Dataset opportunity
Acgpulse — 工业传感器数据集机会
Acgpulse 持有的中等规模工业传感器数据集，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
56%
Action
合作（集团层面）
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 年的价值为 136.5 亿美元，预计将以 24.30% 的复合年增长率增长（2026-2034 年）。
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-09-24
ACG Pulse AB — Sweden – Data-transmission equipment – RFID-taggar till textilier
ted.europa.eu ↗
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
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
Acgpulse 持有的宝贵工业传感器数据集，由其客户部署的 RFID 硬件（包括机柜和门）生成。该数据集主要由来自事件流和物联网源的时间序列数据组成，捕获了理想的聚合使用和流量模式，可用于开发预测性维护模型以预测硬件故障。
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。虽然访问需要从专有的 Q-Web 软件进行技术提取，并且详细的数据所有权归最终客户所有，但聚合的iot_data代表了针对这个利润丰厚市场的 AI 买家一个稀有且有价值的休眠资产。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据通过客户部署的 RFID 硬件（机柜、门）生成；详细的库存数据的所有权可能归最终客户所有；Q-Web 云平台上的聚合使用和流量模式代表了主要的休眠资产；需要从专有的 Q-Web 软件生态系统进行技术提取 · 公司：ACG Gruppen 的子公司。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同证明 Acgpulse 拥有其工业传感器和 RFID 系统生成的专有时间序列数据，用于资产跟踪和库存管理。该数据集直接适用于开发预测性维护和库存优化模型的工业人工智能供应商。在一个年增长率超过 24% 的市场中，这些稀有数据提供了构建和验证高价值人工智能解决方案所需的真实依据，以实现仓库自动化和工业效率，从而提供显著的竞争优势。
See dimension details ↓- Dataset Specificity90
占主导地位的 'iot_data'，行业为工业，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 Volume58
4 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
AI 买家需求极高，这得益于市场从 136.5 亿美元以 24.30% 的复合年增长率快速扩张。
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility40
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 Feasibility0
中等难度，ACG Gruppen 的子公司
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength74
4 种证据类型，4 次命中
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 Independence50
ACG Gruppen 的子公司
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation56
2 个数据需求信号（2 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 — 超出已货币化数据的专有数据
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 Audit58
⚠ 审查 — 该公司的核心业务是销售基于 RFID 的物流和库存管理系统，而不是作为其他运营的副产品生成数据。问题：核心业务是销售技术解决方案（RFID 硬件和软件），其中包括分析和数据洞察作为产品功能；该公司没有自己的运营业务（如车队或工厂）作为副产品生成专有数据；它为其他公司提供系统；它处理的数据（例如，服装位置、库存水平）属于其客户，而不是 Acgpulse 本身。
- Deep Qualification70
✓ 通过 — Acgpulse 是一个数据持有者，销售基于 RFID 的物流系统并生成聚合使用数据作为副产品。数据所有权很可能是混合的，详细数据属于客户，而聚合数据的许可权不明确，但可能受 GDPR 管辖，因为它们可能跟踪员工活动。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Developer portal
该公司确认拥有内部开发团队，负责硬件和软件的开发，向买家保证拥有一个支持良好且专业管理的生成数据基础设施。
IoT / sensor data
Acgpulse 使用RFID 技术生成时间序列数据，以监控整个物流流程中的物品，提供对维护和供应链人工智能至关重要的详细资产跟踪数据。
Industrial data
该数据集包括关于库存状态、使用情况和物品移动的实时数据，这对于训练专注于库存优化和需求预测的人工智能模型至关重要。
Event streams
该公司从其仓库系统中捕获连续的事件流，提供详细的可追溯性日志，这是对资产使用模式进行建模和预测故障的基础。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Acgpulse Industrial Sensor — a Moderate industrial sensor dataset (Time Series modality) in the industrial 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) (source: Fortune Business Insights).. Investment score 47.5/100 (confidence 0.56). Recommended action: Partnership (group-level).
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