Dataset opportunity
Voltfang — 工业传感器数据集机会
Voltfang 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
75.2
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
56%
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 142 亿美元，复合年增长率为 27.9%（来源：Grand View Research）
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.
- 📦Data product
智能能源管理系统 (EMS) 用于实时优化
source ↗
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 — 清晰可授权 · PII/受监管
Buyer persona
工业人工智能与维护优化供应商
Voltfang 持有一个丰富的时间序列数据集，该数据集由其部署的能源存储系统中的 `industrial_data`、`iot_data` 和 `geo_data` 组成。这些精细的传感器信息捕获了真实的运行性能和能源消耗模式，使其可以直接应用于训练复杂的预测性维护模型，以预测组件故障并优化维护计划。
预测性维护的全球市场规模巨大，2025 年市场价值为142 亿美元，预计将以27.9% 的复合年增长率增长。[1] 这种高增长表明了对能够减少运营停机时间和成本的数据的巨大需求。虽然由于客户现场数据生成和专有电池退化模型需要进行协商才能访问，但此工业数据的稀有性和直接适用性使其成为能源和制造领域任何人工智能买家的核心资产。⚠ 尽职调查（有价值的数据，可协商访问）：数据部分由客户现场安装的硬件生成；能源消耗模式的所有权可能与商业客户共享；专有电池退化模型是核心知识产权资产 · 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 Voltfang 拥有一个专有的、高稀有性的时间序列传感器数据集，来自其工业能源存储系统。该数据详细介绍了其翻新电动汽车电池的真实性能和寿命，对于人工智能供应商来说是一项独特而有价值的资产。在预计到 2025 年将达到 142 亿美元的预测性维护市场中，该数据集直接支持开发复杂的预测性维护和性能优化模型，为寻求提高资产可靠性和效率的工业人工智能买家提供了独特的竞争优势。
See dimension details ↓- Dataset Specificity100
主导的 'iot_data'，工业部门，4 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 Rarity94
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 Value94
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 Demand92
人工智能买家需求极高，这得益于预测性维护市场的快速增长，该市场正以 27.9% 的复合年增长率扩张。[1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility16
PII/受监管
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility0
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 Strength74
4 种证据类型，4 个命中
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，授权=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 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，4 个近期外部信号 — 超出已货币化的专有数据
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. - Deep Qualification80
✓ 通过 — Voltfang 是一家硬件和服务提供商，拥有其能源管理系统提供的宝贵工业传感器数据，但所有权可能与客户共享，这使得数据访问成为一个重大的谈判障碍。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
press
- “<figure><div><img src="https://imgproxy.divecdn.com/kyng3yXHJb0vSHY0pBqIm3WG9xydkNnMKa0JKytLR7Y/g:nowe:0:0/c:3000:1694/rs:fill:1600:900:1/Z3M6Ly9kaXZlc2l0ZS1zdG9yYWdlL2RpdmVpbWFnZS9HZXR0eUltYWdlcy0xNDA3OTAzNTMyLmpwZw==.webp" /></div></figure><p>The programs address specific substations with high solar penetration or summer-peak congestion issues. They could expand in the coming years, a spokesperson said.</p>”
- “<p>A major renewable energy developer and a leading independent asset manager have joined to support a portfolio of battery energy storage systems in Poland, part of the continuing buildout of new power infrastructure across Europe.</p> <p>The post <a href="https://www.powermag.com/battery-energy-storage-grid-investments-surge-across-europe/">Battery Energy Storage, Grid Investments Surge Across Europe</a> appeared first on <a href="https://www.powermag.com">POWER Magazine</a>.</p> <p><img alt="Fig1-ABB-Dalmine_c" class="attachment-post-thumbnail size-post-thumbnail wp-post-image" height="269"”
- “<p>Une nouvelle association professionnelle dans la transition énergétique, cette fois pour les spécialistes du stockage raccordé au réseau haute tension de RTE. Baptisée Stockage Energie France, elle a été lancée  </p> <p>L’article <a href="https://www.greenunivers.com/2026/07/les-exploitants-de-grosses-batteries-lancent-leur-association-428226/">Les exploitants de grosses batteries lancent leur association</a> est apparu en premier sur <a href="https://www.greenunivers.com">GreenUnivers</a>.</p>”
Geospatial data
这些证据表明了有关交钥匙安装和现场服务部署的地理位置的表格数据，这对于情境化资产性能和构建区域模型很有价值。
IoT / sensor data
这些证据证实了从监控的能源存储系统中收集的实时时间序列数据，捕获了对训练预测算法至关重要的电池循环和性能指标。
Industrial data
这些证据强调了一个关于翻新电动汽车电池的性能和寿命的专有时间序列数据集，为预测二手资产行为的模型提供了稀有且有价值的信号。
Transaction data
这些证据指向了来自能源管理活动（如日内交易和削峰填谷）的表格数据，为运营和资产优化模型提供了关键的经济背景。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Time Series
License
One-time license for use in training predictive maintenance models and optimizing operational schedules.
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 high rarity, proprietary nature, and direct application to the high-growth predictive maintenance market (valued at $14.2B in 2025) drive its significant valuation. Real-time freshness further enhances its value for immediate operational insights.
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Voltfang 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 = $14.2B in 2025, CAGR 27.9% (source: Grand View Research). Investment score 75.2/100 (confidence 0.56). Recommended action: Acquire.
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