Dataset opportunity
Srsequipment — 维护日志数据集机会
Srsequipment 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
72.9
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
收购
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 = 2025 年为 136.5 亿美元，复合年增长率为 24.30%。
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
工业
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
部分
Legal
混合所有权 — 清晰的许可
Buyer persona
工业人工智能与维护优化供应商
Srsequipment 持有一个宝贵的时间序列数据集，其中包含其在废物管理领域运营的机械的历史维护日志、物联网数据和通用工业数据。这些细致的真实运营数据特别适合开发和训练预测性维护算法，以预测设备故障、优化服务计划并减少昂贵的计划外停机时间。
全球预测性维护市场在 2025 年的估值为136.5 亿美元，预计将以 24.30% 的复合年增长率增长。虽然访问需要应对数据共享所有权（与最终用户）、与 Komptech Connect 生态系统集成以及从服务记录中提取数据等复杂性，但该数据在如此高增长的市场中的稀缺性和战略价值证明了付出的努力是值得的，为任何人工智能买家提供了独特的竞争优势。⚠ 注意（有价值的数据，可协商的访问权限）：数据所有权可能与操作机械的最终用户（废物管理公司）共享；遥测数据可能集成在 Komptech Connect 生态系统中；访问历史吞吐量数据需要从调试和服务记录中提取。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同证明了 SRS Equipment 持有一个专有数据集，该数据集结合了工业机械的物联网遥测和相应的服务记录。这正是工业人工智能供应商寻求构建和训练高价值预测性维护模型所需的数据。访问这种独特的传感器数据和地面真实维护日志的组合，为利用快速增长的、价值数十亿美元的工业优化市场提供了直接途径。
See dimension details ↓- Dataset Specificity90
主导的“维护日志”，行业为工业，3 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 Rarity82
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 Value84
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 Demand90
人工智能买家需求极高，这得益于一个快速扩张的市场，预计将以 24.30% 的复合年增长率增长，因为工业部门越来越多地采用数据驱动的维护解决方案。
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility50
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 License58
所有权=混合，许可=清晰
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 — 这家加拿大回收设备服务提供商非常合适，因为它拥有一个运营业务，可以生成有价值的维护数据，而这些数据似乎并未作为产品出售。问题：公司规模未明确说明，但其作为两个先前实体的合并历史以及其加拿大全国范围的运营表明它是一家中小型企业，而不是一家大型企业。
- Deep Qualification80
⚠ 需要审查 — 目标是重型回收机械的服务提供商，数据是可能的副产品。然而，数据归制造商（Komptech）所有，制造商明确保留将其披露给第三方的权利，这使得与目标直接协商独家权利不太可能。[许可受限]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Industrial data
这些证据表明了持有者工业运营的规模，证实了其数据源自与企业级人工智能应用相关的大型真实系统。
IoT / sensor data
这些证据证实了持有者可以访问机器遥测和性能数据，提供了预测性维护模型的主要输入——连续的时间序列传感器数据。
Maintenance logs
这些证据证明了持有者生成并控制内部服务记录，提供了训练和验证预测性维护算法所需的关于维修和组件故障的基本地面真实数据。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Srsequipment Maintenance Logs — a Moderate maintenance logs dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market = $13.65B in 2025, CAGR 24.30% (source: Fortune Business Insights). Investment score 72.9/100 (confidence 0.49). Recommended action: Acquire.
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