With the explosion of the Internet of Things in recent years, it is no surprise that Google would want to get developers involved using the Android OS. The resulting product is Android Things (first released in May 2018), a version of the Android OS specifically designed for IoT devices. Based on the same operating system as Android phones, Android Things simplifies the development process and makes creating IoT programs the same procedure as a phone or watch app, but the available libraries are different depending on the IoT hardware.
While Elasticsearch is primarily used as a search engine, the platform has recently become more widely used in a variety of analytics tasks, including the ELK Stack of Elasticsearch, Logstash, and Kibana for real time analysis of large datasets. Elasticsearch also shows great potential in the realm of IoT, in which hundreds of data sources must be monitored in real time. Through optimized searching of time series data, Elasticsearch can be integrated with RESTful web services such as Spring Boot to provide users with real time visualizations of their sensor data.
Speech recognition is a technology we have been interested in for a while. Some of our earlier projects include integrating Alexa with Slack and creating an Alexa skill to aid with inventory management. We have been eager to work with speech recognition again since attending this year’s SpeechTek conference in Washington, DC. Excited to apply some of the lessons we learned and develop something both interesting and practical, we set out to create a smart digital assistant with Jasper.
AR and VR technologies have been a key trend for a while now, and many are saying that augmented reality will be the “new mobile” in terms of the next major platform. The tech is increasingly becoming more accessible to developers, especially in the AR market. This is evidenced by Apple’s announcement of ARKit, Aryzon’s cardboard for mixed reality, and Occipital’s low-cost AR/VR tracking platform.
We recently tested Rekognition’s image detection capabilities with photos from a cell phone camera, so next we decided to automate the process with photos from a Raspberry Pi camera module. We used a motion sensor we had set up in one of our previous projects to begin work on our desired motion-activated identity verification system. With that in mind, we set the Raspberry Pi and camera up on a desk in one of our office rooms, pointed it at the door, and got to work.
In a slight change of pace from our recent explorations of Internet of Things platforms, we started digging into Amazon’s recently announced Rekognition service. Rekognition is a powerful image processing service capable of detecting faces, people, objects, and subtle photo elements such as scene and sentiment.
As with any augmented reality device, the HoloLens has the ability to overlay content on the physical world. The content can take on a number of different forms such as simple 2D gauges or complex 3D models. No matter what the content type is, it has to be positioned somewhere in the physical world. This is where content locking comes in. We have put together an example of each type of content lock option that is available for the HoloLens along with a few notes on each.
We’ve begun to explore potential use cases for virtual reality, and decided to start with creating a virtual office tour – which we believe can be an effective recruitment tool for new employees.
This is part of a running commentary for a project that our Labs team is working on. We are interested in non-visual user interfaces. Broadly, interfaces that consider the use of people’s other modes of interacting with the world: speaking, hearing, feeling, and gesturing. So we decided to start playing around with the Amazon Echo.