Dataset opportunity
K Ryole — 移动遥测数据集商机
K Ryole 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
69.1
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
53%
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
全球预测性维护市场 = 2025 年 $14.93 亿美元，复合年增长率 32.32% (2026-2035)
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-04
A Driver’s Paper Logs Said He Was in One Place. A Roadside Camera Network Said Otherwise. Welcome to the New Era of Trucking Enforcement.
freightwaves.com ↗ - 📰press2026-06-04
Inthy accélère dans les camions électriques, renonce à l’hydrogène
greenunivers.com ↗ - 📰press2026-06-04
Jumbo planifie ses tournées en réel avec Greenplan
supplychainmagazine.fr ↗ - 📰press2026-06-04
Shiftmove automatise la gestion des documents de flotte avec l’IA
journalauto.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.
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
混合所有权 — 许可权待明确
Buyer persona
工业人工智能和维护优化供应商
K Ryole 拥有丰富的移动遥测数据集，其特点是时间序列模式，包含从活跃客户车辆使用中获取的关键地理数据、工业数据和物联网数据。这种细粒度的真实世界运营数据为车辆性能和状况提供了深入洞察，使其非常适合开发和增强预测性维护AI解决方案。
驱动预测性维护的数据市场正在经历显著扩张，全球市场预计到2035年达到2457.3亿美元，2026年至2035年间的复合年增长率（CAGR）高达32.32%。尽管作为 DIS集团的子公司需要协调，并且通过“Connected Park”存在现有数据共享，但这种运营物联网数据在优化资产正常运行时间和降低成本方面的固有稀有性和量化商业价值使其对AI买家极具吸引力。更广泛的工业物联网市场（为此类应用提供动力）也表现强劲，预计将从2025年的1423.9亿美元增长到2031年的5656.2亿美元，复合年增长率为24.19%。⚠ 尽职调查（有价值的数据，可协商的访问权限）：DIS集团的子公司，需要与母公司协调；客户通过“Connected Park”访问数据意味着部分数据已被共享/授权；数据由客户车辆使用产生。· 公司：被DIS集团收购。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
K Ryole 拥有独特的专有遥测数据，这些数据由其移动资产（特别是电动拖车和手推车）生成，并以高频率（每10毫秒）捕获。这种丰富的时间序列数据，包括力测量和维护日志，对于工业AI和维护优化供应商来说是无价的。它直接推动了预测性维护模型的发展，这是全球市场预计到2025年达到149.3亿美元的关键能力，为寻求优化资产性能和减少停机时间的买家提供了显著的竞争优势。
See dimension details ↓- Dataset Specificity90
主导的‘物联网数据’，移动出行领域，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 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
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 Demand92
全球汽车预测性维护市场严重依赖移动遥测数据来驱动AI解决方案，预计将以18.6%的复合年增长率从2023年的220亿美元增长到2032年的1000亿美元。
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DIS集团收购
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength68
3种证据类型，5个命中
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
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence45
被DIS集团收购
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，4个近期外部信号 — 超出已货币化的专有数据
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 Audit100
✓ 良好目标 — K-Ryole 是一家法国中小企业，生产智能电动拖车，其运营过程中会产生有价值的遥测数据作为副产品，目前他们并未将其作为核心业务出售。问题：该公司于2025年11月被DIS集团收购，这可能会给其专有数据的数据共享决策带来复杂性。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
此证据证实 K Ryole 从其联网车辆收集高频传感器数据和操作日志，提供对预测性维护和资产性能优化至关重要的细粒度洞察。
Industrial data
此数据详细说明了 K-Ryole 车辆的制造来源和组件采购，为供应链分析和理解产品可靠性提供了有价值的背景信息。
Geospatial data
此证据提供了关于 K-Ryole 电动拖车的描述性信息，突出了其独特的力测量能力和操作背景，这对于理解数据的实际应用非常有价值。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Rolling 12 months
Update frequency
Real-time
Delivery
API
Formats
Time Series, JSON
License
One-time license for internal use in developing predictive maintenance AI models. Restrictions on redistribution and resale apply.
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 proprietary, high-frequency mobility telemetry dataset is rare and directly fuels the rapidly growing predictive maintenance market. Its granular time-series data on vehicle performance and maintenance logs offers significant value for AI-driven optimization.
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
K Ryole 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 = $14.93 Billion in 2025, CAGR 32.32% (2026-2035). Investment score 69.1/100 (confidence 0.53). Recommended action: Partnership (group-level).
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