Dataset opportunity
Dukosi — 工业传感器数据集机会
Dukosi 持有的大型工业传感器数据集，可用于预测性维护和异常检测。
Score
81.2
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
74%
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
$$$ — 高AI买家需求
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-04
Surge Battery raises $21M for Nevada lithium project
mining.com ↗ - 📰press2026-06-03
USA Rare Earth to invest $1.2B in South Carolina magnet factory
manufacturingdive.com ↗ - 📰press2026-06-03
DTE Energy partners with LG to deploy 6 GWh of battery storage
utilitydive.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.
- 📣Press / announcement
Dukosi 将电池单元级数据跟踪与无线通信相结合，以满足电池护照要求。
source ↗
Profile
Dataset profile
Type
工业传感器数据集
Modality
时间序列
Sector
工业
Volume
大
Freshness
实时
Rarity
中等
Accessibility
开放 / API
Legal
公司所有 — 可干净授权
Buyer persona
工业AI和维护优化供应商
公共网络信号表明 Dukosi（工业领域）拥有一个工业传感器数据集（时间序列）。通过 api、data_catalog、developer_portal、event_streams、industrial_data、iot_data 等5个来源的证据检测到。主要证据：iot_data。⚠ 尽职调查（有价值的数据，可协商访问）：被 KCK Group 收购，这可能会增加公司审批的层级；数据由集成到客户电池系统中的硬件生成，需要客户协作才能完全访问；数据技术性强，专门针对电池性能和生命周期。· 公司：被 KCK Group 收购。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Dukosi 明确拥有一个丰富、高保真的工业传感器数据集，其特点是电池单元级时间序列数据和全面的生命周期溯源。这包括通过其独特的“电池护照”系统从“第一天”起持续记录的精确电压和温度测量值，为每个电池单元提供了深入的历史记录。这种细粒度、长期的数据受到寻求为关键电池应用开发先进预测性维护解决方案的工业AI和维护优化供应商的高度需求，在快速电气化的市场中提供了显著的竞争优势。
See dimension details ↓- Dataset Specificity90
主要为“iot_data”，工业领域，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 Rarity58
专有领域数据（开放会降低稀有度）
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume82
8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
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 Demand95
严重依赖工业传感器数据集的AI驱动预测性维护市场预计将以 39.5% 的复合年增长率增长，到 2032 年达到 19.27 亿美元，这表明对此类数据的买家需求非常高且增长迅速。
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility90
开放/API访问
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility69
中等难度，被 KCK Group 收购
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength100
6种证据类型，8个命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License92
所有权=自有，许可=干净
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence45
被 KCK Group 收购
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation39
1个数据需求信号（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，3个近期外部信号 — 超出已货币化范围的专有数据
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 Audit75
⚠ 审核 — Dukosi 的核心业务是销售提供单元级数据和智能的电池监控系统，这属于 d-nvest 目标市场的排除标准。问题：Dukosi 的核心业务是开发和销售电池监控系统及半导体解决方案，通过 API 和分析提供数据和智能；Dukosi 系统生成的数据并非休眠数据，而是其产品和价值主张的组成部分。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Developer portal
此证据表明 Dukosi 提供了一个开发者门户，其中包含用于电池设计和BMS集成的资源和评估平台，这表明他们致力于为潜在的AI买家实现外部创新和数据交互。
API access
这证实了 DK-NFLNK 系统存在一个强大的 API 和库，便于程序化访问电池监控器数据并与BMS主机系统集成，这对于AI平台自动摄取数据至关重要。
IoT / sensor data
这直接证实了从其电池监控器收集准确、同步的电池单元测量值作为时间序列数据，为预测性维护模型提供了关键的基础传感器读数。
Industrial data
这明确了每个电池单元收集的高精度电压和温度测量值，突出了可用工业传感器数据的质量和粒度，这对于准确的电池健康预测至关重要。
Event streams
此证据表明在电池单元级进行持续的24/7数据监控和事件记录，这表明时间序列数据持续流动，对于工业应用中的实时洞察和异常检测至关重要。
Data catalog / marketplace
这揭示了“电池护照”系统，该系统提供静态元数据和动态参数（如温度和电压）的芯片级终身存储，为每个单独的电池单元创建了全面的数据溯源，对于长期AI模型训练具有不可估量的价值。
Marketplace
Dataset details
Geographic coverage
Global
Time range
2019-present
Update frequency
Real-time
Delivery
API
Formats
Time Series
License
One-time license for predictive maintenance and analytics, subject to corporate approval and customer collaboration.
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 dataset's value is driven by its high-fidelity, long-term industrial sensor time-series data, crucial for predictive maintenance in the battery sector. High AI buyer demand and the unique 'Cell Passport' lineage support 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
Dukosi Industrial Sensor — a Large industrial sensor dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: $$$ — high AI buyer demand. Investment score 81.2/100 (confidence 0.74). Recommended action: Partnership (group-level).
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