市场调查报告书
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自然灾害检测物联网市场:按组件、技术、应用和最终用户划分 - 2024-2030 年全球预测Natural Disaster Detection IoT Market by Component, Technology, Application, End-User - Global Forecast 2024-2030 |
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预计2023年自然灾害检测物联网市场规模为66.8亿美元,预计2024年将达84.5亿美元,2030年将达373.2亿美元,复合年增长率为27.85%。
使用物联网(IoT)进行自然灾害侦测是指应用互连的配备感测器的设备来收集和传输资料,以侦测、监控和应对自然灾害。这些物联网设备将部署在地震、海啸、飓风、洪水和野火等自然灾害易发地区,为早期预警和快速反应提供必要的即时资料。自然灾害检测物联网市场的成长受到感测器和机器对机器通讯技术进步、气候变迁导致的世界自然灾害数量增加、脆弱地区的都市化以及政府对灾害的投资的影响备灾基础设施。此外,用于预测分析的人工智慧 (AI) 和机器学习 (ML) 的集成,以及物联网平台中云端运算的日益采用,都进一步刺激了需求。然而,一些限制和挑战阻碍了市场的成长,包括物联网基础设施的初始设置成本高、感测器和设备的维护和更新、对资料隐私和安全的担忧以及不同技术之间的标准化需求。此外,扩展物联网基础设施、建立强大的低延迟通讯网路以进行即时警报以及开发人工智慧主导的预测模型是当前准确预测灾害事件的机会。加强社区復原力的官民合作关係以及部署边缘运算来处理更接近源头的资料也有越来越大的潜力来加快回应时间。此外,我们正在研究和开发提高即时资料分析的准确性,建立自适应学习系统以应对不断变化的威胁场景,并探索区块链技术以实现灾难期间安全可靠的资料共用,我们希望您能关注。更多关于这一点。提高公众意识提升并促进有关技术采用的教育计划可以进一步促进市场渗透和扩张。
主要市场统计 | |
---|---|
基准年[2023] | 66.8亿美元 |
预测年份 [2024] | 84.5亿美元 |
预测年份 [2030] | 373.2亿美元 |
复合年增长率(%) | 27.85% |
对硬体的依赖增加,包括 24/7 组件监控、即时更新和自然灾害自动警报
自然灾害检测物联网硬体包括有形组件和设备,例如物联网感测器、致动器、电脑晶片、电缆和智慧型设备,用于实现连接和检测环境变化。提供复杂演算法和长期资讯保留所需的处理能力和资料归檔功能。资料传输设备确保感测器与中央资料中心之间的无缝连接和通讯,促进资讯的快速中继。电力供应和能源储存系统对于稳定运作至关重要,特别是在受自然灾害影响的偏远地区或电力短缺的地区。感测器和探测器是一线组件,负责捕获指示潜在灾害的环境资料和信号,用户界面和通知系统使信息获取民主化,并吸引相关人员和公众参与,从而能够及时向公众发出警告和警报,并促使立即采取行动。
自然灾害侦测物联网市场提供快速监控潜在风险并向使用者发出警报的服务。这些服务通常包括 24/7 监控、即时更新、自动警报和视觉化仪表板,以帮助即时追踪与即将发生的自然灾害情况相关的途径和状态。软体解决方案通常提供一个集中检测系统,向指挥中心发送警报。自然灾害侦测物联网软体透过整合人工智慧和机器学习等先进技术,可以提供更准确的结果。自然灾害管理当局可以透过为特定区域配备感测器设备、微控制器和各种检测和分析环境条件的软体应用程式来实现更好的控制。通讯和网路软体建立了强大的感测器资料传输通道,并确保不同设备和平台之间的互通性,从而在发生危机时实现即时警报和协调。资料分析和管理软体处理大量的环境资料,并使用先进的演算法来检测模式、预测事件并支援决策,从而缩短回应时间并减少误报。地理资讯系统 (GIS) 软体在地图上直观地表示资料,整合了地形、人口和基础设施资讯层,这些资讯对于规划、风险评估和实施有效的疏散策略至关重要。
科技:更多采用人工智慧(AI)来提高对自然灾害的了解
先进计算和巨量资料分析对于处理大量环境资料至关重要。这些技术对于解释感测器资料和天气模式以及提供预测见解以预防自然灾害的影响至关重要。高效能运算系统可以管理来自物联网网路的大量资料吞吐量,这对于近即时分析至关重要。人工智慧 (AI) 和机器学习 (ML) 技术使系统能够理解历史资料并随着时间的推移改进预测,从而彻底改变自然灾害检测领域。人工智慧和机器学习 (ML) 技术可以透过识别自然灾害领先的典型模式来协助灾害预测,并为当局提供可操作的见解以降低风险。物联网广泛依赖行动和通讯技术将资料从感测器传输到执行分析的伺服器。即使在最不利的条件下,这些技术对于确保无缝资讯流至关重要。卫星、行动电话网路和无线通讯系统(包括 5G)都是实现即时资料传输的基础设施的一部分。
检测恶劣天气条件的应用程式普及
基于物联网的即时地震检测系统可在地方、国家和全球层面使用。每个城市都可以部署地震探测系统,所有地震探测设备都可以利用物联网平台进行即时监控。自然灾害管理机构正在使用新兴的基于物联网的自动洪水检测和预防系统来提供持续的监测和预警。同样,这些基于物联网的系统用于监测极端干旱状况。火灾警报系统中的物联网技术使用温度、火焰和烟雾感测器来侦测火灾案例,并即使在偏远地区也能提供早期回应警报。持续监测天气状况并进行相应更新的持续多年的天气监测技术透过物联网技术的整合得到了增强。山体滑坡的即时监测是具有挑战性的研究领域之一,也可以透过无线感测器网路进行监测,以做出关键和紧急回应。
最终用户:政府增加对自然灾害检测物联网系统的投资,以实现快速有效的回应
政府机构正在使用这种自然灾害检测物联网系统来快速有效地回应。各国政府正在增加对新天气监测技术的投资,以追踪自然状况。执法机构主要利用物联网系统进行灾难侦测,例如疏散计画、灾后取证分析以及紧急情况下维护公共秩序。他们的要求通常集中在行动性、快速部署能力和安全通讯通道。私人公司可以使用自然灾害侦测物联网系统来保护资产、遵守法规并确保员工安全。这些公司正在寻找经济高效且易于整合到其业务流程中的解决方案。消防员和护理人员等救援人员需要可携式、耐用且易于使用的物联网解决方案。他们优先考虑帮助定位受害者、评估结构完整性以及在救援行动期间即时监测环境条件的设备。
区域洞察
在亚太地区,日本地震、东南亚海啸、印度飓风等天灾的发生率不断上升,带动了消费者对自然灾害侦测物联网解决方案的需求。日本正在策略性地利用物联网和地震仪的先进组合进行预警。该地区先进感测器技术和通讯专利不断涌现,而中国在研发投资方面处于领先地位。随着美洲专注于应对飓风、龙捲风和野火,美国公司正在挑战与智慧家庭无缝整合并提供即时警报的灾难侦测和缓解物联网工具的极限。加拿大由于其多样化的气候而面临挑战,并专注于物联网以应对野火和洪水。美国紧急灾难管理署(FEMA) 综合公共预警系统是政府投资利用物联网进行广泛灾害预警的典型例子。此外,欧洲、中东和非洲地区的应对措施取决于其多样化的区域和气候条件,并且技术投资坚持科学严谨性和永续性。中东地区重点关注防治沙漠化以及投资物联网来预测沙尘暴和管理水资源短缺,反映了该地区对干旱气候的适应。在非洲,重点是可负担且可部署的物联网系统,以应对干旱、洪水和蝗虫群,非洲联盟非洲灾害风险资金筹措支持减少灾害风险的技术,其中包括物联网计画。
FPNV定位矩阵
FPNV定位矩阵对于评估自然灾害侦测物联网市场至关重要。我们检视与业务策略和产品满意度相关的关键指标,以对供应商进行全面评估。这种深入的分析使用户能够根据自己的要求做出明智的决策。根据评估,供应商被分为四个成功程度不同的像限:前沿(F)、探路者(P)、利基(N)和重要(V)。
市场占有率分析
市场占有率分析是一种综合工具,可以对自然灾害检测物联网市场中供应商的现状进行深入而详细的研究。全面比较和分析供应商在整体收益、基本客群和其他关键指标方面的贡献,以便更好地了解公司的绩效及其在争夺市场占有率时面临的挑战。此外,该分析还提供了对该行业竞争特征的宝贵见解,包括在研究基准年观察到的累积、分散主导地位和合併特征等因素。详细程度的提高使供应商能够做出更明智的决策并制定有效的策略,从而在市场上获得竞争优势。
1. 市场渗透率:提供有关主要企业所服务的市场的全面资讯。
2. 市场开拓:我们深入研究利润丰厚的新兴市场,并分析其在成熟细分市场的渗透率。
3. 市场多元化:提供有关新产品发布、开拓地区、最新发展和投资的详细资讯。
4. 竞争评估和情报:对主要企业的市场占有率、策略、产品、认证、监管状况、专利状况和製造能力进行全面评估。
5. 产品开发与创新:提供对未来技术、研发活动和突破性产品开发的见解。
1.自然灾害侦测物联网市场的市场规模和预测是多少?
2.在自然灾害侦测物联网市场的预测期内,有哪些产品、细分市场、应用程式和领域需要考虑投资?
3.自然灾害检测物联网市场的技术趋势和法规结构是什么?
4.自然灾害检测物联网市场主要厂商的市场占有率是多少?
5.进入自然灾害侦测物联网市场的合适型态和策略手段是什么?
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 | |
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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