Kx for IoT turns on the lights

GitHub: Kx and IoT, turning on the lights with kdb+/q

23 Sep 2016 | , , ,
Share on:

Expert Kx developer JP Armstrong recently added an interesting kdb+/q project to GitHub.

It is a small web application to control the lights in his apartment. It does this by wrapping Philips Hue’s comprehensive REST API into simple functions that turn on/off lights, change “scene”, and schedule light changes through URL GET calls. The project also comes with the ability to get today’s sunset time and schedule the lights to turn on 30 minutes in advance.

Check out JP’s project on GitHub.

Here is info on Philips Hue.

SUGGESTED ARTICLES

Signal processing in kdb+

Signal processing with kdb+

6 Sep 2018 | , ,

In the latest in our ongoing series of kdb+ technical white papers published on the Kx Developer’s site, Kx engineer Callum Biggs examines how kdb+/q can be used instead of popular software-based signal processing solutions. Signal processing is used for analyzing observable events, such as IoT sensor data, sounds, images and other types of pulses […]

Rust, meet q

24 Aug 2018 | , , ,

by Rahul Powar Red Sift is a Kx Technology Fund partner that provides a data analysis platform that is purpose-built for the challenges of cybersecurity. By leveraging the elegance of kdb+ and the power of Rust to create data applications, Red Sift can process data at the rate of tens of GB/second on consumer grade […]

Kx Insights: Machine learning subject matter experts in semiconductor manufacturing

9 Jul 2018 | , ,

Subject matter experts are needed for ML projects since generalist data scientists cannot be expected to be fully conversant with the context, details, and specifics of problems across all industries. The challenges are often domain-specific and require considerable industry background to fully contextualize and address. For that reason, successful projects are typically those that adopt a teamwork approach bringing together the strengths of data scientists and subject matter experts. Where data scientists bring generic analytics and coding capabilities, Subject matter experts provide specialized insights in three crucial areas: identifying the right problem, using the right data, and getting the right answers.