Dataset opportunity
Imove — 移动遥测数据集机会
Imove 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
63.2
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
44%
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)
全球车辆预测性维护市场 = 2026 年为 33 亿美元，复合年增长率为 20.5%。
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
Volume
中等
Freshness
实时
Rarity
中等
Accessibility
受限
Legal
公司所有 — GDPR 敏感（个人身份信息审查）
Buyer persona
工业人工智能与维护优化供应商
Imove 持有一个移动遥测数据集，该数据集包含其车队运营的时间序列 iot_data 和业务记录。这些详细数据捕获发动机性能、组件状态和驾驶行为等指标，直接适用于训练预测性维护用例的算法，使模型能够在组件发生故障之前进行预测。
全球车辆预测性维护市场在 2026 年的价值约为 33 亿美元，预计到 2033 年将达到 123 亿美元，复合年增长率高达 20.5%。[1] 虽然访问需要处理与合作伙伴 Casi 的数据共享所有权以及高度的 GDPR 敏感性，但该数据集的丰富性为在这个高增长、数十亿美元的市场中建立竞争优势提供了难得的机会。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据所有权与车队管理运营相关，并与技术合作伙伴 Casi 共享；由于详细的驾驶行为和位置跟踪，GDPR 敏感性高；在 2023 年破产后重组实体，现为 Hedin Mobility Group 生态系统的一部分 · 公司：Hedin Mobility Group 的子公司。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据表明 Imove 拥有其超过 1,500 辆电动汽车车队的大量运营遥测和驾驶行为数据集。这些时间序列数据是工业人工智能供应商构建预测性维护模型的宝贵资产，该市场预计到 2026 年将达到 33 亿美元。该数据集对寒冷气候下电动汽车电池性能的独特关注，为训练优化车队利用率并降低该增长车辆细分市场维护成本的算法提供了地面实况。
See dimension details ↓- Dataset Specificity66
主导的 'iot_data'，移动行业，1 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
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 Value64
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
人工智能买家需求旺盛，这得益于车辆预测性维护市场的快速增长，该市场正以 20.5% 的复合年增长率扩张。[1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility20
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，Hedin Mobility Group 的子公司
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength53
2 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 License62
所有权=公司所有，许可=GDPR 敏感
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence50
Hedin Mobility Group 的子公司
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation73
3 个数据需求信号（3 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
✓ 好目标 — 该公司的核心业务是 B2C 汽车订阅服务和使其他公司能够提供订阅的 B2B SaaS 平台，作为副产品生成专有移动数据，而不是将其作为核心产品出售。问题：该公司的业务包括销售白标 SaaS 平台，这接近于“销售情报/软件”排除标准，但该平台
- Deep Qualification70
✓ 通过 — 目标是一个数据持有者，拥有适用于预测性维护用例的合理数据集，但由于与技术提供商 Casi 的公司拆分，数据所有权复杂，并且在没有特定法律文件的情况下无法验证许可权。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
这些证据表明收集了详细的时间序列物联网数据，捕获了驾驶行为和电动汽车电池性能，这是开发车队预测性维护模型的人工智能供应商的关键输入，这些车队在寒冷气候下运行。
business_records
这些证据指向内部平台分析，这些分析量化了车队性能，通过将其与利用率和财务绩效等关键业务指标联系起来，为物联网数据提供了商业背景和验证。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Imove Mobility Telemetry — a Moderate mobility telemetry dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Vehicle Predictive Maintenance market = US$ 3.3 billion in 2026, CAGR 20.5% (source: Insight-Ace-Analytics). [1]. Investment score 63.2/100 (confidence 0.44). Recommended action: Data Sharing Agreement.
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