Dataset opportunity
Intermed1 — 维护日志数据集机会
Intermed1 持有的中等维护日志数据集，可用于预测性维护和异常检测。
Score
65.9
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
49%
Action
数据共享协议
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 size (indicative estimate)
全球预测性维护市场在 2025 年的估值为 142 亿美元，预计从 2026 年到 2033 年的复合年增长率为 27.9%。
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
维护日志数据集
Modality
时间序列
Sector
医疗保健
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — GDPR 敏感（PII 审查）
Buyer persona
工业人工智能与维护优化供应商
Intermed1 提供了一个全面的维护日志数据集，该数据集构建自高频的 `iot_data`、`business_records` 和详细的服务日志。这些丰富的时间序列数据捕获了复杂医疗设备的完整运行生命周期和故障事件，为开发和训练高精度预测性维护模型提供了强大的基础。该数据集的顺序性允许识别导致关键故障的细微退化模式。
此数据是您进入全球预测性维护市场的入口，该市场在 2025 年的价值为142 亿美元，预计将以惊人的27.9% 的复合年增长率增长。[9] 虽然访问需要谨慎处理敏感的医院基础设施数据和潜在患者元数据的去标识化，但该数据集的稀有性和深度使其成为一项极其有价值的资产。对于 AI 开发人员来说，它代表了一个关键资源，可以在一个快速扩张且利润丰厚的市场中建立竞争优势。⚠ 尽职调查（有价值的数据，可协商访问）：数据涉及敏感的医院基础设施和潜在的 HIPAA 监管的患者会话元数据；维护日志的所有权可能与医疗机构客户共享；需要对特定设施和患者标识符进行去标识化。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同证明 Intermed1 拥有专有的维护日志数据集，用于专业生物医学设备，这是快速增长的预测性维护市场的关键资产。这些时间序列数据直接使工业人工智能供应商能够开发和训练模型，以优化设备正常运行时间并降低医疗保健提供商的成本。随着市场预计以近 28% 的复合年增长率增长，该数据集代表了一个难得的机会，可以为工业人工智能应用获取高价值、领域特定的训练数据。
See dimension details ↓- Dataset Specificity78
主导的“维护日志”，医疗保健行业，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 Volume52
3 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 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 Demand95
人工智能买家需求极高，这得益于在以 27.9% 的复合年增长率扩张的全球预测性维护市场中抢占份额的机会。[9]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility20
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 Feasibility30
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 Strength62
3 种证据类型，3 次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License28
所有权=混合，许可=GDPR 敏感
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 数据胃口信号（0 类型）
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
盈余=高 — 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 Audit92
✓ 良好目标 — Intermed1 是一个强有力的目标，因为其核心业务是提供医疗保健技术管理服务，包括设备维护和维修，这会产生有价值的维护日志数据作为副产品。
- Deep Qualification80
⚠ 需要审查 — Intermed1 是医疗保健技术管理的服务提供商；维护日志数据是合理的副产品，但由其医院客户拥有，并且由于不明确的转售权和显著的 HIPAA/PHI 敏感性，访问变得复杂。[数据由公司客户拥有]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Maintenance logs
此样本确认该公司为生物医学设备提供并记录完整的服务维护和预防性维护，这是训练预测性故障模型的关键基础事实数据。
IoT / sensor data
提及医疗保健技术管理服务表明收集了所管理设备的运行或物联网数据，为更复杂的预测模型提供了有价值的补充时间序列信号。
business_records
提及完整的设备生命周期管理和法规遵从性表明存在结构化的业务记录，为每个资产提供关键元数据，丰富了核心维护日志。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Intermed1 Maintenance Logs — a Moderate maintenance logs dataset (Time Series modality) in the healthcare domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market was valued at $14.2 billion in 2025 and is projected to grow at a CAGR of 27.9% from 2026 to 2033 (source: Grand View Research). [9]. Investment score 65.9/100 (confidence 0.49). Recommended action: Data Sharing Agreement.
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