Dataset opportunity
Waste — 传感器遥测数据集机会
Waste 持有的海量传感器遥测数据集，可用于预测性维护和异常检测。
Score
79.4
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
73%
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在 2025 年的估值为 136.5 亿美元，预计在 2026-2034 年期间的复合年增长率为 24.30%。
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-08-11
California Makes Progress on Organic Waste Despite Challenges
wasteadvantagemag.com ↗ - 📰press2026-08-10
Reworld, Goodwill of NEPA Announce Free E-Waste Recycling Program
waste360.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.
Profile
Dataset profile
Type
传感器遥测数据集
Modality
时间序列
Sector
其他
Volume
大型
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
聚合/第三方 — 许可权待澄清
Buyer persona
工业人工智能与维护优化供应商
此传感器遥测数据集提供高频时间序列数据，非常适合预测性维护应用。它融合了来自超声波和图像传感器的 `iot_data`、来自不同废物流的 `industrial_data` 以及相应的 `maintenance_logs`，全面展示了废物收集基础设施的资产性能和故障模式。
全球预测性维护市场在 2025 年的估值为136.5 亿美元，预计将以24.30% 的复合年增长率增长。[1] 虽然访问需要处理 5,000 多个站点的使用权并整合混合数据源，但该数据集的价值是巨大的。它包含来自制造、零售和医疗保健行业的专有基准数据，这种跨行业细节提供了构建独特准确且可泛化的人工智能模型的稀有且强大的基础。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据来自加拿大 5,000 多个客户站点，需要明确的使用权进行二次货币化；专有基准数据来自多行业废物流（制造、零售、医疗保健）；访问涉及物联网传感器数据（超声波/图像）和第三方承运商日志的混合。· 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 Waste Solutions 拥有其“WasteMetric”技术平台的传感器遥测专有数据集。这些独特的时间序列数据，跟踪容器的装满程度和服务历史，是工业人工智能供应商构建预测性维护和路线优化模型的关键资产。在全球市场预计每年增长超过 24% 的情况下，该数据集为优化工业运营和服务计划提供了显著的竞争优势。
See dimension details ↓- Dataset Specificity86
主导的 'iot_data'，行业其他，4 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 Rarity94
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume94
10 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 Value94
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 Demand92
人工智能买家需求极高，这得益于预测性维护市场的快速扩张，预计复合年增长率为 24.30%。[1]
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 Strength100
5 种证据类型，10 次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License18
所有权=聚合，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，2 个近期外部信号 — 超出已货币化范围的专有数据
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 — 俄克拉荷马州这家运营型废物管理中小企业是一个不错的目标，因为它提供实体废物收集服务，并且似乎不销售数据或情报产品。问题：初步提示中提到的‘传感器遥测数据集’似乎是推测性的；公司网站上没有直接证据表明他们使用传感器遥测
- Deep Qualification60
✓ 通过 — 该目标是一家废物管理服务提供商，传感器遥测数据是其‘WasteMetric’平台的合理副产品。然而，数据所有权和许可权完全未知，因为没有找到面向客户的法律文件，这代表了一个重大的尽职调查差距。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
持有者运营着一个生成智能传感器数据的专有技术平台，该平台直接提供训练预测性维护和物流优化算法所需的实时时间序列遥测数据。
Event streams
这些证据指向结构化的事件流，这些事件流集中了运营数据，如填充水平和服务成本，为验证人工智能模型性能提供了关键的地面真实指标。
Knowledge base / docs
该公司维护着一个监管和合规性文件的知识库，为构建在特定市政或区域规则内运行的模型提供了至关重要的上下文数据。
Maintenance logs
该数据集包括服务历史和重量报告，这些报告是标记事件和训练用于预测性服务的监督学习模型所需的关键维护日志。
Industrial data
这些证据证实了用于跨不同行业进行基准测试的聚合工业数据的存在，从而能够开发更健壮和可泛化的人工智能解决方案。
Marketplace
Dataset details
Detailed schema & sample available on access request.
Coverage
Scanned sources
Deliverable
Premium dataset report
Waste Sensor Telemetry — a Large sensor telemetry dataset (Time Series modality) in the other domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market was valued at USD 13.65 billion in 2025, projected to grow at a CAGR of 24.30% (2026-2034). [1]. Investment score 79.4/100 (confidence 0.73). Recommended action: Acquire.
From the marketplace
Explore live data opportunities
Anyshape — 检验报告数据集机会
View opportunity →工业Merit3D — 工业运营数据集机会
View opportunity →工业3Deo — 知识库数据集机会
View opportunity →