Issue #2 of Confluent Chronicles: The Force of Kafka + Flink Awakens | Read Now
IoT Data Integration for Real-Time Processing
Tap into the power of data streaming to seamlessly integrate data and drive real-time analytics from IoT sensors and connected devices. Create new revenue models and transform your trucking operations to stay ahead of your competition.
Elevate Decision-Making with Trucking Analytics
With a combination of MQTT, a lightweight messaging protocol, and Confluent’s cloud-native data streaming platform, vehicle logistics companies can continuously integrate data and unlock real-time insights across applications, systems, and IoT devices such as GPS tracking, Electronic Logging Devices (ELDs), tire pressure monitoring systems, and maintenance devices. Below are some of the use cases you can power.
Predictive maintenance
Route optimization
Drive monitoring for compliance
Build with Confluent
This use case leverages the following building blocks in Confluent Cloud.
Reference Architecture
The reference architecture below shows how to capture data with MQTT, process and store with Confluent Cloud, and then deliver the enriched data back to downstream consumers and customers.
Use an MQTT client to collect GPS and ELD data from IoT devices and send it to an MQTT broker.
Confluent has a fully-managed MQTT connector that is perfect to easily integrate your MQTT broker with a Confluent Cloud cluster.
Stream processing is a core piece of distributed systems and pivotal to quickly process this IoT data in flight rather than in a batch method. As an example, you can easily filter out trucks that have accumulated 1,000s of miles and could require maintenance soon.
Once the data is in Confluent, you can use various tools to move data to the right place for the right job. For example, you can use a connector to AWS S3 for long-term storage or Snowflake for data warehousing.