CNC Controller in Python

Technical Challenge

Typically, Computer numerical control (CNC) machine controllers are implemented in C or C++ and run on OSless or real-time operating systems. For example, Linux by default is not a real-time operating system. And running projects like LinuxCNC requires adding special real-time features to the kernel.

Some of these approaches seem to be quite old-fashioned. Modern ARM processors allow using high-level programming languages like Python to provide easy development, flexibility, and migration between hardware.

About the Project

This is the first ever CNC machine

Machine Learning for Asset Management

About the Client

The client is a EU-based startup company. They use an automated approach to monitor their installations for utility companies. Their main objectives are managing assets and improving maintenance processes using fast drones.

Business Challenge

The client collects images of the objects maintained using drones. The images are collected at high speed, and not all the images contain useful information. This increases the need for a human workforce to filter the images before processing.

The business challenge was to improve the

DeviceHive 3.2.0 is released

DataArt’s IoT team is proud to release a new version of the open source IoT platform DeviceHive.

This update improves general performance and stability, introduces new API features, and enables Kubernetes cluster deployment.

Please see the details about the recent changes below:

Server:

  • Added the Hazelcast microservice module.
  • Added the device\list websocket command.
  • Removed Device Class.
  • Removed Device Equipment.
  • Network key removed, Device key removed, Device Guid renamed to ID.
  • Updated Swagger auth model (api_key could be used between API calls).

Big Data News Digest for June, 2017

Most of the time when a warehouse transforms into a datalike, question arises on how to normalize/denormalize the data. As an intro you can read an article, and follow the guidelines for deploying an IBM Industry Model to Hadoop.

To get an insight into a new highload big data platform you can read a blogpost on the keen website that highlights the architecture of several giants from a 10000 ft view.

Again serverless architectures are coming, the number of