Dataset opportunity
Autonomousagrisolutions — 工业传感器数据集机会
由 Autonomousagrisolutions 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
71.1
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
49%
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 = 2025 年为 142 亿美元，复合年增长率为 27.9%。
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-09-02
Robotti is back: UK company Autonomous Agri Solutions steps in to secure the robot’s future
futurefarming.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.
Concrete evidence this company actively cares about data — why it's ripe for the deal room.
- ✨Signal
专注于传感器融合和自主导航系统
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 — 许可权待澄清
Buyer persona
工业人工智能与维护优化供应商
Autonomousagrisolutions 持有一个专有的工业传感器数据集，该数据集源自其在英国各地运营的自主农业车队。数据以时间序列模式捕获，包含 `industrial_data`、`iot_data` 和 `image_collection`，以提供全面的运营视图。这个丰富、多模态的数据集非常适合开发预测性维护模型，因为它会跟踪设备的健康状况和性能随时间的变化，从而能够在发生机械故障之前进行预测。
全球预测性维护市场在 2025 年的价值为 142 亿美元，预计到 2033 年将以 27.9% 的复合年增长率增长。[2] 虽然访问需要处理与农场所有者之间的数据所有权分割以及从车辆边缘系统进行技术提取，但该数据集对英国农业地形和作物类型的特定性使其成为一项独特且稀有的资产。这种特定性对于构建欧洲农业部门高度准确的 AI 模型至关重要，证明了投资访问的合理性。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据所有权可能在公司和农场所有者（最终用户）之间分割；需要从自主车辆边缘系统进行技术提取；数据高度特定于英国农业地形和作物类型。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同证明了持有者拥有来自真实自主农业机械的稀有、专有的工业传感器数据。这包括来自定制工程项目的宝贵的时间序列和运营数据，使其成为训练复杂AI 模型的独特资产。对于工业人工智能领域的供应商而言，这些数据直接支持了高价值预测性维护解决方案的开发，该市场预计到 2025 年将达到 142 亿美元。该数据集的特定性和稀有性在这个快速增长的行业中提供了独特的竞争优势。
See dimension details ↓- Dataset Specificity90
主导的 'iot_data'，工业部门，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
AI 买家需求极高，这得益于预测性维护市场的快速扩张，该市场正以 27.9% 的复合年增长率增长。[2]
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 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 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 Independence90
独立
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation39
1 个数据胃口信号（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，1 个近期外部信号 — 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
✓ 良好目标 — 该公司是一家英国中小企业，销售、租赁和维修农业机器人；其“机器人即服务”产品产生的运营数据是一项有价值的副产品，而非其核心销售产品。[1, 2, 5] 问题：该公司的核心业务是提供“机器人即服务”和销售设备；在客户农场合同工作中生成的数据的所有权是
- Deep Qualification80
⚠ 需要审查 — 目标是第三方农业机器人的授权经销商和服务提供商，而非车队运营商；因此，运营数据由其客户（农民）生成和拥有。[数据由公司客户拥有]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
这是时间序列数据，捕获了自主拖拉机系统的核心运营日志，包括 GPS 和转向控制，这对于对组件行为和磨损进行建模至关重要。
Image collection
该数据集包括来自障碍物检测系统的图像和 LiDAR 数据，提供了一个有价值的多模态层，用于将视觉异常与潜在的设备故障相关联。
Industrial data
这是在执行自主任务和定制工程项目期间生成的、高度专有的时间序列数据，为在非标准操作条件下训练模型提供了独特的来源。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Autonomousagrisolutions 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 = $14.2B in 2025, CAGR 27.9% (source: Grand View Research). Investment score 71.1/100 (confidence 0.49). Recommended action: Acquire.
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