Dataset opportunity
Pro Vigil — 传感器遥测数据集机会
Pro Vigil 持有的中等规模传感器遥测数据集，可用于预测性维护和异常检测。
Score
45
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
58%
Action
数据共享协议
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 年估值为 142 亿美元，预计复合年增长率为 27.9%（2026-2033 年）。
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
传感器遥测数据集
Modality
时间序列
Sector
其他
Volume
中等
Freshness
实时
Rarity
中等
Accessibility
部分
Legal
混合所有权 — GDPR 敏感（PII 审查）
Buyer persona
工业人工智能与维护优化供应商
Pro Vigil 持有源自其远程监控运营的大量传感器遥测数据集，包含丰富的时间序列数据。该集合包括部署的摄像头和传感器的大量 `iot_data` 和 `event_streams`，使其非常适合开发预测性维护模型，以在设备发生故障前进行预测。
商业价值巨大，面向全球预测性维护市场，该市场在2025 年估值为 142 亿美元，预计将以27.9% 的复合年增长率增长。[3] 虽然访问需要处理视频数据中的个人身份信息 (PII) 匿名化以及潜在的数据共享所有权，但在快速增长的市场中，该稀有且标记的事件数据量大，为创建先进的人工智能解决方案提供了关键优势。[3] ⚠ 尽职调查（有价值的数据，可协商访问）：视频数据包含需要匿名化的个人身份信息（面部、车牌）；数据所有权可能通过服务合同与场地所有者（建筑/经销商）共享；大量的标记“事件”数据（犯罪与误报）可能是专有的。· 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 Pro-Vigil 拥有大规模的传感器遥测数据集，涵盖了工业领域数亿个真实世界的设备事件和系统响应。这些数据对于构建预测性维护解决方案的人工智能供应商至关重要，使他们能够训练强大的异常检测算法来预测设备故障。在全球市场预计每年增长近 28% 的情况下，这一独特的真实数据集合为优化工业运营提供了显著的竞争优势。
See dimension details ↓- Dataset Specificity74
占主导地位的 'iot_data'，行业其他，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 Rarity58
专有领域数据（开放会降低稀有度）
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume64
5 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 Demand95
人工智能买家需求异常高，这得益于对海量真实传感器和事件数据的需求，以利用预测性维护市场 27.9% 的复合年增长率。[3]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility48
开放/API 访问
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility66
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 Strength77
4 种证据类型，5 次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License28
所有权=混合，许可=GDPR 敏感
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 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 — 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 Audit50
⚠ 审查 — 该公司的核心业务是销售人工智能驱动的远程视频监控和安全即服务，这是一种情报产品，因此不适合。问题：公司的核心产品是销售从传感器数据（视频流）中提取的情报/分析，而不是其他运营业务的副产品。[9, 14, 17；该公司明确将自己定位为“人工智能视频监控公司”和“远程视频监控解决方案”的提供商。[9, 10, 14]；业务模式是按订阅收费的“监控即服务”，这属于排除标准。[4, 15]；他们的长期目标是为客户从视频流中提取有意义的见解，这证实了他们从事销售情报的业务。[16]
- Deep Qualification80
✓ 通过 — Pro-Vigil 是一个强大的数据持有者候选者，销售人工智能驱动的远程安全服务，并产生有价值的事件和设备遥测数据副产品。虽然数据所有权条款未公开，但其设备健康监控服务已确认该数据集与预测性维护的直接相关性。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Downloads / exports
该公司发布行业报告和案例研究，展示了在货运与物流等领域的深厚专业知识，为主要传感器数据提供了宝贵的背景信息。
Event streams
该数据集包含来自建筑和汽车站点的数亿个带时间戳的运动警报，提供了训练预测模型所需的大量事件数据。
Image collection
持有者维护着数千个已验证的安全干预记录，这是一个高价值的标记数据集，用于训练和验证威胁检测算法。
IoT / sensor data
数据包括超过 520 万个已部署的音频/视频威慑器的日志，提供了对检测到的事件的系统响应的独特时间序列信号，这对于建模设备行为至关重要。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Pro Vigil Sensor Telemetry — a Moderate sensor telemetry dataset (Time Series modality) in the other domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market was valued at USD 14.2 billion in 2025, with a projected CAGR of 27.9% (2026-2033) (source: Grand View Research). [3]. Investment score 45.0/100 (confidence 0.58). Recommended action: Data Sharing Agreement.
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