NearForm clocks in with hackable open source JavaScript AI smartwatch
The Irish county town of Kilkenny is known for its medieval buildings and castle, its rich history of brewing, its distinctive black marble and as the home of White House architect James Hoban.
In more recent times, Kilkenny has become known as the home of the NodeConf EU conference, a coming together of Node.js specialists who all gravitate towards this open source cross-platform JavaScript runtime environment that executes JavaScript code outside of a browser.
This year’s event saw NearForm Research and Espruino surprise delegates by giving out something better than plain old lanyards and name tags — the two companies came together to offer an arguably rather more exciting Machine Learning (ML)-driven smartwatch to act as attendee’s conference badges.
Bangle.js is said to be the first open source JavaScript (JS) smartwatch to be powered by Machine Learning via Google’s TensorFlow Lite. It is hoped to be a step towards the mainstream adoption of JS and ML in low cost consumer electronics.
Developers will be able to create their own AI applications for the Bangle.js device.
It comes pre-loaded with features and apps including: GPS, compass, heart rate monitor, maps, games and gesture-control of PC applications over Bluetooth.
“Bangle.js is not just about a single device, codebase or company. I believe it has the potential to bootstrap a community-driven open health platform where anyone can build or use any compatible device and everyone owns their own data. Machine Learning is a critical aspect of health technology and we’re so pleased to be further involved in the TensorFlow open source project,” said Conor O’Neill, chief product officer for NearForm.
County Waterford headquartered NearForm is known for its professional technology consultancy work with both local Irish and international companies spanning a range of industries. “Everything we do emanates from open source,” insists the company.
Watch-makers
The team took a reasonably powerful off-the-shelf smartwatch and ported the Espruino code to the device so that all of its sensors were accessible to JavaScript programmers.
This first Bangle.js device can also be easily disassembled with just a screwdriver for ease of fixing and replacing its parts.
The teams also ported the Micro version of Google’s TensorFlow Lite to the watch to give it Machine Learning capabilities with input from Google’s TensorFlow community. They then designed an ML gesture detection algorithm which is built into every watch and enables the user to control applications, including PowerPoint, with hand gestures.
The companies explain that even ‘lapsed’ and non-programmers can also interact with Bangle.js using Blockly or low-code Node-RED.