Dataset opportunity
Oakland International — Mobility Telemetry Dataset Opportunity
Oakland International 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
66.9
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
Acquire
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)
Global Predictive Maintenance Market = $13.65 billion in 2025, CAGR 24.30%.
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
mobility
Volume
Moderate
Freshness
Real-time
Rarity
高（专有）
Accessibility
Restricted
Legal
Mixed ownership — licensing rights to clarify
Buyer persona
Industrial AI & maintenance-optimization vendors
Oakland International 拥有一个重要的移动遥测数据集，该数据集以时间序列数据的形式构建，源自其核心物流运营。该数据集包括来自 iot_data 的专有运营遥测数据（如温度和车辆日志）以及事件流，为训练预测性维护模型以预测设备故障和优化车队正常运行时间提供了丰富的基础。
该数据的商业价值在全球预测性维护市场中得到凸显，该市场在 2025 年的估值为136.5 亿美元，预计将以惊人的24.30% 的复合年增长率增长。虽然访问需要仔细处理专有、客户拥有和 GDPR 敏感信息，但这种真实运营数据的稀有性及其对高增长人工智能应用的直接适用性为买家提供了引人注目的机会。⚠ 尽职调查（有价值的数据，可协商的访问权限）：运营遥测数据（温度/物流）是专有的，但库存数据是客户拥有的；B2C 履行数据包含 GDPR 敏感的个人身份信息；海关数据涉及监管敏感性 · 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 Oakland International 拥有其复杂的冷链 物流运营产生的丰富、专有的时间序列数据集。这是工业人工智能供应商构建用于温度控制设备和车队预测性维护模型的首选资产。在一个年增长率超过 24% 的市场中，这个独特的数据集提供了训练算法所需的真实传感器和运营数据，这些算法可以预测故障、优化资产正常运行时间并减少关键供应链中昂贵的停机时间。
See dimension details ↓- Dataset Specificity78
主导的 'iot_data'，行业 mobility，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 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 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. - Buyer Demand95
人工智能买家需求极高，这得益于全球预测性维护市场的快速增长，该市场正以 24.30% 的复合年增长率扩张。
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 Feasibility30
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 Strength62
3 种证据类型，3 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 Orientation22
0 个数据需求信号（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 Audit75
✓ 良好目标 — Oakland International 是一个强有力的目标，因为它是一家大型、可联系的物流公司，拥有大量的车队，其核心业务的副产品是产生专有遥测数据，并且没有出售这些数据的迹象。问题：初始提示提到了“Oakland International — Mobility Telemetry Dataset Opportunity”，但搜索结果显示了两个不同的公司：“Oakland Inte；该公司比典型中小企业规模更大，员工人数报告在 318 到 763 人之间，这可能与理想客户画像略有偏差；有一家名称相似的数据咨询公司“Oakland”，明确销售数据分析和人工智能服务；应排除此实体，因为它是一个糟糕的目标。
- Deep Qualification90
✓ 通过 — 目标是一家物流运营商（`data_holder`），其运营副产品（移动和温度遥测数据集）与其业务模式一致；但是，数据所有权是混合的，并且涉及其 D2C 服务的 GDPR 敏感信息。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
这些证据证实了来自监控冷藏和冷冻环境的物联网传感器的连续时间序列数据的存在，这对于训练模型以预测制冷单元和其他关键冷链资产的故障至关重要。
Event streams
这代表了来自复杂分销网络管理的基于事件的时间序列数据，为更准确的维护预测提供了资产使用和运营压力的关键背景。
business_records
这些文件证据验证了公司国际物流运营的规模和复杂性，提供了丰富的元数据来为遥测数据提供背景信息，特别是在脱欧后的贸易模式方面。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Oakland International 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 = $13.65 billion in 2025, CAGR 24.30% (source: Fortune Business Insights). Investment score 66.9/100 (confidence 0.49). Recommended action: Acquire.
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