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The article deals with optimization of input data for wireless IoT devices with database handled by cloud framework. Tested hardware consists of ESP32 board with WiFi technology support (Thinger.IO cloud platform) and Sensor Tag development boards with integrated sensors and Bluetooth connection communicating with IBM Watson IoT framework. The new idea is how to send optimized measured data to IoT platform which is limited to one message per second usually. We propose two separate approaches for input data: accumulation data in IoT device to multi-value packet and noise elimination solved by advanced interpolation (Kalman filter). Both principles can be combined to reduce noise and increase of data frequency stored in cloud platform for next knowledge datamining. Data accumulation can be used for machine or product vibration analyses (acceleration data packed during 1 second) in cloud platform. Interpolated data can remove noise from actual product operational speed (gyroscope/magnetometer corrected value) to reduction false alarm messages in cloud framework.

Data optimization for communication between wireless IoT devices and Cloud platforms in production process