Dataset opportunity
Ekkosense — 工业传感器数据集机会
Ekkosense 持有的大型工业传感器数据集，可用于预测性维护和异常检测。
Score
73.1
Score (0–100) blends weighted dimensions — dataset rarity, training value, buyer demand, evidence strength and right-to-license. 70+ is deal-ready. See the scored dimensions below for the breakdown.Confidence
56%
Action
获取
The recommended deal structure for this dataset: Acquire (full buyout), License (paid usage rights), Data Sharing Agreement (controlled access, no transfer of ownership), Partnership (co-development) or Annotation Program (labeling). Chosen from data ownership, licensing complexity and accessibility.Market
全球预测性维护市场 = 2024年12.3亿美元，复合年增长率29.7% (2024-2033)。数据中心预测性维护市场 = 2024年1.8亿美元，复合年增长率16.7% (2024-2033)。
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-08
Can stadiums be energy efficient? USGBC map shows that many of them are
utilitydive.com ↗ - 📰press2026-06-08
Behind-the-meter data center gas plants will raise US energy bills
utilitydive.com ↗ - 📰press2026-06-08
Rising load growth reshapes cooperative portfolios and strategy
utilitydive.com ↗ - 📰press2026-06-08
The benefits of a unified billing, payment, communications platform
utilitydive.com ↗ - 📰press2026-06-08
How live conversations can close the gap between awareness and enrollment for load flexibility
utilitydive.com ↗
Lineage
How this lead was derived
The signal-first chain, end to end: recent external signals → qualified niche → resolved data-holder → site verification → scored opportunity. Every lead is explainable.
Profile
Dataset profile
Type
工业传感器数据集
Modality
时间序列
Sector
工业
Volume
大
Freshness
实时
Rarity
高（专有）
Accessibility
部分
Legal
公司所有 — 可授权
Buyer persona
工业AI和维护优化供应商
Ekkosense 持有一个宝贵的工业传感器数据集，其模态为时间序列，专门从客户数据中心收集。这些数据主要包含工业/机器数据，如热量、功率和湿度读数，非常适合预测性维护应用，能够实现持续监控、异常检测和潜在设备故障的预测。
预测性维护市场展现出巨大的高商业价值和来自AI买家的需求，全球市场在2024年价值123亿美元，并预计以29.7%的复合年增长率增长至2033年的688亿美元。仅数据中心预测性维护市场在2024年就价值18亿美元，预计复合年增长率为16.7%，到2033年将达到72亿美元。这一显著的市场增长得益于预测性维护能够将维护成本降低30-40%，并将计划外停机时间减少20-50%，尽管从客户数据中心和云存储访问存在复杂性，但这些数据仍然极具价值。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据从客户数据中心收集；数据主要是工业/机器数据（热量、功率、湿度），而非个人数据；SaaS交付模式，数据存储在云端；可与第三方设备集成。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Ekkosense 持有一个高度专有的工业传感器数据集，包含来自100,000多个监控机架的超过500亿个软件数据点，这对于预测性维护应用来说具有非凡的价值。这些通过独特的物联网无线热传感器收集的广泛的时间序列数据，用于数据中心优化，直接满足了工业人工智能与维护优化供应商的关键需求。随着全球预测性维护市场迅速扩展至数十亿美元，该数据集为开发提高效率和降低运营成本的先进解决方案提供了基础性的实时资源。其完整的API集成确保了无缝采用。
See dimension details ↓- Dataset Specificity78
主导的'物联网数据'，工业领域，2种特定类型
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity70
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume74
4个证据命中，明确提及数据量
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness82
实时/流式传输
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value74
适用于预测性维护
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand92
制造业中的人工智能市场，该市场严重依赖工业传感器数据进行预测性维护等应用，预计从2025年到2030年的复合年增长率（CAGR）为46.5%，将达到478.8亿美元
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility62
开放/API访问
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility4
中等难度，独立
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength74
4种证据类型，4次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License92
所有权=已拥有，许可=干净
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence90
独立
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation22
0个数据需求信号（0种类型）
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
剩余=高，5个近期外部信号 — 专有数据超出已货币化的部分
Volume and value of proprietary data this company holds BEYOND what it already monetises — the dormant surplus we can unlock. A company can sell some insights AND still sit on a far larger dormant asset. - ICP Audit42
⚠ 审查 — Ekkosense 的核心业务是销售人工智能驱动的数据中心优化软件和分析解决方案，这意味着他们已经通过数据货币化了智能，因此不适合寻求休眠数据的数据市场目标。问题：Ekkosense 的核心业务是提供人工智能驱动的数据中心优化软件和分析，这属于“销售智能（人工智能软件，；Ekkosense 传感器收集的数据是其核心业务的组成部分。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
该证据证实 Ekkosense 拥有专门用于数据中心优化的物联网无线热传感器，提供对该高增长领域预测性维护至关重要的实时热管理数据。
Data-volume signal
这突显了来自100,000多个监控机架的超过500亿个软件数据点的大量专有集合，为工业环境中的强大人工智能模型训练提供了无与伦比的规模。
Industrial data
这证实了 Ekkosense 的专有来源，可提供准确、低成本的无线传感器数据，包括热量、湿度和冷却单元性能指标，这对于全面的工业预测性维护至关重要。
API access
这表明 Ekkosense 通过完整的 API 集成致力于互操作性，确保其宝贵的数据和平台能够被 AI 买家无缝访问和利用。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Time Series
License
One-time license for predictive maintenance use cases, with potential restrictions on redistribution.
Personal data
No PII
Indicative estimate, derived from public signals — not a quote, not contractual, and not agreed with the company. Is this your company? Correct it.
This dataset's value is driven by its high rarity, proprietary nature, and massive scale (50B+ data points) from unique IoT sensors, directly feeding the high-demand, high-growth predictive maintenance market. The significant market size and CAGR for predictive maintenance, particularly in data centers, indicate strong buyer interest.
Detailed schema & sample available on access request.
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This listing was generated automatically from public signals. It is not verified, and we are not affiliated with this company.
Coverage
Scanned sources
Deliverable
Premium dataset report
Ekkosense Industrial Sensor — a Large industrial sensor dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market = USD 12.3 billion in 2024, CAGR 29.7% (2024-2033). Data Center Predictive Maintenance market = USD 1.8 billion in 2024, CAGR 16.7% (2024-2033).. Investment score 73.1/100 (confidence 0.56). Recommended action: Acquire.
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