Automated evaluation of IoT sensor data – efficiency through cloud reporting

From manual Excel calculations to a central IoT platform: temperature and humidity data is automatically collected in the cloud, evaluated and made available in standardized reports.

Customer

Customer benefits

Automated data evaluation instead of manual Excel calculations
Standardized database for transparent decisions and traceability
Future-proof platform that can be flexibly adapted to new projects & requirements
Early warning messages when limit values are exceeded to prevent damage

Technology stack

Frontend: Angular, TypeScript
Backend: Python (FastAPI)
Cloud & database: MS Azure App Service, Azure SQL
Further services: Azure Secret Server, Azure Networking, E-Mail Service
Data sources: Multisense & MSR sensors, weather APIs

"The new platform makes our work much easier - we can evaluate data immediately, create reports and have transparency about critical values at all times."

Challenges of the customer

Moisture on windows quickly leads to mold – the causes range from leaking insulation to inadequate ventilation. With our customer Previously, we worked manually with individual sensors, whose measured values were calculated in Excel and transferred to PDF reports. This process was time-consuming, error-prone and could only be used selectively. With the use of new Multisense sensors the need arose for a platform that could reliably record, manage and analyze large volumes of data – while at the same time offering flexibility for different projects and buildings. The goal was a solution that not only delivers precise limit value calculations, but also enables reporting, notifications and long-term data archiving.

Our approach

Step-by-step development into a scalable platform: Starting from a local application for individual data records, a cloud solution was created that processes thousands of measured values in a structured manner and visualizes them in a user-friendly way.

Basic system & PDF reports

First, a program was created that could upload and process CSV data from sensors and generate standardized PDF reports - including diagrams, statistics and automatically calculated maximum humidity.

Cloud architecture & database

A scalable Azure architecture was established with the use of multisense sensors: FastAPI backend, Angular frontend and Azure SQL database ensure that sensor data is continuously processed and available at all times.

Project & task structure

Flexible project management allows measurement jobs to be organized down to room level. Measurements can be assigned to individual apartments, buildings or projects - including coordinates, logger management and automatic data assignment.

Visualization & notification system

Clear dashboards with filter and export functions provide insight into temperature and humidity curves. A notification system informs you by e-mail about critical limit value violations or daily humidity reports.

Optimization of performance & data quality

Down-sampling algorithms (Largest Triangle Three Buckets) ensure that even large amounts of data are visualized with high performance. Weather data is also compared from two APIs in order to subsequently validate modeled values with measured data.

Results for the customer

Duration of report generation per measurement job (previously several hours)

< 0 min

Automated data transfer from sensors to the platform

0 %

Further results:

Automated PDF reports for internal documentation and customer verification
Better basis for decision-making thanks to standardized data and comprehensible reports
Faster response times thanks to automatic alerts to prevent damage in good time
Cost reduction and risk minimization through less manual work for damage repair

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