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Telemetry data collected from freight trucks is streamed in real time to Kafka in Confluent Cloud to provide a vast source for analysis using Confluent’s Flink service and detect trends regarding delivery delays, optimal delivery routes, and other optimization problems that can help identify cost efficiencies and improve customer experience. This use case explores detecting speeding in the fleet of trucks specifically but can be expanded to more complex analysis.
Obtain Real-Time Insights and Optimize Freight Logistics with Apache Flink on Confluent Cloud
Experience the power of real-time data analysis with this Apache Flink demo, seamlessly integrated with Confluent Cloud. You can Stream telemetry data from freight trucks directly to Kafka and leverage Confluent's Flink service to uncover actionable insights.
You could detect delivery delays, optimize routes, and solve critical logistics challenges to enhance cost efficiency and elevate customer satisfaction. Transform your freight operations with cutting-edge analytics and drive smarter decisions effortlessly.
Detect problems in your operation in real time.
Optimize the placement of your resources and make decisions as events happen.
Base your decision on fresh and live data rather than snapshots.
Build with Confluent
This use case leverages the following building blocks in Confluent Cloud:
Reference Architecture
Trucks continuously deliver messages about vehicle fleet, speed, distance traveled, and load weight.
EKS cluster receives the events from the sensors (or this layer could be replaced by an IoT gateway/connector if transformations are not needed), and sends them through the Kafka Cluster for analysis via Flink.
Confluent Cloud hosts the Kafka Cluster and Flink Compute pools that will be used to analyze and aggregate the data.
Resources
Contact Us
Contact Ness to learn more about this use case and get started.