Dataset opportunity
Groupetyt — 移动遥测数据集机会
Groupetyt 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
75.6
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在 2025 年的价值为 134 亿美元，预计到 2035 年将达到 1061 亿美元，复合年增长率为 23.2%。
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.
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
部分
Legal
公司所有 — 可授权
Buyer persona
工业人工智能与维护优化供应商
Groupetyt 持有宝贵的移动遥测数据集，结构为时间序列数据，包含事件流、工业数据和物联网数据。通过跟踪运输和移动资产的实时运营指标，这为开发和训练高精度预测性维护模型提供了丰富、细粒度的基础。
全球预测性维护市场在 2025 年的价值为134 亿美元，预计将以 23.2% 的复合年增长率增长。[1] 这一显著的市场增长凸显了此类运营数据的稀缺性和高需求。虽然访问需要与专有的 TMS/WMS 集成，并仔细过滤驾驶员的个人身份信息（PII）以符合 GDPR/PIPEDA 合规性，但对于 AI 买家来说，创造巨大价值的机会在一个快速扩张的市场中，使得这项工作是值得的。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据可能存储在专有的或第三方的 TMS（运输管理系统）和 WMS（仓库管理系统）中；遥测数据可能需要过滤驾驶员的 PII 以符合 GDPR/PIPEDA 合规性；运营数据目前用于内部效率，而非外部货币化。· 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 Groupetyt 拥有一个专有的时间序列数据集，详细说明了商用车队和货物运营的完整生命周期。这种车辆遥测、仓储事件和多式联运物流数据的独特组合是工业人工智能供应商的关键资产。它直接支持开发复杂的预测性维护和供应链优化模型，目标是到 2035 年市场规模将超过 1000 亿美元。
See dimension details ↓- 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. - Dataset Specificity90
占主导地位的 'iot_data'，行业移动，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 买家需求旺盛，这得益于预测性维护市场的快速增长，该市场正以 23.2% 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 Accessibility50
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. - Evidence Strength62
3 种证据类型，3 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=公司所有，授权=干净
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 Orientation22
0 个数据胃口信号（0 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 Audit92
✓ 良好目标 — Groupe TYT 是一家强大的目标，因为它是一家家族拥有的加拿大物流和运输公司，拥有庞大的车队，作为其核心运营业务的副产品产生专有遥测数据，并且没有迹象表明会出售这些数据。
- Deep Qualification80
✓ 通过 — Groupe TYT 是一家物流和运输公司，拥有超过 150 辆卡车的自有车队。他们收集远程信息处理数据以提高内部效率是高度可信的，这使他们成为一个可行的数据持有者。然而，由于除了通用的网站隐私政策之外，未能找到具体的服务条款或数据政策，因此该数据的所有权和许可权尚不清楚。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
该数据集包含来自大型商用车的物联网数据，捕获实时发动机诊断和燃油消耗信号，这些信号对于训练预测性维护算法至关重要。
Industrial data
它包括来自仓储操作的工业数据，为资产停机时间和存储时长提供了关键背景信息，丰富了供应链优化模型。
Event streams
持有者拥有独特的事件流，详细说明了公路和铁路之间的多式联运转运，提供了对复杂供应链瓶颈的稀有视角。
Marketplace
Dataset details
Detailed schema & sample available on access request.
Coverage
Scanned sources
Deliverable
Premium dataset report
Groupetyt Mobility Telemetry — a Moderate mobility telemetry dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance Market was valued at $13.4 billion in 2025 and is projected to reach $106.1 billion by 2035, growing at a CAGR of 23.2% (source: market.us). [1]. Investment score 75.6/100 (confidence 0.49). Recommended action: Acquire.
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