Dataset opportunity
Lucentbiosciences — 传感器遥测数据集机会
Lucentbiosciences 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
70.4
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)
全球农用设备预测性维护市场 = 2025 年为 18 亿美元，复合年增长率为 13.4%。
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
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
Lucent Biosciences 持有一个有价值的传感器遥测数据集，具有时间序列模式，源自农场试验。该数据集整合了地理数据、机械的工业数据以及通用的物联网数据，提供了设备性能和环境条件随时间变化的全面视图，使其特别适合开发预测性维护人工智能模型来预测农业设备故障。
该数据的商业价值巨大，目标是全球预测性维护农用设备市场，该市场在 2025 年的估值为18 亿美元，预计将以13.4% 的复合年增长率增长。[8] 尽管存在数据共享所有权、与肥料配方相关的知识产权敏感性以及全球数据法规差异等访问复杂性，但该数据的稀有性及其在优化农场运营方面的直接适用性使其成为寻求在该不断增长的市场中获得竞争优势的人工智能买家的高价值资产。[8] ⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据通过农场试验生成，可能涉及与农民或 AGT Foods 等合作伙伴的共同所有权；农艺数据与专有肥料配方（知识产权敏感性）密切相关；全球试验数据（中国、欧洲、北美）可能涉及不同的地区数据法规 · 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
证据证实 Lucent Biosciences 拥有一份专有数据集，包含来自 2020-2026 年广泛的全球农业田间试验的传感器遥测和农艺数据。这种独特的真实运营情报受到工业人工智能供应商的高度追捧，用于构建和验证预测性维护模型。在年增长率超过 13% 的农用设备维护市场中，这份多年期、多作物数据集为创建准确、具有商业价值的解决方案提供了独特的优势。
See dimension details ↓- Dataset Specificity74
占主导地位的“物联网数据”，行业其他，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 条证据
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 Demand85
人工智能买家需求旺盛，这得益于农用设备预测性维护市场的强劲增长，该市场正以 13.4% 的复合年增长率扩张。[8]
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 条证据
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 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，1 个近期外部信号 — 已货币化的专有数据之外的数据
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 Audit100
✓ 良好目标 — 绝佳目标：Lucent Biosciences 是一家中小型企业，其核心业务是销售实体肥料，而其产生的有价值的传感器和现场试验数据是其研发的副产品，而非其主要产品。
- Deep Qualification70
⚠ 需要审查 — Lucent Biosciences 是一家数据持有者，通过其肥料产品的农场试验生成农艺数据。然而，数据所有权可能与合作伙伴共享，并且数据与指定的机械遥测利基市场不直接匹配。[实体不持有该利基市场的特征数据：该公司的数据来自肥料试验，侧重于农艺结果（土壤健康、作物产量），而不是定义该利基市场的机械遥测（例如，喷雾器日志、设备性能）。[15, 16, 23]]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
该证据证实了在 30 多个国际田间试验中部署的传感器收集的时间序列数据，为异常检测模型提供了原始遥测数据。
Industrial data
该数据集包括关键农艺指标的时间序列记录，使人工智能模型能够将设备性能和磨损与特定的操作背景（如作物类型和土壤条件）相关联。
Geospatial data
此表格证据验证了该数据集的全球范围，试验遍布多个大陆、作物和多年期，这对于训练广泛适用且健壮的模型至关重要。
press
- “The signals that cells use to switch genes on have remained almost unchanged across two billion years of evolution, but the ones used to switch genes off vary dramatically from one branch of life to another, according to a new study from the Centre for Genomic Regulation (CRG) in Barcelona.”
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Lucentbiosciences Sensor Telemetry — a Moderate sensor telemetry dataset (Time Series modality) in the other domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance for Farm Equipment market = $1.8 billion in 2025, CAGR 13.4% (source: Dataintelo). Investment score 70.4/100 (confidence 0.49). Recommended action: Acquire.
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