A company deploys thousands of connected sensors in various remote locations to monitor environmental data and relay it to an analytics platform. Network links are intermittent, and the company wants to keep critical data available while reducing data traffic to the cloud. Which solution addresses this goal?
Set up a large high-performance computing solution in each remote location
Have personnel collect logs and review them before uploading summaries
Forward all sensor readings directly to the analytics platform
Use a small gateway onsite that processes readings and sends essential metrics to the central platform
A localized gateway offering basic data analytics handles preliminary filtering, minimizing the amount of data transported and retaining key information locally if the link is down. Sending everything to the cloud strains bandwidth, large high-performance setups often exceed project scope, and manual checks lack scalability and reliability. The local gateway approach combines efficient data use with fallback capabilities.
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What is a gateway in the context of IoT (Internet of Things)?
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What filtering or processing can a localized gateway perform?
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Why is a full high-performance computing setup not suitable for remote IoT locations?