Considering the need for real$-$time data processing and bandwidth optimization in an IoT$-$driven agricultural environment, which computing setup would best suit an extensive network of soil and climate sensors spread across a large geographic area?

Considering the need for real$-$time data processing and bandwidth optimization in an IoT$-$driven agricultural environment, which computing setup would best suit an extensive network of soil and climate sensors spread across a large geographic area?

Fog Computing: Utilize local computers and edge devices for data processing before sending it to the central cloud for further analysis, optimizing both local responsiveness and centralized data collection.

Distributed Cloud Computing: Implement cloud services distributed geographically close to sensor locations to ensure data locality and low latency without the need for local storage or processing.

Edge Computing: Process data directly on IoT devices or nearby edge servers to minimize latency and reduce bandwidth usage, crucial for real$-$time agricultural decision$-$making.

Traditional Cloud Computing: Centralize all data processing in a single cloud$-$based system to simplify management and utilize powerful cloud$-$based analytics