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How do gateways perform local data processing to cut latency?
Asked on Nov 07, 2025
Answer
Gateways perform local data processing by leveraging edge computing capabilities to handle data near the source, reducing the need to send all data to the cloud and thereby cutting latency. This is particularly effective in IoT systems where real-time decision-making is crucial, such as in industrial automation or smart cities.
Example Concept: Gateways equipped with edge computing capabilities process data locally by filtering, aggregating, and analyzing sensor inputs before transmitting only essential information to the cloud. This reduces data volume, minimizes latency, and allows for faster response times in critical applications. By using protocols like MQTT or CoAP, gateways can efficiently manage communication between devices and the cloud, ensuring that only relevant data is sent for further processing or storage.
Additional Comment:
- Gateways often use lightweight machine learning models to perform real-time analytics.
- They can act as intermediaries, translating different protocol communications between devices and cloud services.
- Local processing helps in scenarios where immediate feedback or action is necessary, such as in predictive maintenance.
- Security is enhanced by reducing the exposure of raw data to external networks.
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