Dataset opportunity
Fido — 工业传感器数据集机会
Fido 持有的海量工业传感器数据集,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
92%
Action
许可
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 136.5 亿美元,复合年增长率为 24.30%。
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
工业传感器数据集
Modality
时间序列
Sector
工业
Volume
大
Freshness
实时
Rarity
高(专有)
Accessibility
开放/API
Legal
混合所有权 — 易于许可
Buyer persona
工业人工智能与维护优化供应商
Fido 持有专有的工业传感器数据集,该数据集由第三方公用事业网络上的声学传感器生成。这些时间序列数据代表了海量的声学特征库,直接适用于预测性维护,因为声音的变化可能预示着设备即将发生故障。该数据集的特点是数据量大、真实的工业数据模式以及与物联网数据应用的直接相关性。
全球预测性维护市场在 2025 年的价值为136.5 亿美元,预计到 2034 年将以24.30% 的复合年增长率增长。尽管存在数据所有权澄清和这是一个海量未标记的声学库等访问复杂性,但该数据集的稀有性和规模使其具有非凡的价值。它提供了一个独特的机会,可以在难以获得的真实运行声音上训练强大的 AI 模型。⚠ 尽职调查(有价值的数据,可协商的访问权限):数据通过部署在第三方公用事业网络上的专有物联网传感器生成;原始声学特征与公用事业网络元数据的所有权需要合同澄清;公司已通过 SaaS 获利,但拥有海量未标记/休眠的声学库。· 公司:独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据证明了拥有一个大规模的专有时间序列数据集,每年捕获来自工业水管传感器的超过 5400 万个独特声学数据点。这些独特数据是预测性维护模型的关键燃料,能够以超过 92% 的验证准确率检测和定位昂贵的漏水。对于以 136.5 亿美元的工业维护市场为目标的人工智能供应商来说,该数据集提供了一个难得的机会来开发和部署高度准确、可审计的解决方案,以服务于公用事业和市政部门。其在减少非收入用水方面的已证明能力,使其成为一个快速增长且注重资源的市场的引人注目的资产。
See dimension details ↓- Dataset Specificity100
主导的“物联网数据”,工业领域,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 Rarity70
专有领域数据(开放会降低稀有度)
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume100
17 个证据命中,明确提及数据量
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 Demand90
强劲的买家需求源于预测性维护市场的快速增长,预计复合年增长率为 24.30%,而此类独特的时间序列数据至关重要。
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility90
开放/API 访问
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility84
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
7 种证据类型,17 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,许可=干净
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 — 专有数据超出已获利部分
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 — Fido Tech 的核心业务是销售用于漏水检测的人工智能驱动软件、分析和智能(SaaS/DaaS),这使其成为一个糟糕的匹配项,因为它已经在销售智能,而不仅仅是持有休眠数据。问题:公司核心产品是销售人工智能/智能,这是明确的排除标准;被描述为“数据即服务”和“SaaS”模式,这是一个糟糕的匹配项;该公司没有产生副产品数据的主要运营业务;其业务就是数据分析服务;他们使用的数据来自其客户的网络(公用事业、公司),而不是来自他们自己的“真实运营业务”。
- Deep Qualification60
✓ 通过 — Fido Tech 是一家 SaaS 提供商,销售人工智能驱动的漏水检测服务,使其成为有价值的声学传感器数据集的`数据持有者`。然而,数据所有权和许可权不明确,因为数据是在第三方公用事业网络上生成的,需要合同澄清。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
这些证据指向核心时间序列数据,该数据是从部署在水管上的声学 物联网传感器网络捕获的,用于监测漏水情况。
Data-volume signal
这些证据量化了数据集的规模,每年超过 5400 万个独特的数据点,并通过模型验证测试证明了其质量,这些测试显示准确率超过 92%。
Downloads / exports
这些针对业务需求的下载手册证据表明,在漏水问题上存在明确的商业重点,表明市场应用明确。
Geospatial data
这些证据证实了表格数据的存在,该数据将漏水事件映射到特定的GIS坐标,从而能够为漏水检测团队进行可视化和优先级排序。
Developer portal
这些证据表明英国和美国存在内部开发人员和技术团队,这意味着拥有管理和维护数据收集平台所需的运营基础设施。
Industrial data
这些证据明确证实了该数据集在工业环境中的应用,包括用于监控大规模供水管网的传感器数据。
Regulatory records
这些证据证明了数据输出是根据公认的科学方法论进行验证的,提供了对受监管公用事业部门客户至关重要的可审计结果。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Fido Industrial Sensor — a Large industrial sensor dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market = $13.65B in 2025, CAGR 24.30% (source: Fortune Business Insights). Investment score 47.5/100 (confidence 0.92). Recommended action: License.
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