Example Concept: Edge processing involves deploying computational resources closer to data sources, such as sensors and devices, to perform data filtering, aggregation, and analysis locally. This reduces the need to transmit large volumes of raw data to the cloud, thereby minimizing latency and bandwidth consumption. Edge devices can execute machine learning models for real-time decision-making, ensuring that only relevant insights are sent to the cloud for further processing or storage.