IoT Data Platforms and Real-Time Analytics
IoT generates massive amounts of data. In 2025, we developed a platform that ingests sensor data via MQTT and stores it in InfluxDB.
Dashboards and Anomaly Detection
Grafana dashboards provided real-time visualizations, while machine learning models detected anomalies in the data. The system is scalable and can handle thousands of devices.
Our IoT expertise can help you harness your sensor data.
Frequently Asked Questions
What stack do you use for IoT data platforms?+
We use MQTT for sensor data ingestion, InfluxDB for time-series storage, Grafana for real-time dashboards, and machine learning models for anomaly detection—scalable to thousands of devices.
How do you detect anomalies in IoT data?+
Machine learning models analyze the sensor data stream to detect anomalous patterns in real time, alerting operators before issues escalate.
Need help building this?
Kimpuler engineers production-grade systems for enterprises. Let's discuss your project.
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