Dataset opportunity
Streetdrone — 移动遥测数据集机会
Streetdrone 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
70.9
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
合作（集团层面）
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
2024年全球汽车预测性维护市场规模为46.6亿美元，复合年增长率为17.5%（2025-2034年）。[4]
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-12
Gatik to bring autonomous freight to PepsiCo’s North American supply chain
therobotreport.com ↗ - 📰press2026-06-12
Volvo Autonomous Solutions to remove safety drivers in Q1 2027
freightwaves.com ↗ - 📰press2026-06-11
PepsiCo expanding autonomous truck use in its supply chain
supplychaindive.com ↗ - 📰press2026-06-09
Walmart, Wing add 7 markets in drone delivery expansion
therobotreport.com ↗
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.
Profile
Dataset profile
Type
移动遥测数据集
Modality
时间序列
Sector
移动出行
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
Streetdrone 拥有一个宝贵的移动遥测数据集，该数据集由其自动驾驶汽车边缘系统收集的时间序列数据组成。这些数据包括详细的 `event_streams`（事件流）、`geo_data`（地理数据）和 `iot_data`（物联网数据），提供了对车辆运行和组件健康的全面、实时的视图。这些数据流的丰富性和粒度使其非常适合开发复杂的 AI 模型用于预测性维护，从而在潜在系统故障发生之前准确预测它们。
该数据的市场巨大且不断增长；全球汽车预测性维护市场在 2024 年的估值为46.6 亿美元，预计将以 17.5% 的复合年增长率 (CAGR) 扩张。[4] 尽管存在已知的访问复杂性——例如 Streetdrone 被 Oxa 收购、潜在的三方数据所有权协议以及高昂的技术提取障碍——但该数据集仍然是一项有价值且稀有的资产。对运营效率和减少停机时间的追求驱动着强劲的市场需求，这证明了为高级 AI 应用访问这些高质量数据所需的谈判努力是合理的。⚠ 尽职调查（有价值的数据，可协商访问）：最近被 Oxa 收购；数据策略可能已整合到母公司；数据所有权可能受与工业场地运营商（港口、机场）的三方协议约束；从自动驾驶汽车边缘系统提取数据的技术复杂性高 · 公司：被 Oxa 收购。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同证明 Streetdrone 拥有来自自动驾驶系统在港口和物流中心等复杂工业环境中的车辆遥测和运行事件的专有数据集。AI 供应商寻求这些独特数据来构建和验证下一代预测性维护解决方案。在一个预计将超过 46.6 亿美元的市场中，该数据集提供了改进模型准确性和可靠性以抢占市场份额所需的关键传感器数据和地面实况故障事件。
See dimension details ↓- Dataset Specificity90
主导的 'iot_data'（物联网数据），移动出行行业，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 个证据点
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 Demand85
全球汽车预测性维护市场，该市场基本依赖于移动遥测数据，预计将以强劲的 18.6% 的复合年增长率增长，这表明 AI 团队对此类数据的需求非常高且不断增长。
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 Feasibility15
中等难度，被 Oxa 收购
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 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 Independence45
被 Oxa 收购
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation56
2 个数据需求信号（2 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 — 超出已货币化数据的专有数据
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. - ICP Audit42
⚠ 审查 — Streetdrone 被 Oxa 收购，其核心业务是销售自动驾驶软件和技术解决方案，而不是作为副产品生成的数据。问题：公司被更大的自动驾驶软件公司 Oxa 收购，成为一个更大、更复杂的集团的一部分。[1, 3, 4, 5]；公司的核心业务是开发和销售自动驾驶技术（线控驱动、远程操作、软件）作为产品，这是明确的排除项；它是一家技术/软件公司。
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 Streetdrone 在真实物流环境中运行的线控驱动系统的传感器数据时间序列的存在，这是训练预测性维护算法的基础。
Geospatial data
该数据集包含高清晰度的私人工业站点的空间数据和地图，提供了关键的环境背景，使 AI 模型能够通过将车辆性能与特定位置相关联来改进维护优化。
Event streams
这指向了一系列远程操作日志，这些日志充当高价值的干预日志，明确标记系统异常和边缘情况事件，用于训练稳健的故障预测模型。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
JSON, Time Series
License
One-time license for AI model development and validation in predictive maintenance, with restrictions on redistribution.
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 real-time freshness from autonomous vehicle edge systems drive its value for AI-driven predictive maintenance. The substantial and growing global automotive predictive maintenance market, projected to exceed $4.66 billion, indicates strong demand for such granular telemetry.
Detailed schema & sample available on access request.
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This listing was generated automatically from public signals. It is not verified, and we are not affiliated with this company.
Coverage
Scanned sources
Deliverable
Premium dataset report
Streetdrone Mobility Telemetry — a Moderate mobility telemetry dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global automotive predictive maintenance for vehicles market = $4.66 Billion in 2024, CAGR 17.5% (2025-2034). [4]. Investment score 70.9/100 (confidence 0.49). Recommended action: Partnership (group-level).
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