Intelligent interactive LED experience system

Gesture lighting control

Gesture control of the lighting environment involved in the third experiment. The Ultra High Dynamics 2.0 sensor is used to allow the user to control the brightness of multiple light sources by pointing a person's finger on the object to activate its natural interaction. By pointing to the light source with your right hand finger, you can adjust the brightness of your individual's light by raising and lowering your left arm. Source code and technical details are available below.

The world of interactive LED experiences is growing rapidly. There are many technical options available to become available digital content creators to explore this immersive medium. I hope these experiments will stimulate more exploration. The interactive model that looks forward to seeing creativity is defined as taking advantage of the unique shape of this new media and enabling LEDs to be ubiquitous in display potential.

Technical failure

For all of these experiments, the technology NeoPixel LED module from Adafruit was used. NeoPixels are WS2812 integrated light sources that are individually addressed and can be linked together.

Also used is open source hardware FadeCandy comes with OS X, Windows, OpenWRT, and raspberry PI platform compatible server software. It has, for example, client-side processing languages, Python and Node.js, Javascript and C++. Develop a library, cinder creation coding framework, you can download it here, and patch the environment for VVVV, you can find a customer here.

For mobile experiments, use an Android app to process the FadeCandy client. The raw pressure data used is converted from the phone's barometric sensor to a high degree of Java code. By setting a zero point pressure on the first floor you can determine the height of the elevator in real time. Android processing client code used in mobile experiments can be downloaded here.

For wireless control of light displays, use the OpenWRT feature of the router. The optical server is set up on the router to receive messages from the WiFi client and then pass the data to the LED strip through its built-in USB port by customizing the OpenWRT package. This way any device with a WiFi radio can become an optical interaction interface through its onboard touch screen and / or sensor.

For the gesture experiment, the skeleton used tracks the ability of the new Kinect 2.0 sensor. Kinect 2.0 has many new features that greatly increase the effectiveness of gesture interaction. The new sensor is based on the "flight time" of the technology, not the sensor based on the front of the projected structured light pattern. This means it guarantees an effective depth reading, thus making each image more stable in depth images. This is also a higher resolution and improved human tracking algorithm. The result is the ability to track hands and fingers in fidelity from impossible with old ultra-high dynamics. This new ability is exploited from the user's wrist by calculating its indicated direction and determining the virtual vector projected by the intersection with the predetermined target object in space. In this case, two small lights are displayed.