Dataset opportunity
Kotra — 移动遥测数据集机会
Kotra 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
75.8
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 年的估值为 136.5 亿美元，预计到 2034 年的复合年增长率为 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.
Concrete evidence this company actively cares about data — why it's ripe for the deal room.
- ✨Signal
实时跟踪和追踪系统实施
source ↗
Profile
Dataset profile
Type
移动遥测数据集
Modality
时间序列
Sector
mobility
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
Kotra 持有一个专有的移动遥测数据集，该数据集由其庞大的温控卡车和仓库车队生成。这些时间序列数据包括详细的 `geo_data`、`industrial_data` 和 `iot_data`，为构建和训练高保真预测性维护模型提供了丰富的运营基础，以预测车辆组件故障、减少计划外停机时间并优化整个车队的维护计划。
预测性维护的全球市场正在迅速扩张，2025 年市场价值为136.5 亿美元，预计将以24.30% 的复合年增长率增长。虽然由于数据源自更大的 Kotra Group，访问需要高级别的公司参与，但其稀有性及其与这个高增长市场的直接适用性使其成为寻求在物流领域获得竞争优势的 AI 买家的关键资产。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据由大型专有温控卡车和仓库车队生成；运营数据（遥测/物联网）与客户拥有的货物清单不同；作为更大的 Kotra Group 的一部分，需要高级别的公司参与。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同证明了持有方运营着一个大型专有网络，拥有超过 150 辆温控卡车，从工业冷却发动机和自动化传感器生成连续的时间序列数据。这个独特的数据集是工业人工智能供应商为冷链物流行业构建预测性维护解决方案的首选资产。在一个预计年增长率超过 24% 的全球市场中，这些数据直接支持了能够预测设备故障、优化维护计划并防止昂贵停机时间的模型的训练。
See dimension details ↓- Dataset Specificity90
占主导地位的 'iot_data'，行业 mobility，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 买家需求异常高，这得益于预测性维护市场的快速扩张，预计复合年增长率为 24.30%。
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. - 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 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，许可=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 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. - ICP Audit92
✓ 目标明确 — Kotra 是一个强有力的目标；这是一家家族经营的温控物流中小企业，拥有大型车队，作为其核心运输业务的副产品，生成专有遥测和温度数据。问题：该公司正在积极对其流程进行数字化，包括使用电子 CMR 平台，这意味着他们了解自己的数据，但他们的重点是内部优化；员工人数因来源而异（101-200，501-1000），但它牢牢地属于中小企业或稍大一些的类别。
- Deep Qualification90
✓ 通过 — Kotra 是一个强大的数据持有者候选者。它运营着一支大型现代化车队，配备了用于实时温度和位置监控的远程信息处理系统，作为其核心物流业务的副产品，生成了宝贵的移动和物联网数据集。该公司已明确表示打算使用这些数据进行流程优化。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
这些证据表明来自拖车式冷却发动机和温度传感器的专有时间序列数据，这对于训练算法以预测组件故障至关重要。
Geospatial data
这些表格数据量化了运营规模，证实了拥有超过 150 辆卡车的车队，并定义了欧洲地理范围，这为分析不同路线上的资产绩效提供了关键背景。
Industrial data
这证实了从温控环境中持续生成自动化时间序列数据，这是优化能源消耗和确保冷链完整性的模型的关键输入。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Kotra 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 $13.65 billion in 2025, with a projected CAGR of 24.30% through 2034 (source: Fortune Business Insights).. Investment score 75.8/100 (confidence 0.49). Recommended action: Acquire.
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