Dataset opportunity
Adamaswind — 工业运营数据集机会
Adamaswind 持有的中等规模工业运营数据集，可用于工业监控和预测。
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
58%
Action
合作（集团层面）
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
全球风力涡轮机预测性维护人工智能市场在 2025 年的价值为 28 亿美元，预计到 2034 年将达到 104 亿美元（复合年增长率为 14.6%）。[1]
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-16
Le fondateur d’Arverne va s’associer à RGreen Invest pour renforcer son contrôle
greenunivers.com ↗ - 📰press2026-06-16
Verogy Starts Work on Solar Facilities at Municipal Landfills
powermag.com ↗ - 📰press2026-06-16
In wildfire country, every home should be a microgrid
utilitydive.com ↗ - 📰press2026-06-16
Comment Poweend veut valoriser ses petites éoliennes en autoconsommation
greenunivers.com ↗ - 📰press2026-06-16
Engie crée sa task force pour les centres de données
greenunivers.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.
Concrete evidence this company actively cares about data — why it's ripe for the deal room.
Profile
Dataset profile
Type
工业运营数据集
Modality
时间序列
Sector
工业
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — 许可权待明确
Buyer persona
工业人工智能集成商
Adamaswind 持有一个宝贵的工业运营数据集，该数据集由其风力发电场资产的专有时间序列数据组成。这包括细粒度的 `event_streams`（事件流）、`iot_data`（物联网数据）和详细的 `maintenance_logs`（维护日志），为开发和验证复杂的工业监控人工智能模型提供了全面、真实的基石。该数据的结构非常适合预测组件故障、优化维护计划和提高运营效率。
该数据的市场潜力巨大，仅全球风力涡轮机预测性维护人工智能市场在 2025 年的价值就达到28 亿美元，并预计到 2034 年将增长到 104 亿美元，复合年增长率（CAGR）为14.6%。[1] 尽管存在数据所有权与资产所有者共享以及潜在的 OEM 限制等访问复杂性，但该运营数据的稀缺性和深度使其克服这些许可障碍成为一项有价值的投资，为寻求在可再生能源领域获得独特竞争优势的人工智能买家提供了机会。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据所有权可能与风力发电场资产所有者（客户）共享；许可可能需要 Galetech Group 的批准，因为存在合资企业；运营数据通过第三方涡轮机硬件（例如 Vestas）生成，可能涉及 OEM 限制 · 公司：Galetech Group 的子公司。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
证据证实 Adamaswind 拥有专有数据集，该数据集结合了实时风力涡轮机运营数据和相应的维护日志。这种独特的时间序列数据集合正是工业人工智能集成商训练和验证高价值预测性维护模型所需的。随着风力涡轮机预测性维护人工智能市场预计到 2034 年将达到 104 亿美元，该数据集为开发下一代工业监控解决方案和抢占市场份额提供了关键资产。
See dimension details ↓- Dataset Specificity100
主导的'工业数据'，行业为工业，4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 Rarity94
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume64
5个证据命中
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 Value94
适用于工业监控
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand92
制造业人工智能市场是工业运营数据监控的直接消费者，预计到 2030 年将以惊人的 42.1% 的复合年增长率增长至 341 亿美元，这表明需求极高且正在加速。
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility28
受限/未知
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility15
中等难度，Galetech Group 的子公司
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength77
4种证据类型，5次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License36
所有权=混合，许可=权利不明确
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence50
Galetech Group 的子公司
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation56
2个数据需求信号（2种类型）
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus70
盈余=中等，5个近期外部信号 — 已货币化的专有数据之外的数据
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 Audit67
⚠ 审查 — Adamas Wind 的核心业务是作为服务出售智能和分析以优化风力涡轮机运营，这使其成为市场上的参与者，而不是休眠数据的持有者，因此不适合。问题：该公司的核心产品不是物理运营，而是从数据中提取的智能；该网站明确推广了一个使用人工智能提供'宝贵见解和可操作情报'作为产品的'先进状态监控系统'；该公司的价值
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Industrial data
Adamaswind 利用其内部分析从涡轮机数据中生成见解，提供经过处理的数据集，可以加速性能优化模型的开发。
Event streams
该公司确认直接从风力涡轮机收集实时数据流，提供训练异常检测算法所必需的原始时间序列输入。
Maintenance logs
该数据集包括详细说明特定组件更换的结构化维护日志，提供了训练监督式预测故障模型所需的关键真实标签。
IoT / sensor data
通过其 24/7 运营控制中心，该公司汇集了连续的物联网数据，表明拥有一个集中且可扩展的数据收集基础设施，这对于构建健壮的、覆盖整个机队的工业人工智能解决方案至关重要。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Time Series, JSON
License
One-time license for AI model development and internal operational use. Restrictions may apply to 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 proprietary, real-time time-series dataset offers high value for industrial monitoring and predictive maintenance AI, particularly within the rapidly growing wind turbine sector. The significant market demand, driven by a projected CAGR of 14.6% for predictive maintenance AI, justifies a premium valuation.
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
Adamaswind Industrial Operations — a Moderate industrial operations dataset (Time Series modality) in the industrial domain. Primary AI use-case: Industrial Monitoring. Market signal: Global Wind Turbine Predictive Maintenance AI market valued at $2.8 billion in 2025, projected to reach $10.4 billion by 2034 (CAGR 14.6%). [1]. Investment score 73.1/100 (confidence 0.58). Recommended action: Partnership (group-level).
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