Dataset opportunity
Edgecomenergy — 传感器遥测数据集机会
Edgecomenergy 持有的中等规模传感器遥测数据集，可用于预测性维护和异常检测。
Score
47.5
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在 2024 年的价值为 123 亿美元，预计到 2033 年将以 29.7% 的复合年增长率增长（来源：Custom Market Insights）。[6]
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.
- 📦Data product
pTrack™：利用历史和实时电网数据进行人工智能驱动的峰值预测
source ↗
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
部分
Legal
混合所有权 — 清晰可授权
Buyer persona
工业人工智能与维护优化供应商
Edgecomenergy 持有一个有价值的传感器遥测数据集，其中包含来自部署在客户现场的专有物联网传感器的数据的时间序列模态数据。这些丰富的工业数据，包括事件流和物联网数据，捕获了真实的运营性能，使其非常适合开发和验证旨在预测设备故障的预测性维护模型。
该数据的商业价值在全球预测性维护市场中得到体现，该市场在 2024 年的价值为123 亿美元，预计将以29.7% 的复合年增长率扩张。[6] 虽然访问需要处理客户-供应商数据共享协议，但核心价值在于聚合、匿名化的工业负荷剖面，它们提供了稀缺的跨行业洞察，在人工智能应用中需求量很大。⚠ 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收集，但代表工业客户托管；访问需要处理客户-供应商数据共享协议；主要价值在于跨不同行业的聚合、匿名化的工业负荷剖面。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据证实 Edgecomenergy 拥有来自其自有物联网硬件在电表和子电表级别直接捕获的专有实时工业能源数据流。这个精细的时间序列数据集是人工智能供应商构建预测性维护和能源优化模型的重要资产。在全球年增长近 30% 的市场中，该数据在预测高风险能源事件方面的已证实能力使其成为训练复杂资产管理算法的稀有且宝贵的资源。
See dimension details ↓- Dataset Specificity74
主导的'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 Demand95
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 29.7% 的复合年增长率扩张。[6]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility50
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 License58
所有权=混合，授权=清晰
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 — 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 Audit58
⚠ 审查 — 该公司的核心业务是销售人工智能驱动的能源管理软件和智能，因此作为现有市场的一部分，它不适合。问题：核心业务是销售智能/人工智能软件（AI Energy CoPilot, pTrack®, dataTrack™）以优化能源使用。[5, 9, 12, 14]；该公司的产品被明确描述为“一体化能源管理解决方案”和“人工智能驱动的能源管理和优化平台”。[8, ; 该公司的价值主张是提供数据洞察和分析，这是一项服务/产品，而不是将休眠数据作为副产品出售。[3, 13]；首席执行官曾表示，他们的核心业务是“预测这些工业设施的能源价格和能源需求”。[14]
- Deep Qualification90
⚠ 需要审查 — 目标公司销售人工智能驱动的能源管理软件和分析，而不是休眠数据；其核心业务是将客户的运营数据转化为可操作的洞察。[4, 12, 16] “传感器遥测数据集”标签与其收集实时工业物联网数据的业务一致。[7, 10, 11] 虽然原始数据所有权可能属于客户，但该公司的隐私政策允许无限期保留和使用聚合、匿名化数据。[17] 最近的一个触发因素是 2025 年 1 月的 250 万美元种子轮融资，用于扩展其人工智能平台并进入美国市场。[4, 5] [将数据/智能作为核心产品出售；商业模式 = 数据销售商]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Industrial data
持有者收集实时运营能源数据，这是自动化排放跟踪和工业客户 ESG 报告的人工智能平台的关键输入。
IoT / sensor data
该数据集包含由专有物联网硬件捕获的精细能源消耗数据，提供了训练精确资产监控和优化算法所需的高分辨率信号。
Event streams
该集合包含历史和实时事件流，这些事件流已成功用于预测高风险能源峰值，直接证明了该数据在构建高精度预测模型方面的价值。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Time Series, JSON
License
One-time license for use in predictive maintenance model development and validation, subject to client-vendor data sharing agreements.
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 proprietary, real-time industrial sensor telemetry dataset is highly valuable for predictive maintenance due to its granular, time-series nature and the significant growth in the predictive maintenance market. Its rarity and direct capture from IoT hardware drive its premium valuation.
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
Edgecomenergy 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 market was valued at $14.2 billion in 2025 and is projected to grow at a CAGR of 27.9% (source: Grand View Research). Investment score 47.5/100 (confidence 0.49). Recommended action: Acquire.
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