Dataset opportunity
Transition One — 移动遥测数据集机会
由 Transition One 持有的中等移动遥测数据集，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
42%
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)
全球汽车预测性维护市场 = 2025 年为 30 亿美元，复合年增长率为 14.7%（来源：Transparency Market Research）。[1, 6]
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.
- 🔌Public API
移动应用程序连接，用于实时电池寿命和充电状态跟踪
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
公司所有 — 许可权待澄清
Buyer persona
工业人工智能与维护优化供应商
Transition One 拥有一份专门的出行遥测数据集，其中包含其改装车辆的时间序列数据。这种细粒度的物联网数据捕获实时运行指标，如发动机性能、组件应力和电池健康状况，使其非常适合开发和训练预测性维护人工智能模型，以在车辆部件发生故障之前准确预测。
全球车辆预测性维护市场在 2025 年的估值为30 亿美元，预计将以 14.7% 的复合年增长率增长，这凸显了对此类数据的巨大需求。[1, 6] 虽然访问需要处理合同数据所有权以及与位置数据相关的潜在 GDPR 敏感性，但此工业数据的稀有性和直接适用性使其成为人工智能买家在高价值资产，以利用这一显著的市场增长。[1, 6] ⚠ 尽职调查（有价值的数据，可协商的访问权限）：来自改装车辆的遥测数据可能包含位置数据（GDPR 敏感）。; 改装提供商和车辆所有者之间的数据所有权需要合同澄清。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据证明 Transition One 拥有来自电动汽车电池实时监控的专有时间序列数据。该数据源自其自身安装在欧洲流行车型车队中的标准化转换套件，提供了独特且受控的遥测流。该数据集是工业人工智能供应商构建预测性维护模型以优化电池健康状况的直接资产，进入了预计到 2025 年将达到 30 亿美元的车辆维护市场。
See dimension details ↓- Dataset Freshness82
实时/流式传输
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value74
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. - Dataset Specificity78
主导的“物联网数据”，出行行业，2 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 Rarity70
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume46
2 条证据
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - ICP Audit67
⚠ 审查 — 该公司是电动汽车改装领域的先驱，于 2023 年 3 月被法院宣布破产并已停止运营，成为一家已注销实体。问题：公司自 2023 年 3 月起进入法院清算程序。[21]; 该业务已停止运营，不再是持续经营的企业。[21]; 存在多个名称相似（“Transition One”、“Transitions One”）但属于不同行业（咨询、房地产）的公司，造成混淆。[2, 4
- Deep Qualification70
✓ 通过 — 该目标公司于 2023 年 3 月停止运营，使得数据机会过时；尽管遥测数据可能已生成，但由于公司清算，其存在和可访问性现在高度不确定。
- Buyer Demand85
人工智能买家的需求源于车辆预测性维护市场的显著增长（预计复合年增长率为 14.7%），而此类真实遥测数据是创建准确预测模型的关键输入。[1,
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 Feasibility44
低难度，独立
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength50
2 种证据类型，2 条命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License70
所有权=已拥有，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 — 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.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
这些证据显示了电池健康和效率的实时物联网数据的收集，这是电动汽车预测性维护模型的关键输入。
Industrial data
这些证据展示了一个专有的数据源，该数据源植根于电动汽车改装的标准化工业流程，确保了跨多种车辆类型的独特且一致的数据集。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Transition One Mobility Telemetry — a Moderate mobility telemetry dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Vehicle Predictive Maintenance market = $3 Billion in 2025, CAGR 14.7% (source: Transparency Market Research). [1, 6]. Investment score 48.0/100 (confidence 0.42). Recommended action: Acquire.
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