![]() Copy the value of the 'SkillLambdaFunctionQualifiedArn' parameter - the first line shown below: $ cat stack.json Īfter completion, inspect the results of stack.json of the current directory. Go back to its parent directory and copy the data/stack.json file to src/config/stack.json, and then run the 'serverless deploy' command again: cd. Go to the 'data' directory and run the 'serverless deploy' command: cd data Then, go to the dasBridge directory and run npm install: cd dasbridge On the machine, clone the dasBridge skill code: git clone If you've got problems, feel free to address in the comments below. On the examples below, we'll be using Linux commands, but it shouldn't be hard to translate those to Windows. AWS Account, with Access Key Id and Secret Access Key, Administrator Group Access Level, with awscli configured under the us-east-region.Machine with both git and nodejs installed - desktop recommended, regardless of being Windows or Linux.Be able to install the Go Language on the Raspberry Pi.Basic Raspberry Pi and Linux skills (install a package, open a shell session and run commands and download/unpack packages).Basic Arduino Skills (assemble a circuit, compile and upload a sketch).An Amazon Web Services Account to deploy the code, as well as a account.Basic node.js skills (installing node and running npm), regardless of windows and Linux.In order to build this, its required to the user the ability to: At the same time, leverage as much as possible from the Device Shadow API, while ensuring enough isolation On the worst case, rely on CloudWatch Period Events, and/or AWS Step Functions. Rely as much as possible on an AWS Serverless Stack in order to heavily reduce costs.Using TypeScript to ensure correctness on the server side with an Average Performance and Good Productivity, while Golang + Gobot + Firmata on the Device Side will work as a good prototyping environment, offering both performance, portability and performance - while with average productivity levels. ![]() Considering the price for an Arduino Board + a Raspberry Pi (W or not) + card + USB Power, it looks like the 'IoT Tax' (read: the cost to connect a device) for the average maker could be safely around USD 20 per device, which is acceptable Using Arduino as a gateway to the underlying hardware whenever possible, and leave the middleware to Raspberry.However, time constraints held us back - we might reconsider doing it at a later point) (In fact, this still was originally built to be sent straight to Alexa Skills' Certification. By this, we mean that we've already built the wheel, do you don't have to reinvent it. It was meant to be easily extensible, thus acting as the core fabric for your next Smart Home SkillsĭasBridge is meant to serve as a template for a pure, enterprise grade device gateway. Generic Smart Relay (ditto, except with Relays).Color Lamp (Bare Golang + Custom Arduino Firmware + NeoPixels).Generic Temperature Sensor (using GoBot + Arduino with Firmata + BMP280).Clients using either GoBot or custom Firmware to allow one to integrate their devices to Amazon's IoT Gateway.Boilerplate configuration for AWS, using the Serverless Framework.Boilerplate code for a generic Alexa Smart Home Bridge, supporting a couple of interesting devices (Temperature, Color Lamp, and Smart Relay).In order to prove it, we built dasBridge, a platform which aims to solve address the main pain points in building Alexa Smart Home Devices for the Maker. Publishing Alexa's Smart Home Skill for a Maker doesn't need to be hard.
0 Comments
Leave a Reply. |