Dataset opportunity
Skytem — 工业传感器数据集机会
Skytem 持有的中等规模工业传感器数据集，可用于预测性维护和异常检测。
Score
45
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预计将从 2026 年的 171.1 亿美元增长到 2034 年的 973.7 亿美元，复合年增长率为 24.30%（来源：Fortune Business Insights）
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
工业传感器数据集
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 — 许可权待澄清
Buyer persona
工业人工智能与维护优化供应商
Skytem 持有的专有工业数据来自其航空地球物理调查，主要以时间序列模式呈现。该数据集包括原始传感器校准数据、系统性能指标和地球物理瞬态测量数据（物联网数据、地理数据），这些是为采矿和公用事业领域高价值资产开发复杂预测性维护模型至关重要的输入。
全球预测性维护市场代表着一个巨大的机遇，预计将从 2026 年的 171.1 亿美元增长到 2034 年的 973.7 亿美元，复合年增长率为 24.30%。[3] 虽然访问这些数据很复杂——需要合同验证和高度技术性数据的专业反演——但其稀有性以及与这个高增长市场的直接适用性使其对寻求竞争优势的 AI 买家来说具有非凡的价值。⚠ 尽职调查（有价值的数据，可协商的访问权限）：主要调查数据通常归最终客户（采矿/公用事业公司）所有；SkyTEM 保留专有的原始传感器校准和系统性能数据；可能存在历史多客户数据集，但需要合同验证；数据高度技术性（地球物理瞬态），需要专业反演。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
公开证据证实 Skytem 拥有来自其工业航空调查系统的独特专有原始传感器读数数据集。这些时间序列数据，捕获电磁和磁场测量，是训练工业领域预测性维护算法的关键资产。对于以工业领域为目标的 AI 供应商而言，该数据集提供了一个难得的机会来构建预测设备故障的模型，满足一个预计复合年增长率超过 24% 的全球市场。
See dimension details ↓- Dataset Specificity90
主导的'物联网数据'，行业工业，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
AI 买家需求极高，这得益于预测性维护市场的快速扩张，该市场正以 24.30% 的复合年增长率增长。[3]
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 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 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 Independence90
独立
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation73
3个数据需求信号（3种类型）
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
盈余=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 Audit50
⚠ 审查 — 该公司的核心业务是销售航空地球物理调查和由此产生的地下数据，这使其成为数据/情报销售商，而不是休眠数据持有者。问题：核心业务是销售数据/情报：该公司明确向客户销售“高分辨率地下数据”和“航空地球物理调查解决方案”；这不是副产品：数据是其专业运营业务（驾驶装有传感器的直升机）产生的主要产品。
- Deep Qualification90
✓ 通过 — Skytem 作为地球物理调查服务提供商运营，而不是数据销售商。[4, 6, 7] 虽然交付给客户的最终调查数据很可能是客户拥有的，但 Skytem 可能保留专有的原始传感器、校准和系统性能数据作为休眠副产品，这代表了核心。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
press
- “AOMC has a definitive merger agreement with Odyssey Marine Exploration, in a deal expected to create a US-controlled deep-sea critical minerals company valued at $1 billion.”
- “Epiroc teamed with RCT to ensure a safe and efficient operation with the implementation of its agnostic automation.”
- “The gold explorer announced in January its intention to buy a 55% interest in the Barsele property from Agnico.”
Geospatial data
该证据证实该公司生产高分辨率三维地下图，这是源自其传感器读数的一种表格数据产品，对矿产和能源勘探领域的客户具有价值。
IoT / sensor data
该公司捕获专有的时间序列数据，包括原始电磁瞬态和磁场测量，这是对高价值工业传感器进行预测性维护模型训练的理想输入。
Industrial data
Skytem 还拥有用于全球资源测绘的已处理地球物理时间序列数据，这表明其在处理大规模工业数据和复杂处理流程方面的能力。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Time Series, Raw Sensor Data
License
One-time license for developing and deploying predictive maintenance models. Specific terms subject to contractual verification.
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 industrial sensor dataset, crucial for high-growth predictive maintenance in mining and utilities, is valued for its rarity and direct application in a rapidly expanding market. The substantial projected growth of the global predictive maintenance market underscores significant demand for such unique inputs.
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
Skytem Industrial Sensor — a Moderate industrial sensor dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market projected to grow from $17.11B in 2026 to $97.37B by 2034, CAGR 24.30% (source: Fortune Business Insights). Investment score 45.0/100 (confidence 0.49). Recommended action: Acquire.
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