Dataset opportunity
Minut — 传感器遥测数据集机会
Minut 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
48
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
83%
Action
数据共享协议
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 134 亿美元,复合年增长率为 23.2%。
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
实时噪声、入住率和气候监测洞察
source ↗
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
中等
Accessibility
部分
Legal
公司所有 — GDPR 敏感(个人身份信息审查)
Buyer persona
工业人工智能与维护优化供应商
Minut 持有其安装在住宅物业中的硬件生成的专有传感器遥测数据集。此时间序列数据包括噪声水平、温度、湿度和运动等指标,提供了丰富的连续环境和设备健康信息流,非常适合训练预测性维护模型以预测硬件故障或异常环境条件。
该数据在全球预测性维护市场中具有极高的价值,该市场在 2025 年的估值为134 亿美元,预计将以 23.2% 的复合年增长率增长。[1] 尽管访问复杂性要求对住宅数据进行严格匿名化并进行数据所有权合同验证,但该数据集的稀有性质和注重隐私的设计(无摄像头或音频录制)使其成为在快速扩张的市场中开发下一代人工智能解决方案的抢手资产。⚠ 尽职调查(有价值的数据,可协商访问):数据通过私人住宅中的专有硬件传感器收集,需要严格匿名化;注重隐私的设计(无摄像头/录音)简化了某些方面,但限制了原始音频访问;原始遥测数据与客户洞察的所有权需要合同验证。· 公司:独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
公开证据证实 Minut 拥有其专有物联网传感器生成的海量时间序列数据。该数据集捕获了真实的现实世界环境条件,包括温度、湿度、噪声和入住率水平,这些对于训练预测性维护算法至关重要。对于工业和维护优化领域的 AI 供应商而言,这些数据为开发更准确的模型提供了直接途径,以应对预计到 2025 年将达到 134 亿美元的全球市场。获取这种独特的遥测数据可以显著加速产品开发,并在快速扩张的行业中增强竞争优势。
See dimension details ↓- Dataset Specificity62
主导型 'iot_data',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 Rarity46
专有领域数据(开放性降低稀有度)
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 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 Demand90
人工智能买家需求异常高,这得益于全球预测性维护市场以 23.2% 的复合年增长率快速扩张,因为公司越来越多地采用物联网和人工智能来减少运营停机时间。[1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility60
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,10 个命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License62
所有权=公司所有,许可=GDPR 敏感
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 Audit75
⚠ 审查 — Minut 是一个糟糕的目标,因为其核心业务是销售基于订阅的智能服务,提供来自其专有传感器数据的实时洞察和分析,使其成为一个智能供应商,而不是休眠数据的持有者。问题:该公司的核心产品不是硬件传感器本身,而是提供“主动物业洞察”和分析的基于订阅的软件平台;这种销售分析和警报访问的商业模式是一种“服务型智能”,明确被 ICP 排除为“糟糕的目标”;该公司已在其产品中使用人工智能和机器学习,例如用于烟雾检测和客户沟通,这证实了它销售智能;他们提供商业 API 供客户访问传感器数据并构建自定义集成,这表明存在清晰、现有的数据货币化策略。[21]
- Deep Qualification70
✓ 通过 — Minut 是一个数据持有者,拥有高度一致的利基数据集。最近的 B 轮融资延期提供了一个强烈的触发因素,但其法律文件中并未明确定义数据所有权,这造成了一个关键的尽职调查障碍。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Event streams
该公司运营实时事件流,用于跟踪入住率等物业状况,提供动态人工智能模型所需的连续数据流,以优化资源分配。
API access
提供了一个现代化的、基于 REST 的API,使买家能够以最小的工程工作量,以编程方式将传感器数据集成到他们自己的系统和人工智能工作流中。
IoT / sensor data
该数据集包含详细的物联网数据,包括温度、湿度和设备电池电量,这些是训练高价值预测性维护模型的直接输入。
Developer portal
存在一个带有 API 文档的开发者门户,这表明数据结构良好且得到支持,从而减少了买家工程团队的集成摩擦。
JSON files
使用JSON有效负载证实数据以标准、机器可读的格式交付,确保与现代人工智能开发堆栈的即时兼容性。
Knowledge base / docs
一个带有 API 文档的技术知识库进一步证明了数据的成熟度,让买家对数据集的可用性和长期价值充满信心。
Downloads / exports
一个具有下载功能的面向客户的 Web 应用程序表明存在一个已建立的机制,用户可以通过该机制检索可用于批量数据交付的文件。
Marketplace
Dataset details
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
Minut 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 = $13.4 billion in 2025, CAGR 23.2% (source: Market.us). Investment score 48.0/100 (confidence 0.83). Recommended action: Data Sharing Agreement.
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