ATM Fraud Detection with Apache Kafka and KSQL | Confluent

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This post details building an end-to-end IoT motion detection and alerting system using Confluent Cloud and ksqlDB. It covers hardware choices (Raspberry Pi Zero W), software components (Motion, librdkafka, Docker), and the architecture for ingesting motion events into Kafka. The system utilizes ksqlDB for real-time stream processing and querying, enabling both real-time monitoring with push queries and historical event search with pull queries. The UI is built with React and Next.js, demonstrating a practical application of stream processing for fraud detection. Specifically, it showcases how ksqlDB can be used for stream-stream joins within a time window to identify fraudulent ATM transactions based on account, location, and time proximity.