Dataset opportunity
Libelium — Industrial Sensor Dataset Opportunity
Large industrial sensor dataset held by Libelium, usable for Predictive Maintenance and Anomaly Detection.
Score
88.5
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
License
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
The global predictive maintenance market was estimated at **USD 14.29 billion in 2025** and is projected to reach **USD 98.16 billion by 2033**, growing at a **CAGR of 27.9%** from 2026 to 2033.
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-02
LoRa Alliance Sets Three-Year Plan to Make LoRaWAN Easier to Integrate and Operate
iotbusinessnews.com ↗ - 📰press2026-06-01
Mocking a Year of IoT Sensor Time Series Data with Mimesis
kdnuggets.com ↗ - 📰press2026-05-28
Nordic Extends AI Assistance from Firmware Development to Deployed IoT Fleets
iotbusinessnews.com ↗ - 📰press2026-05-28
AT&T Moves Deeper Into Supply Chain IoT Through Wiliot Collaboration
iotbusinessnews.com ↗ - 📰press2026-05-27
MWC 2026 signals a split IoT connectivity market shaped by AI, NTN and eSIM orchestration
iotbusinessnews.com ↗
Concrete evidence this company actively cares about data — why it's ripe for the deal room.
- 📦Data product
iris360: Data Management Platform for IoT, Data Spaces, and Digital Twins
source ↗ - 📦Data product
envair360: AI service for environmental monitoring
source ↗ - 📦Data product
grid360: Efficient Energy Transmission solution
source ↗ - 📝Published article
Company states 'We capture the data that transforms the world. We empower decision-making with data.'
source ↗ - 📣Press / announcement
Libelium integrates customized IoT projects and consulting services into business model, focusing on data intelligence
source ↗
Profile
Dataset profile
Type
Industrial Sensor Dataset
Modality
Time Series
Sector
industrial
Volume
Large
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Open / API
Legal
Mixed ownership — clean to license
Buyer persona
Industrial AI & maintenance-optimization vendors
Libelium holds a diverse collection of Industrial Sensor Datasets, primarily in a Time Series modality, originating from various sensor types and deployments across the industrial sector. This rich, high-frequency data, encompassing parameters like temperature, vibration, and pressure, is highly valuable for Predictive Maintenance applications, enabling the detection of early signs of equipment degradation and the identification of failure patterns.
Despite the data being primarily customer-owned, requiring agreements for access, its value is substantial due to the significant cost of unplanned downtime in industries, which can exceed USD 1 million per hour in high-precision sectors. AI-driven predictive maintenance, powered by such rare and granular data, offers a compelling ROI of 10:1 to 30:1 within 12-18 months, leading to 30-50% reductions in unplanned downtime and 18-25% lower maintenance costs. The demand from AI buyers for this type of data is strong, driven by the need for enhanced operational efficiency and cost reduction. ⚠ Diligence (valuable data, access to negotiate): Data is primarily customer-owned, requiring agreements with clients for access.; Data is diverse, originating from various sensor types and deployments.; Company's primary focus is on providing IoT solutions and insights, not raw data sales. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
- Dataset Specificity100
dominant 'iot_data', sector industrial, 4 specific types
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity70
proprietary domain data (open lowers rarity)
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume100
19 evidence hits
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness82
real-time/streaming
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value94
fit for Predictive Maintenance
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand92
The global predictive maintenance market, which heavily relies on industrial sensor data and AI, is projected to grow at a CAGR of 27.9% from 2026 to 2033, indicating very high demand for this type of data.
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility90
open/API access
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility84
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength100
7 evidence types, 19 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License58
ownership=mixed, licensing=clean
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence90
independent
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation84
5 data-appetite signals (3 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
surplus=high, 5 recent external signals — proprietary data beyond what's already monetised
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
⚠ review — Libelium is a well-established SME that provides IoT hardware, software, and consulting solutions, enabling customers to collect and utilize data for intelligence, which places them too close to the 'selling intelligence' category to be a good target for dormant data. Issues: Libelium's core business is providing IoT solutions and enabling data intelligence, which means they are already active in the data/intelligence market, making ; While Libelium manufactures sensors and platforms
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Libelium, a proven IoT hardware manufacturer and solutions provider, possesses a proprietary Industrial Sensor Dataset directly applicable to predictive maintenance. This rich Time Series data, evidenced by its use in digital twin applications for critical infrastructure like power grids, is invaluable for Industrial AI & maintenance-optimization vendors. With the predictive maintenance market projected to reach USD 98.16 billion by 2033, this dataset offers a unique opportunity to develop advanced AI models that drive operational efficiency and reduce costly downtime.
IoT / sensor data
This section confirms Libelium's core expertise in connecting sensors to the cloud and delivering IoT solutions, specifically generating Time Series data from diverse environments, including smart cities and environmental monitoring.
Data catalog / marketplace
This evidence highlights Libelium's advanced capabilities in IoT device management, participation in data sharing frameworks like EU Data Acts, and integration of Digital Twins, underscoring their structured approach to data governance and accessibility.
Downloads / exports
This evidence comprises public reports and financial statements, confirming Libelium's robust business operations and significant financial growth, indicating a stable and expanding source of proprietary data.
Industrial data
Crucially, this directly confirms Libelium's generation of industrial Time Series data for predictive maintenance and digital twin applications, with specific examples like power grid monitoring at high temporal resolution.
Developer portal
This portal clearly establishes Libelium as an IoT hardware manufacturer and solutions provider, demonstrating their capability to design and produce the physical sensors that generate industrial data.
Event streams
This demonstrates Libelium's capacity for handling real-time data streams to create detailed virtual models, further supporting the potential for dynamic industrial monitoring and simulation.
Geospatial data
This showcases Libelium's expertise in collecting and processing environmental sensor data, such as air quality and noise, with high spatial granularity, which can be critical for site-specific industrial insights.
Coverage
Scanned sources
Deliverable
Premium dataset report
Libelium Industrial Sensor — a Large industrial sensor dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: The global predictive maintenance market was estimated at **USD 14.29 billion in 2025** and is projected to reach **USD 98.16 billion by 2033**, growing at a **CAGR of 27.9%** from 2026 to 2033.. Investment score 88.5/100 (confidence 0.92). Recommended action: License.