Dataset opportunity
Iamrobotics — 工业传感器数据集机会
Iamrobotics 持有的中等工业传感器数据集，可用于预测性维护和异常检测。
Score
48
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 size (indicative estimate)
全球预测性维护市场 = 2025 年为 136.5 亿美元，复合年增长率 24.30%。
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
为本地化系统迭代积极收集传感器数据
source ↗
Profile
Dataset profile
Type
工业传感器数据集
Modality
时间序列
Sector
工业
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — 需明确许可权
Buyer persona
工业人工智能与维护优化供应商
Iamrobotics 拥有由其自主移动机器人车队生成的宝贵工业传感器数据集。这些数据以时间序列 `event_streams` 和 `iot_data` 的形式呈现，捕获工业环境的连续运行指标，使其非常适合开发和验证预测性维护算法以预测设备故障。
全球预测性维护市场在 2025 年的估值为 136.5 亿美元，预计到 2034 年将增长到 973.7 亿美元，复合年增长率 (CAGR) 达到惊人的 24.30%。虽然访问需要应对客户数据权利和机器人即服务 (Robotics-as-a-Service) 模型固有的安全敏感性等复杂问题，但这同时也确保了数据的稀有性和高价值。数据集的丰富性在对有效人工智能解决方案需求强烈的市场中提供了显著的竞争优势。⚠ 尽职调查（有价值的数据，可协商的访问权限）：仓库布局和吞吐量数据可能在合同上归物流客户所有；关于工业安全和设施映射的高度敏感性；数据通过机器人即服务 (RaaS) 生成，该服务通常集中遥测 · 公司：KCK Group（投资者/所有者）的子公司。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同证明 Iamrobotics 拥有其在真实物流和仓储环境中运行的工业机器人的专有、高稀有度时间序列数据。该数据集包括来自多传感器融合的信号，并捕获人机系统内的复杂交互，使其成为人工智能供应商独一无二的宝贵资产。对于开发预测性维护解决方案的买家来说，这些数据提供了训练能够预测故障的模型所需的真实情况，这是在预计到 2025 年将达到 136.5 亿美元的市场中至关重要的能力。
See dimension details ↓- Dataset Specificity90
主导的 'iot_data'，行业工业，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 Demand90
人工智能买家需求极高，这得益于预测性维护市场的快速增长，该市场正以 24.30% 的复合年增长率扩张。
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，KCK Group（投资者/所有者）的子公司
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 License36
所有权=混合，许可=权利不明确
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence50
KCK Group（投资者/所有者）的子公司
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 — 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 Audit75
⚠ 审查 — 该公司的核心业务是销售人工智能驱动的软件平台 (Pyxis) 和机器人硬件来优化仓库物流，使其成为智能/人工智能软件供应商，而不是合适的目标。问题：核心产品是销售智能/人工智能软件 (Pyxis 工作流管理)，这属于明确的排除标准。[14, 17]；该公司已从 IAM Robotics 更名为 Onward Robotics，这标志着战略上转向以软件为中心、人到货物的自动化模式。[14, 15]；他们的商业模式是机器人即服务 (RaaS)，客户为系统提供的运营效率付费，而不是为物理产品付费。
- Deep Qualification70
✓ 通过 — 该目标（现为 Onward Robotics）销售完整的仓库自动化解决方案，结合了 AMR 和软件，包括 RaaS 选项。这使其成为运营 AMR 遥测数据的首要数据持有者。然而，数据所有权可能与客户混合，其隐私政策在转售运营数据的权利方面不明确。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
持有者从其机器人的本地化系统生成时间序列传感器数据，包括来自多传感器融合的信号，这对于构建能够检测多个组件异常的复杂模型至关重要。
Industrial data
这是机器人导航工业环境并与人类工人协调的运营数据，提供了用于准确维护预测的设备使用和压力模式的真实记录。
Event streams
该公司从其协调机器人和人类的协同系统捕获事件流，为买家提供关于人类互动如何影响设备性能和可靠性的独特情境数据，尤其是在仓储运营中。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Iamrobotics Industrial Sensor — a Moderate industrial sensor dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market = $13.65B in 2025, CAGR 24.30% (source: Fortune Business Insights). Investment score 48.0/100 (confidence 0.49). Recommended action: Partnership (group-level).
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