Dataset opportunity
Konux — 移动遥测数据集机会
Konux 持有的中等规模移动遥测数据集，可用于预测性维护和异常检测。
Score
48
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
51%
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)
全球数字铁路市场 = 2023 年为 645 亿美元，复合年增长率为 9.4%（来源：Global Market Insights, Inc.）。[20]
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.
- 🧑💻Hiring a data role
招聘高级数据科学家（深度学习）
source ↗
Profile
Dataset profile
Type
移动遥测数据集
Modality
时间序列
Sector
移动
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
Konux 提供专有的时间序列数据集，该数据集由其在关键铁路基础设施上的IIoT 传感器生成。这些 `industrial_data`，包括来自铁路道岔的 `event_streams` 和原始 `iot_data`，提供了资产健康的直接、高保真视图，对于开发和验证预测性维护算法具有极高的价值。
该数据面向全球数字铁路市场，该市场在 2023 年的价值为645 亿美元，预计将以9.4% 的复合年增长率增长。[20] 尽管由于其与关键国家基础设施的联系以及与德国铁路等客户的共同所有权而存在访问复杂性，但该数据的稀缺性和已证实的运营相关性使其成为针对这一高增长市场的 AI 买家的优质资产。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据通过专有的 IIoT 传感器生成，但涉及关键国家基础设施（铁路）。；所有权可能与德国铁路等主要客户共享或受到合同限制；数据访问需要遵守严格的铁路安全和安保规定。· 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 Konux 拥有稀有的专有时间序列数据集，该数据集捕获了真实的铁路运营情况，包括详细的列车轨迹和物联网传感器读数。这些数据对于开发预测性维护模型以提高效率和安全性的工业人工智能供应商来说是关键资产。在预计将超过 645 亿美元的数字铁路市场中，该数据集为下一代维护优化解决方案的培训和验证提供了显著的竞争优势。
See dimension details ↓- Dataset Specificity90
主导的 'iot_data'，移动行业，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 Volume58
4 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 买家需求异常高，这得益于数字铁路市场对预测性维护解决方案的迫切需求，该市场正以 9.4% 的复合年增长率扩张。[20]
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 Feasibility14
高难度，独立
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength65
3 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 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 Orientation39
1 个数据胃口信号（1 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 — 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 Audit67
⚠ 审查 — Konux 的核心业务是销售用于预测性维护的 AI 驱动的软件即服务 (SaaS) 产品，而不是休眠数据，因此不适合。问题：该公司的整个业务模式都基于销售智能和 AI 软件，这属于明确的排除标准；他们的主要收入来源是其预测分析平台的 SaaS 订阅。[3, 7]；他们将自己定位为销售端到端解决方案的 AI/IoT 公司，而不是副产品数据的持有者。[1, 2, 5]；产品是 AI 驱动的洞察、预测和分析，这也是像德国铁路这样的客户付费的内容。[1, 2]
- Deep Qualification90
⚠ 需要审查 — Konux 的核心业务是销售用于铁路预测性维护的 AI 驱动的 SaaS 解决方案，而不是原始数据。底层时间序列遥测数据非常合理，但其所有权复杂，可能在 Konux 及其客户（如德国铁路）之间混合，并且由于其与关键国家基础设施的联系而受到使用限制。[将数据/情报作为核心产品出售；业务模式 = 数据销售商；许可受限]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
该数据集包含由可配置的工业级物联网传感器生成时间序列数据，为 AI 供应商提供了对组件磨损建模所需的粒度、可操作的输入。
Event streams
该数据集包括广泛的列车轨迹事件流，这些轨迹跨越不同的地理区域和季节，对于构建能够考虑真实世界运营变异性的稳健模型至关重要。
Industrial data
这些工业数据的集合代表了多年积累的铁路遥测数据，为训练和验证高精度预测模型以提高网络可靠性提供了丰富的历史基线。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Time Series, Event Streams, IoT Data
License
One-time license for developing and validating predictive maintenance algorithms. Usage may be restricted to specific applications and geographies.
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, high-fidelity time-series IIoT data from critical railway infrastructure is exceptionally valuable for predictive maintenance in the rapidly growing digital railway market. Its rarity, real-time freshness, and direct insight into asset health drive significant demand for industrial AI applications.
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
Konux Mobility Telemetry — a Large mobility telemetry dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Railway Predictive Maintenance Market was valued at $12.4 billion in 2025, projected to reach $28.9 billion by 2034, CAGR 9.8% (source: Dataintelo). [1]. Investment score 48.0/100 (confidence 0.51). Recommended action: Acquire.
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