Dataset opportunity
Haeberle Logistik — 移动遥测数据集机会
Haeberle Logistik 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
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
42%
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 = 2024 年为 88.9 亿美元，复合年增长率为 32.30%（来源：Data Bridge Market Research）。[1]
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
使用最先进的 GPS/跟踪和 EDP 控制的仓储系统
source ↗
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
高（专有）
Accessibility
部分
Legal
混合所有权 — 可授权
Buyer persona
工业人工智能与维护优化供应商
Haeberle Logistik 持有一个宝贵的移动遥测数据集，该数据集结构为时间序列数据，收集自其在汽车物流领域广泛的工业数据和物联网数据基础设施。这些详细的运营数据跟踪车辆和设备随时间推移的性能，非常适合开发和训练预测性维护人工智能模型，以便在发生昂贵的故障之前准确预测组件故障并优化维护计划。
其商业价值巨大，因为全球预测性维护市场在2024 年的估值为88.9 亿美元，预计将以惊人的32.30% 的复合年增长率扩张。[1] 虽然由于数据存储在专有的 WMS/TMS 系统中以及传统的德国中型企业文化，访问需要仔细协商，但防止停机时间和优化高风险汽车供应链的巨大价值使其成为人工智能买家稀有且备受追捧的资产。⚠ 尽职调查（有价值的数据，可协商的访问权限）：运营遥测和供应链日志可能存储在专有的 WMS/TMS 系统中；客户特定的库存数据在外部使用前需要匿名化；传统的德国中型企业文化可能需要高接触式参与。· 企业：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 Haeberle Logistik 拥有来自其现代、完全监控的 120 辆车队的专有且连续的时间序列遥测数据流。该数据集直接服务于高增长的预测性维护市场，使工业人工智能供应商能够训练预测组件故障并优化准时制供应链的模型。在一个年增长率超过 32% 的市场中，这种稀有的移动出行数据是开发下一代维护优化解决方案的关键资产。
See dimension details ↓- Dataset Specificity78
占主导地位的'物联网数据'，移动出行行业，2 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 Rarity70
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume46
2 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 Value74
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，这得益于全球预测性维护市场的爆炸式增长，预计该市场将以 32.30% 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 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 Strength50
2 种证据类型，2 个命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License58
所有权=混合，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，2 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 Audit92
✓ 良好目标 — 这家家族式中型物流公司拥有自己的车队，并专注于复杂的物流业务，使其成为持有宝贵、休眠遥测和供应链数据的有力候选者。问题：该公司是拥有 800 名员工的更大集团（'Häberle Gruppe'）的一部分，这可能会使决策复杂化，尽管物流部门本身有 300 名员工；他们拥有一家软件开发和管理咨询子公司（'Logigraphics Logistics & Solutions'），这可能意味着存在一些数据专业知识。
- Deep Qualification80
✓ 通过 — 该目标是一家传统的物流公司，持有但不出售相关的运营数据；由于其车队配备了现代化的远程信息处理系统用于跟踪和监控，因此“移动遥测数据集”是合理的。
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 120 辆车队的持续时间序列物联网数据的存在，这些车队得到了完全监控，是训练人工智能模型以预测车辆维护需求的关键输入。
Industrial data
这些证据指向与汽车客户的准时制交付物流相关的工业流程数据，为供应链优化模型提供了重要的运营背景。
press
- “<figure><div><img src="https://imgproxy.divecdn.com/2nLbPa8nzUfMhrLKUBWFViob05LpXMy6UYtXhY3suUY/g:ce/rs:fill:1600:900:1/Z3M6Ly9kaXZlc2l0ZS1zdG9yYWdlL2RpdmVpbWFnZS8yMDI2X1RveW90YV9UYWNvbWFfU1I1XzAwNS0xLTE1MDB4MTAwMC5qcGVn.webp" /></div></figure><p>The automaker won’t yet say what portion of U.S.-bound Tacoma production will shift from Mexico after expanding the San Antonio factory.</p>”
Marketplace
Dataset details
Detailed schema & sample available on access request.
Want this data?
Request access — we broker a secure deal room. Operator-reviewed, no automatic sharing.
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
Haeberle Logistik 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 = $8.89B in 2024, CAGR 32.30% (source: Data Bridge Market Research). [1]. Investment score 69.1/100 (confidence 0.42). Recommended action: Acquire.
From the marketplace
Explore live data opportunities
Chipolo — 可下载数据资产机会
View opportunity →工业Trophyfoods — 监管记录数据集机会
View opportunity →工业Wesltd — 检验报告数据集机会
View opportunity →