Software

Excited by Machine Learning for intelligence at the edge? Make sure it’s the right tool for your job.

IoT devices can generate a lot of data, and of course there is a natural interest to apply machine learning techniques to look for trends and patterns. Of course, we have plenty of tools up in the cloud, and it is certainly possible to build a solution this way for some use cases. The next

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Anomaly Detection For IoT Using Open Distro For ElasticSearch

This post is the third in series on using the AWS ecosystem for IoT applications. Previously, we integrated AWS IoT with Timestream /Quicksight and ElasticSearch/Kibana. Why # Anomaly detection is the foundation for applications such as Predictive Maintenance, which in turn is the driving force behind most industrial IoT deployments. Now that the essentials of sensors, communication, storage and visualisation have

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Websockets for Hardware Engineers – Part 1

Before we start, what is HTTP? # This is what HTTP REST looks like…ClientServerIdentify Yourself!SSL HandshakeAuthenticateAuthorizeMake a RequestAsk for dataSend dataTypical Client-Server FlowClientServerIdentify Yourself!SSL HandshakeAuthenticateAuthorizeMake a RequestSend dataAcknowledgeA bit later… We noticed some issues… # Each request is preceded by an SSL handshake (if HTTPS) and authentication This can consume significant resources (CPU, time, memory) each time

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