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  1. Last 7 days
    1. Real-Time Embedded Systems

      A real time embedded system is a small computer built inside a device that does specific jobs and gives results within a fixed time. It is called “real time” because it must respond quickly without delay, like in car airbags, traffic lights, or medical machines. These systems are designed to be fast, reliable, and accurate since even a small delay can cause problems. In simple words, it is a hidden computer inside machines that makes sure they react and work at the right time.

  2. Jul 2025
    1. Google offers Firebase Realtime Database, a cloud-hosted NoSQL database, as a component of the Firebase product suite. It offers programmers a scalable and adaptable way to create real-time applications that need data to be synchronized across several clients.

      Learn how to convert Firebase Realtime Database data into a list view in Flutter. Step-by-step guide to display dynamic content efficiently with Firebase and Flutter integration.

  3. Nov 2024
  4. Jun 2024
  5. Aug 2023
      • for: extreme weather, realtime extreme weather analysis, World weather attribution
      • description
        • the World Weather Attribution organization is a group of research institutes that provides robust scientific answers to the question:
          • is climate change to blame?
        • when an extreme weather event has occurred
        • This is usually available days to weeks after the event and informs discussions about climate change while the impacts of the events are still fresh in the minds of the public and policymakers.
  6. Mar 2023
  7. Jun 2017
  8. Dec 2015
    1. Why use Storm? Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm is simple, can be used with any programming language, and is a lot of fun to use! Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate. Storm integrates with the queueing and database technologies you already use. A Storm topology consumes streams of data and processes those streams in arbitrarily complex ways, repartitioning the streams between each stage of the computation however needed. Read more in the tutorial.

      stream computation