Dataset opportunity
Moocall — 传感器遥测数据集机会
Moocall 持有的中等传感器遥测数据集，可用于预测性维护和异常检测。
Score
68.3
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
全球牲畜监测市场在 2024 年的价值为 46.1 亿美元，复合年增长率为 15.2%（来源：Polaris Market Research）
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
传感器遥测数据集
Modality
时间序列
Sector
其他
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
公司所有 — 许可权待澄清
Buyer persona
工业人工智能与维护优化供应商
Moocall 持有一个专有的传感器遥测数据集，该数据集由其物联网设备在数千个农场收集的时间序列数据组成。该数据集提供了详细的事件流和物联网数据，专门捕获与产犊事件相关的牛行为，因此非常适合开发用于牲畜健康和福利的预测性维护模型。
全球牲畜监测市场在 2024 年的估值为 46.1 亿美元，预计将以 15.2% 的复合年增长率增长。[4] 尽管存在访问复杂性，例如需要验证匿名化历史传感器流的商业化权利，但该数据集的高度特异性和稀有性带来了巨大的机遇。市场的快速增长凸显了对这种专业数据以训练优化农场运营和动物健康的 AI 模型的需求。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据通过专有物联网传感器从数千个第三方农场聚合而来；需要验证匿名化历史传感器流用于第三方 AI 训练的商业化权利；数据集高度特异于牛行为和产犊事件 · 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据证明了持有者拥有海量的专有传感器遥测数据集，直接关联到超过一百万个已标记事件——即实际的牛分娩。这种独特的时间序列数据集合是工业 AI 供应商开发用于蓬勃发展的精准农业领域的预测性维护算法的金矿。随着全球牲畜监测市场每年增长超过 15%，该数据集提供了一个难得的机会，可以大规模训练和验证预测关键、时间敏感结果的模型。
See dimension details ↓- Dataset Specificity62
主导的'物联网数据'，行业其他，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 Volume68
3 个证据命中，明确的数据量提及
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 Demand80
AI 买家需求强劲，这得益于快速增长的牲畜监测市场（复合年增长率 15.2%）以及对专业数据以训练预测性健康模型的需求。[4]
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 次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License70
所有权=已拥有，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 Orientation56
2 个数据需求信号（2 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 Audit100
✓ 良好目标 — Moocall 是一个理想的目标；它向农民销售基于硬件的警报服务，并以此为副产品，积累了来自牛的大量专有且目前未货币化的传感器遥测数据流。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
持有者拥有高频时间序列数据，传感器每秒收集超过 600 个数据点，以精确跟踪动物行为，提供先进预测模型所需的详细输入。
Event streams
该数据集包含超过一百万个已确认的已标记事件（牛分娩）的大规模流，提供了大规模训练和验证监督式预测算法所需的关键真实数据。
Data-volume signal
这些证据证实了数据集的规模相当可观，通过商用级物联网平台捕获了超过一百万次分娩，展示了构建企业级AI 解决方案的成熟度和可靠性。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Time Series
License
One-time license for commercial use, subject to verification of anonymization and commercialization rights for historical streams.
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 dataset's value is driven by its high rarity as proprietary sensor telemetry for a niche but rapidly growing livestock monitoring market. The demand is amplified by its direct application in predictive maintenance for animal welfare and health.
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
Moocall Sensor Telemetry — a Moderate sensor telemetry dataset (Time Series modality) in the other domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Livestock Monitoring Market was valued at USD 4.61 billion in 2024, CAGR 15.2% (source: Polaris Market Research). Investment score 68.3/100 (confidence 0.49). Recommended action: Acquire.
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