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市場調查報告書
商品編碼
1470419
邊緣人工智慧軟體市場:按組件、資料來源、應用程式和最終用途分類 - 全球預測,2024-2030 年Edge AI Software Market by Component (Services, Solution), Data Source (Biometric Data, Mobile Data, Sensor Data), Application, End-use - 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年邊緣人工智慧軟體市場規模為12.5億美元,預計2024年將達15.8億美元,2030年將達到65.4億美元,複合年成長率為26.55%。
邊緣人工智慧是指在邊緣運算環境中部署和利用人工智慧,從而在更靠近資料收集的地方執行複雜的運算,而不是在集中式雲端運算設施或異地資料中心中進行。邊緣人工智慧軟體允許機器學習演算法在實體硬體設備上運行。邊緣人工智慧軟體主要應用於工業自動化、監控、機器人和物聯網設備等各個領域。對低延遲和低頻寬消耗的即時處理的需求正在推動這些領域對邊緣人工智慧軟體的需求,並擴大了行業範圍。認知運算能力的增強,以及各種智慧型裝置產生的資料的激增,正在為邊緣人工智慧軟體創造大量潛在機會。整合和處理邊緣人工智慧軟體的困難,以及維護邊緣人工智慧軟體需要大量資源,可能會阻止新進入者進入這一領域。此外,資料隱私和安全問題,以及設備間通訊標準化通訊協定的缺乏,都阻礙了邊緣人工智慧軟體的普及。然而,製造商不斷投資於研發舉措,以改善其軟體服務的隱私通訊協定和資料安全性。邊緣人工智慧軟體創新和研究最有前景的領域是網路安全、自動化醫療系統和智慧城市等領域。 5G 連接、量子計算和自然語言處理 (NLP) 等技術進步為未來創新帶來了機會。
主要市場統計 | |
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基準年[2023] | 12.5億美元 |
預測年份 [2024] | 15.8億美元 |
預測年份 [2030] | 65.4億美元 |
複合年成長率(%) | 26.55% |
組成部分:支援邊緣人工智慧軟體解決方案進步的研究計劃
與 Edge AI 軟體相關的服務包括諮詢、整合和支援服務,可增強 Edge AI 軟體解決方案的整體功能、可用性和最佳化。這些服務旨在幫助企業部署人工智慧以滿足其獨特需求,從而推動效率和業務成長。邊緣人工智慧軟體服務支援和維護包括定期系統更新、快速故障排除、效能最佳化、即時威脅異常檢測以及主動故障預測的持續監控。透過仔細的系統整合和測試例行實踐來確保可靠的性能。培訓和諮詢包括技術培訓、最佳實踐方法的諮詢服務以及策略邊緣運算使用的諮詢服務。解決方案事業部將專注於人工智慧技術在網路邊緣的應用。這包括機器學習、深度學習、自然語言處理和電腦視覺。邊緣人工智慧平台是一個綜合的生態系統,為網路邊緣的資料收集、處理、分析和決策提供支援。邊緣人工智慧的軟體工具包括預先建構的人工智慧模型、人工智慧演算法、演算法訓練工具、分析軟體和應用開發工具。
資料來源:由於工業中感測器技術的使用增加而產生感測器資料
邊緣人工智慧軟體以有效的方式利用生物識別資料來檢驗身份驗證並建立更複雜的使用案例。通常由軟體管理的生物辨識資料包括指紋、臉部辨識、虹膜圖案等。行動資料構成邊緣人工智慧的關鍵部分,即時分析直接在行動和物聯網設備上管理。邊緣人工智慧允許設備在本地處理和解釋資料,從而提高效能並減少延遲和對持續網際網路連接的需求。邊緣人工智慧軟體利用物聯網設備、工業機械、智慧家庭系統和自動駕駛汽車的感測器資料。語音辨識作為一種邊緣人工智慧應用,為免持設備控制、轉錄服務和輔助技術帶來了巨大的價值。視訊和影像識別功能支援即時視訊分析、物件偵測和臉部辨識。由於邊緣人工智慧在本地處理資料,因此可以最大限度地減少頻寬使用和延遲,從而最佳化監控系統、自動駕駛車輛和其他嚴重依賴視覺資料的技術的效率。
應用:對永續性的日益關注推動邊緣人工智慧軟體在能源管理中的採用
企業使用存取管理解決方案來驗證、授權和審核對本機和雲端基礎的應用程式和 IT 系統的存取。邊緣人工智慧軟體在存取管理方面具有巨大的潛在應用,可以發現行為模式以識別潛在的安全風險。邊緣人工智慧對於自動駕駛汽車至關重要,因為它提供先進導航系統所需的即時資料處理、預測分析和機器學習功能。能源管理部門利用邊緣人工智慧解決方案根據即時資料最佳化能源消耗。邊緣人工智慧可預測能源需求並有效管理供應,從而降低成本和環境影響。邊緣人工智慧透過實現即時作物監測、資源最佳化和最大化作物產量,徹底改變了精密農業。遠端監控和預測性維護應用擴大採用邊緣人工智慧技術來預測設備故障並確定最佳維護計劃。邊緣人工智慧透過提供即時健康追蹤、用戶建議和資料安全,是改善智慧型穿戴裝置功能的關鍵。遙測使用感測器和其他設備來收集、傳輸和測量來自各種遠端來源的資料。邊緣人工智慧即時分析和解釋不同資料集的能力大大增強了遙測技術。視訊監控中的邊緣人工智慧可實現臉部辨識、運動偵測和行為分析等高級功能。
最終用途 政府和公共部門需要最佳的資料安全和隱私
在汽車產業,邊緣人工智慧軟體支援 ADAS(高級駕駛輔助系統)、預測性維護和資訊娛樂等功能。邊緣人工智慧軟體在能源和公共業務部門的能源消耗預測、電網最佳化和業務效率方面發揮關鍵作用。政府和公共部門對先進監控系統、資料安全和智慧公共服務的需求推動了對邊緣人工智慧軟體的需求。邊緣人工智慧將對醫療保健領域的遠端患者監護、醫學影像分析和預測分析產生重大影響。在製造領域,邊緣人工智慧軟體用於預測性維護、品質保證和即時設備監控。在通訊業,邊緣人工智慧對於網路最佳化、即時監控、詐欺偵測和客戶服務至關重要。
區域洞察
技術進步和不斷成長的用戶群推動了美洲(尤其是美國和加拿大)對邊緣人工智慧軟體的需求。這些國家在人工智慧研究、技術專利、資料中心和計算技術方面擁有大量投資。此外,物聯網和感測器技術在工業用例中的快速採用正在推動對邊緣人工智慧軟體的需求。憑藉嚴格的資料隱私法規,歐盟國家正在努力擴大邊緣人工智慧的使用,以減少資料傳輸的需求。歐洲國家也擁有強大的人工智慧專案和技術研究基礎設施,為邊緣人工智慧軟體的重大進步做出了貢獻。在歐盟,由人工智慧軟體支援的邊緣運算設備和技術正在迅速部署,以推進醫學研究。在亞太地區,中國、日本和印度由於其龐大的消費群和快速的數位轉型,在人工智慧軟體的採用方面處於領先地位。中國擁有政府支持的技術研究和智慧城市計劃項目。同時,日本正大力投資機器人技術以及人工智慧解決方案,展示了邊緣人工智慧軟體的廣泛適用性。由於其精通技術的人口和不斷發展的數位生態系統,印度的邊緣人工智慧軟體格局具有巨大潛力。
FPNV定位矩陣
FPNV定位矩陣對於評估邊緣AI軟體市場至關重要。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。最前線 (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,可以對邊緣人工智慧軟體市場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細分市場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:包括新產品發布、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:包括對未來技術、研發活動和突破性產品開發的智力見解。
1.邊緣AI軟體市場的市場規模與預測是多少?
2.在邊緣人工智慧軟體市場預測期內,我們應該考慮投資哪些產品和應用程式?
3.邊緣AI軟體市場的技術趨勢與法規結構是什麼?
4.邊緣AI軟體市場主要廠商的市場佔有率為何?
5. 進入邊緣AI軟體市場的合適形式和策略手段是什麼?
[193 Pages Report] The Edge AI Software Market size was estimated at USD 1.25 billion in 2023 and expected to reach USD 1.58 billion in 2024, at a CAGR 26.55% to reach USD 6.54 billion by 2030.
Edge AI refers to the deployment and utilization of AI in an edge computing environment, which allows complex computations to be done closer to where data is collected rather than at a centralized cloud computing facility or an offsite data center. Edge AI software allows machine learning algorithms to be run on a physical hardware device. Edge AI software is primarily employed in various sectors, including industrial automation, surveillance, robotics, and IoT devices. The need for real-time processing, with reduced latency and bandwidth consumption, has fueled the demand for edge AI software within these sectors, broadening the scope of the industry. The enhancement in cognitive computing capabilities, along with the surge in data generated from various smart devices, has created numerous potential opportunities for edge AI software. Difficulty of integration and handling of edge AI software and the need for a significant amount of resources to maintain edge AI software can deter new entrants in the field. Furthermore, data privacy and security issues and a lack of standardized protocols for inter-device communications have posed hurdles to the widespread adoption of edge AI software. However, manufacturers are constantly investing in R&D initiatives to improve the privacy protocols and data security of their software services. The most promising areas for innovation and research in edge AI software are attributed to sectors such as cybersecurity, automated Healthcare systems, and smart cities. Technological advancements such as 5G connectivity, quantum computing, and advancements in natural language processing (NLP) provide opportunities for future innovation.
KEY MARKET STATISTICS | |
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Base Year [2023] | USD 1.25 billion |
Estimated Year [2024] | USD 1.58 billion |
Forecast Year [2030] | USD 6.54 billion |
CAGR (%) | 26.55% |
Component: Research initiatives to support advancements in edge AI software solutions
Services in the context of edge AI software comprise consultation, integration, and support services that enhance the overall functioning, usability, and optimization of the edge AI software solutions. These services are aimed at helping businesses tailor AI implementations to their unique needs, thus driving efficiencies and business growth. Support and maintenance of edge AI software services include regular system updates, prompt troubleshooting, performance optimization, real-time threat anomaly detection, and continuous monitoring for proactive fault anticipation. Reliable performance is ensured by practicing meticulous system integration and testing routines. Training and consulting include technical training, consultative services for best practice approaches, and advisory services for strategic edge computation use. The solution segment revolves around the application of AI technologies at the edge of the network. This includes machine learning, deep learning, natural language processing, and computer vision. The edge AI platform is a comprehensive ecosystem that facilitates data collection, processing, analytics, and decision-making at the edge of the network. Software tools for edge AI include pre-built AI models, AI algorithms, algorithm training tools, analytics software, and application development tools.
Data source: Generation of sensor data due to growing utilization of sensor technologies in industries
Edge AI software utilizes biometric data in an effective manner in order to validate authentications and build more complex use cases. The biometric data typically managed by the software might include fingerprints, facial recognition, and iris patterns, among others. Mobile data forms a critical part of edge AI with real-time analytics, managed directly on mobile or IoT devices. Edge AI enables devices to process and interpret data locally, thereby enhancing performance and reducing both latency and the need for constant internet connection. Edge AI software's effective utilization of sensor data stems from IoT devices, industrial machines, smart home systems, and autonomous vehicles. Speech recognition, as an application of edge AI, holds tremendous value in hands-free device control, transcription services, and assistive technology. Video and image recognition capabilities support real-time video analytics, object detection, and facial recognition. Since edge AI processes the data locally, it minimizes bandwidth use and latency, thus optimizing the efficiency of surveillance systems, autonomous vehicles, and other technologies relying heavily on visual data.
Application: Growing sustainability concerns driving adoption of edge AI software in energy management
Access management solutions are used by organizations to authenticate, authorize, and audit access to on-premises and cloud-based applications and IT systems. Edge AI software finds substantial application in access management, where it uncovers patterns in behavior to identify potential security risks. AI at the edge is essential for autonomous vehicles as it offers real-time data processing, predictive analytics, and machine learning capabilities required for sophisticated navigation systems. The energy management segment utilizes edge AI solutions to optimize energy consumption based on real-time data. It aids in predicting energy needs and managing supply efficiently, thus saving costs and reducing environmental impact. Edge AI has transformed precision agriculture by enabling real-time crop monitoring, optimizing resources, and maximizing crop yield. Remote monitoring and predictive maintenance applications are increasingly embracing edge AI technology to predict equipment failures and determine optimal maintenance schedules. Edge AI has been key to improving the functionality of smart wearables by providing real-time health tracking, user recommendations, and data security. Telemetry allows the collection, transmission, and measurement of data from diverse remote sources using sensors and other devices. Telemetry has been greatly enhanced by edge AI's ability to analyze and interpret diverse data sets in real-time. Edge AI in video surveillance enables sophisticated functions such as facial recognition, motion detection, and behavioral analysis.
End-use: Need to ensure optimum data security and privacy in government & public Sector
In the automotive industry, edge AI software aids in functions such as advanced driver assistance systems (ADAS), predictive maintenance, and infotainment. Edge AI software plays an important role in energy consumption prediction, power grid optimization, and operational efficiency in the energy and utilities sector. The demand for edge AI software is driven by the need for sophisticated surveillance systems, data security, and intelligent public services in the government and public sector. Edge AI has a tremendous impact on remote patient monitoring, medical image analysis, and predictive analytics in healthcare. The manufacturing industry utilizes edge AI software for predictive maintenance, quality assurance, and real-time equipment monitoring. Edge AI is essential in the telecom industry for network optimization, real-time monitoring, fraud detection, and customer service.
Regional Insights
The demand for edge AI Software in the Americas, notably in the United States and Canada, is fueled by technological advancements and a growing user base. These countries are characterized by high investment in AI research, technological patents, data centers, and computing technologies. Furthermore, the rapid adoption of IoT and sensor technologies in industrial use cases has driven the demand for edge AI software. EU countries, driven by stringent data privacy regulations, are striving to increase the use of edge AI, lessening the need for data transport. European nations are also characterized by robust research infrastructure for AI programs and technologies, contributing to significant advancements in edge AI software. In the EU, edge computing devices and technologies equipped with AI software are rapidly being deployed to advance healthcare research. In the APAC region, China, Japan, and India drive the adoption of edge AI software due to their vast consumer base and rapid digital transformation. China has government-backed programs for technological research and smart city initiatives. Meanwhile, Japan is investing heavily in robot technology along with AI-infused solutions, thereby demonstrating a broad scope for edge AI software. India's landscape for edge AI software holds massive potential due to its tech-savvy demographics and growing digital ecosystem.
FPNV Positioning Matrix
The FPNV Positioning Matrix is pivotal in evaluating the Edge AI Software 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 Edge AI Software 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 Edge AI Software Market, highlighting leading vendors and their innovative profiles. These include Adapdix, Inc., Alef Edge, Inc., Amazon Web Services, Inc., Anagog Ltd., Atos SE, Azion Technologies, Inc., Blaize, byteLAKE s.c., ClearBlade, Inc., Ekinops S.A., Eurotech S.p.A., Google LLC by Alphabet, Inc., Gorilla Technology Group Inc., Gorilla Technology Inc., Hailo Technologies Ltd., Imagimob AB, Infineon Technologies AG, Intel Corporation, International Business Machines Corporation, Johnson Controls International PLC, Kinara Inc., Kneron, Inc., Mavenir Systems, Inc., Microsoft Corporation, Numurus LLC, Nutanix, Inc., NVIDIA Corporation, Synaptics Incorporated, T-DAB.AI Ltd., Tact.ai Technologies, Inc., Tata Elxsi Limited, TIBCO Software Inc., Veea Inc., VMWare, Inc., and ZEDEDA, Inc..
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 Edge AI Software Market?
2. Which products, segments, applications, and areas should one consider investing in over the forecast period in the Edge AI Software Market?
3. What are the technology trends and regulatory frameworks in the Edge AI Software Market?
4. What is the market share of the leading vendors in the Edge AI Software Market?
5. Which modes and strategic moves are suitable for entering the Edge AI Software Market?