From sensor data to predictive insights

Many organizations collect large amounts of IoT data from machines, sensors and installations. Yet this data often remains underutilized.

IOT APPS helps organizations combine IoT data with the knowledge of their own domain experts. This creates practical Machine Learning solutions for predictive maintenance, process optimization and cost reduction.

What is AIoT (Artificial Intelligence of Things)?
IoT data generally consists of structured data with timestamps that are generated by connected devices in the cloud.

This data provides an excellent foundation for machine learning. In addition, context such as maintenance reports, fault logs and operational notes can be used to improve models.

This creates AIoT: a combination of sensor data, contextual data and domain knowledge.

Why small AI models often work better than large AI systems
Unlike large AI systems such as Large Language Models (LLMs), which require enormous datasets and heavy infrastructure, AIoT models are often:

• specific to a single process or installation
• faster to develop
• cheaper to train and maintain
• deployable without GPU infrastructure

This makes AIoT particularly suitable for industrial applications where reliability, predictability and cost are more important than general intelligence.

The power of combining: data + domain expertise
IoT data shows what is happening, but not why.

By combining this data with the knowledge of operators, maintenance technicians and process technologists, more explainable models and better predictions can be created.

The limitations and opportunities of AIoT models
Small AI models are efficient and practical to deploy, but without context they often have limited value.

By adding domain knowledge, models become more powerful through:

• input from experts
• data enrichment
• feedback loops

As a result, models improve not only technically, but also remain aligned with practical needs.

Our Machine Learning Platform
IOT APPS has developed a Machine Learning Platform that supports organizations throughout the entire AIoT process: from raw IoT data to operational decision-making.

• collecting and structuring IoT data
• combining data with expert knowledge
• training and managing AI models
• making predictions
• improving based on feedback

The platform is designed for use by both technical and non-technical stakeholders, without requiring in-depth data science knowledge.

Applications of AIoT
AIoT is widely applied in industrial environments, including for:

• predictive maintenance
• cost control and efficiency improvement
• process optimization
• performance improvement of machines and installations

Accessible to all stakeholders

Through user-friendly web interfaces, different stakeholders can:

• add insights based on their expertise
• assess operational situations
• directly view results and predictions

No experience with data analysis or BI tools is required to work effectively with the system.

Interested in the possibilities of your IoT data?
Would you like to know what value your IoT data can deliver within your organization?

Contact us for a no-obligation consultation. We would be happy to show you which predictive applications are possible with your existing IoT data.
T: 0402960040