10 posts tagged with "iot"

MQTT is a common choice for the communication stack in IoT and robotics applications because it is lightweight and easy to integrate. But many of those applications do not send only small JSON telemetry messages. They also publish JPEG frames, vibration waveforms, audio clips, protobuf messages, and other binary payloads that need to be stored and queried later.

This is where a regular MQTT broker or a traditional time-series database starts to fall short. Brokers are designed for message delivery, not long-term historical storage, and many databases either expect structured numeric fields or make it hard to keep large binary records tied to accurate timestamps.

In this tutorial, we will use ReductBridge to subscribe to MQTT topics and write the raw binary payloads into ReductStore with a time index. This lets you keep camera frames and sensor payloads as they are, while still querying them by time range, labels, and entry name for replay, debugging, and offline analysis.

As modern manufacturing becomes increasingly data-driven, the need for efficient data acquisition systems is more critical than ever. In my previous article, Building a Data Acquisition System for Manufacturing, we discussed the challenges of data acquisition in manufacturing and how ReductStore can help solve them. Here we will learn how to use ReductStore at the edge of the shop floor and stream data to the cloud.

Large manufacturing plants generate vast amounts of data from machines and sensors. This data is valuable for monitoring machine health, predicting failures, and optimizing production. It also serves as a foundation for building industrial AI models for predictive maintenance, quality control, and process optimization.

A Data Acquisition (DAQ) system collects this data, processes it, and stores it for further analysis. It typically consists of edge devices that gather real-time data, central servers or cloud storage for retention, and software that enables analytics and AI-driven insights.

Traditional automation solutions like SCADA and historians are complex, expensive, and not optimized for modern cloud-based AI applications. They often limit access to data, making it difficult for engineers and data scientists to develop machine learning models and gain actionable insights.

In this article, we’ll explore the challenges of building a modern DAQ system for manufacturing and how ReductStore can simplify the process and support ELT (Extract, Load, Transform) workflows for advanced analytics and AI applications.