲透率。
3. 市場多元化:提供有關新產品發布、開拓地區、最新發展和投資的詳細資訊。
4. 競爭評估和情報:對主要企業的市場佔有率、策略、產品、認證、監管狀況、專利狀況和製造能力進行全面評估。
5. 產品開發與創新:提供對未來技術、研發活動和突破性產品開發的見解。
1.自然災害偵測物聯網市場的市場規模和預測是多少?
2.在自然災害偵測物聯網市場的預測期內,有哪些產品、細分市場、應用程式和領域需要考慮投資?
3.自然災害檢測物聯網市場的技術趨勢和法規結構是什麼?
4.自然災害檢測物聯網市場主要廠商的市場佔有率是多少?
5.進入自然災害偵測物聯網市場的合適型態和策略手段是什麼?
全球暖化
[192 Pages Report] The Natural Disaster Detection IoT Market size was estimated at USD 6.68 billion in 2023 and expected to reach USD 8.45 billion in 2024, at a CAGR 27.85% to reach USD 37.32 billion by 2030.
Natural disaster detection using the Internet of Things (IoT) refers to the application of interconnected, sensor-equipped devices to collect and transmit data to detect, monitor, and respond to natural disasters. These IoT devices are deployed in areas susceptible to natural catastrophes such as earthquakes, tsunamis, hurricanes, floods, and wildfires, providing real-time data crucial for early warning and rapid response. Growth in the natural disaster detection IoT market is influenced by technological advancements in sensors and machine-to-machine communication, increased global prevalence of natural disasters due to climate change, urbanization in vulnerable areas, and governmental investment in disaster preparedness infrastructure. Additionally, integrating artificial intelligence (AI) and machine learning (ML) for predictive analytics and the growing adoption of cloud computing in IoT platforms further stimulate demand. However, several limitations and challenging factors include high initial set-up costs of IoT infrastructure, maintenance & updating of sensors & equipment, data privacy & security concerns, and the need for standardization across different technologies are hampering the market growth. Moreover, scaling IoT infrastructure, creating robust, low-latency communication networks for real-time alerts, and developing AI-driven predictive models are current opportunities that accurately anticipate disaster events. There is also expanding potential in public-private partnerships to enhance community resilience and the deployment of edge computing to process data closer to the source, thereby hastening response times. Furthermore, it is expected to focus more on research & development to enhance the precision of real-time data analysis, create adaptive learning systems for evolving threat scenarios, and explore blockchain technologies for secure and reliable data sharing during disaster events. Advancing public awareness and education programs on technology adoption could further drive market penetration and expansion.
KEY MARKET STATISTICS | |
---|---|
Base Year [2023] | USD 6.68 billion |
Estimated Year [2024] | USD 8.45 billion |
Forecast Year [2030] | USD 37.32 billion |
CAGR (%) | 27.85% |
Component: Increasing reliance on hardware for 24/7 monitoring, real-time updates, and automated alerts of natural disaster
Natural disaster detection IoT hardware involves the tangible components & devices, such as IoT sensors, actuators, computer chips, cables, and smart devices, employed to enable connectivity and detect environmental changes. Computational & storage devices are major in disaster detection IoT, providing the processing power and data archival capabilities required for complex algorithms and long-term information retention. Data transmission devices ensure seamless connectivity and communication between sensors and central data centers, facilitating the swift relay of information. Power supply & energy storage systems are essential for consistent operation, especially in remote or power-deficient areas impacted by natural disasters. The sensors & detectors are the frontline components, tasked with capturing environmental data and signals indicative of potential disasters, while user interface & notification systems democratize access to the information, enabling timely warnings and alerts to stakeholders and the public for prompt action.
The natural disaster detection IoT market offers services to quickly monitor and alert users of potential risks. These services commonly include 24/7 monitoring, real-time updates, automated alerts, and visual dashboards to help track pathways and conditions related to any upcoming natural disaster conditions in real-time. The software solution commonly provides centralized detection systems that send alerts to a command center. Natural disaster detection IoT software can offer more accurate results by integrating advanced technology, such as artificial intelligence and machine learning. Natural disaster management authorities can create better management by equipping a particular region with sensor devices, microcontrollers, and various software applications to detect and analyze environmental conditions. Communication & networking software establishes robust channels for transmitting sensor data and ensures interoperability among various devices and platforms, enabling real-time alerts and coordination during crises. Data analysis & management software processes the vast inflow of environmental data, using sophisticated algorithms to detect patterns, predict events, and support decision-making, enhancing response times and reducing false alarms. Geographic information system (GIS) software visually represents data on maps, integrating layers of information about terrains, populations, and infrastructure, essential for planning, risk assessment, and executing efficient evacuation strategies.
Technology: Increasing adoption of artificial intelligence (AI) to enhance understanding of natural disasters
Advanced computing and big data analytics are pivotal in processing vast amounts of environmental data. These technologies are crucial for interpreting sensor data and weather patterns and providing predictive insights to preempt the effects of natural disasters. High-performance computing systems can manage the vast throughput of data from IoT networks, which are essential for near-real-time analysis. Artificial intelligence (AI) and machine learning (ML) technologies are revolutionizing the field of natural disaster detection by enabling systems to understand historical data and improve predictions over time. They assist in forecasting disasters by identifying patterns that usually precede natural disturbances and can provide authorities with actionable insights to mitigate the risks. IoT relies extensively on mobile and communication technologies to transmit data from sensors to the servers where analysis occurs. These technologies are essential for ensuring a seamless flow of information even in the most adverse conditions. Satellites, cellular networks, and wireless communication systems, including 5G, are all part of this infrastructure that makes real-time data transmission possible.
Application: Increasing proliferation for detecting harsh weather conditions
IoT-based real-time earthquake detector systems can be used at the provincial, national, or global levels. The earthquake detection system can be deployed in every city, and every earthquake detector device can be monitored in real time utilizing the IoT platform. The emerging IoT-based automatic flood detection & prevention systems are used to continuously monitor and provide alerts by natural disaster management authorities. Similarly, these IoT-based systems are used to monitor conditions for extreme drought. IoT technology in fire alert systems uses temperature, flame, and smoke sensors to detect cases of fire and provide alerts for early response, even in remote locations. The weather monitoring technologies present over the several years to continuously monitor the weather conditions and update accordingly, which has been enhanced with the integration of the IoT technology. Real-time monitoring of landslides is one of the challenging research areas that can also be monitored with the wireless sensor network for critical and emergency responses.
End-User: Increasing investments from governments in natural disaster detection IoT systems for quick and effective response
Government organizations use this natural disaster detection IoT system for quick and effective response. Governments are increasingly investing in new weather monitoring technologies and tracking natural conditions. Law enforcement agencies utilize IoT systems for disaster detection, mainly for evacuation planning, forensic analysis post-disaster, and maintaining public order during emergencies. Their requirements often focus on mobility, rapid deployment capabilities, and secure communication channels. Private companies may use natural disaster detection IoT systems to protect assets, comply with regulations, and ensure the safety of their personnel, focusing on site-specific needs. They are interested in cost-effective, tailored solutions that can be easily integrated with their operational processes. Rescue personnel, such as firefighters and paramedics, require portable, durable, and user-friendly IoT solutions. They prioritize equipment that aids in locating victims, assessing structural' integrity, and monitoring environmental conditions in real-time during rescue operations.
Regional Insights
The Asia-Pacific region has witnessed an uptick in natural disaster occurrences, such as earthquakes in Japan, tsunamis in Southeast Asia, and cyclones in India, spawning increased consumer demand for IoT solutions in natural disaster detection. Japan strategically utilizes a sophisticated combination of IoT and seismography for early warnings. The region shows a surge in advanced sensor technology and communication patents, with China at the forefront of R&D investments. The Americas are focused on responding to hurricanes, tornadoes, and wildfires, with American companies pushing the envelope in disaster-detection-cum-mitigation IoT tools that blend seamlessly with smart homes and provide real-time alerts. Canada, facing challenges due to its diverse climate, is channeling efforts into tailored IoT responses for wildfires and floods. The U.S. FEMA's Integrated Public Alert and Warning System typifies government investment in harnessing IoT for widespread disaster alerts. Moreover, the EMEA region's response is shaped by its diverse geography and climatic conditions, with technological investments adhering to scientific rigor and sustainability. The Middle East concentrates on combating desertification, investing in IoT to anticipate sandstorms and manage water scarcity, reflecting the region's adaptation to its dry climate. In Africa, the focus is on affordable and deployable IoT systems to cope with droughts, floods, and locust swarms, highlighted by the African Union's Africa Disaster Risk Financing Programme supporting disaster risk reduction tech, including IoT.
FPNV Positioning Matrix
The FPNV Positioning Matrix is pivotal in evaluating the Natural Disaster Detection IoT Market. It offers a comprehensive assessment of vendors, examining key metrics related to Business Strategy and Product Satisfaction. This in-depth analysis empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success: Forefront (F), Pathfinder (P), Niche (N), or Vital (V).
Market Share Analysis
The Market Share Analysis is a comprehensive tool that provides an insightful and in-depth examination of the current state of vendors in the Natural Disaster Detection IoT Market. By meticulously comparing and analyzing vendor contributions in terms of overall revenue, customer base, and other key metrics, we can offer companies a greater understanding of their performance and the challenges they face when competing for market share. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With this expanded level of detail, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.
Key Company Profiles
The report delves into recent significant developments in the Natural Disaster Detection IoT Market, highlighting leading vendors and their innovative profiles. These include ABB Ltd., Accenture PLC, ALE International SAS, Aplicaciones Tecnologicas S.A., AT&T Inc., Atos SE, BlackBerry Limited, Cisco Systems Inc., Eaton Corporation PLC, Environmental Systems Research Institute, Inc, Google LLC by Alphabet Inc., Green Stream Technologies, Inc., Grillo Holdings Inc., Hala Systems, Inc., Hitachi Ltd., InfiSIM Ltd., Infosys Limited, Intel Corporation, International Business Machines Corporation, Knowx Innovations Pvt. Ltd., Mitsubishi Electric Corporation, NEC Corporation, Nokia Corporation, One Concern, Inc., Optex Co., Ltd., OroraTech GmbH, Responscity Systems Private Limited, Sadeem International Company, SAP SE, Scanpoint Geomatics Ltd., Semtech Corporation, Sony Group Corporation, Telefonaktiebolaget LM Ericsson, Tractable Ltd., Trinity Mobility Private Limited, Venti LLC, and Zebra Technologies Corporation.
Market Segmentation & Coverage
1. Market Penetration: It presents comprehensive information on the market provided by key players.
2. Market Development: It delves deep into lucrative emerging markets and analyzes the penetration across mature market segments.
3. Market Diversification: It provides detailed information on new product launches, untapped geographic regions, recent developments, and investments.
4. Competitive Assessment & Intelligence: It conducts an exhaustive assessment of market shares, strategies, products, certifications, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players.
5. Product Development & Innovation: It offers intelligent insights on future technologies, R&D activities, and breakthrough product developments.
1. What is the market size and forecast of the Natural Disaster Detection IoT Market?
2. Which products, segments, applications, and areas should one consider investing in over the forecast period in the Natural Disaster Detection IoT Market?
3. What are the technology trends and regulatory frameworks in the Natural Disaster Detection IoT Market?
4. What is the market share of the leading vendors in the Natural Disaster Detection IoT Market?
5. Which modes and strategic moves are suitable for entering the Natural Disaster Detection IoT Market?
and global warming