What if the IoT era starts 2019, is the cloud ready?

IoT: smart homes are connected to the cloud

Edge computing — the response to the IoT problems

In 2016–2017 Microsoft introduced their Azure IoT Edge service, Google Cloud released their Cloud IoT Core, AWS had improved their IoT offers and introduced lots of new features during AWS re:Invent 2017. Meanwhile, a bunch of lesser cloud providers like DigitalOcean and IBM is also seizing their opportunity to get a share of the future IoT market.

  • Data filtering to hot and cold. If there are hundreds of equal signals from identic sensors (like the temperature control network of a plant sending the same values during normal operation), only one signal is transmitted from the IoT node to the cloud for logging, and the rest are discarded — the so-called cold data (1).
    However, if any sensor shows a change of value (2), this means an anomaly (like a fire starting or a short circuit happening), so the signal is also processed according to a response scenario (an alarm is raised and the firefighting systems are activated in the affected zone) — the hot data, which requires action at once.
  • Hot data processing within the node. The aforementioned response scenarios should be handled by Machine Learning models deployed inside the IoT node. The ML algorithms themselves are first trained in the cloud using vast arrays of historical cold data, but the trained models take as little as 1GB of disc space and can efficiently run inside the IoT node. (3)
    Due to such structure, hot data can be handled on-site and the responses can be issued within milliseconds, while cold data is sent to the cloud and used in the ongoing ML model training process(4). For example, when a small batch of sensors registers a gust of wind with gravel that threatens the wind power station, the whole wind farm adjusts the positions of rotors to avoid damage.
  • Regular ML model updates. The more historical data is available to the ML model, the better it can predict the needed outcomes. Therefore, the local instances of the model deployed within the IoT nodes must be updated from time to time, so a secure connection channel and an error-proof CI/CD pipeline must be established to ensure the system is operating efficiently.
  • Internet coverage stability and safety. With regards to the issues of possible burglaries of smart homes or self-driven car crashes, the stability of Internet coverage and the security of connections is another major concern. Many companies like AT&T in the US and Vodafone in the U.K. are planning to launch 5G networks to provide sufficient access to the Internet for smartphones and other connected devices.
Are we ready for the IoT era?

Conclusions on the cloud readiness for the IoT

The possible solution to this dilemma is delivering more personalized IoT applications and systems. While being developed for a specific purpose, these apps can make the IoT implementation feasible in the long run. For example, if the same system of IoT nodes was used for managing the city lights, city traffic control system, self-driving cars, and traffic surveillance, handling the consumer apps synchronization, etc. — that would make it feasible.



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