We were inspired by the idea of creating a friendly and simple way to access the world around us. Our initial idea began with the idea of using dust and humidity sensors to judge air quality with the scope expanding to the ideal situation of being able to easily add add varieties of IoT devices and sensors.

What it does

A Qualcomm Snapdragon 410C using a Grove Base Board uploads sensor data to Amazon DynamoDB tables which the Amazon Alexa skill accesses via Lambda functions.

The Echo will ask the user what kind of data they want to access and will retrieve the most recent value and respond to the user.

How we built it

Amazon Web Services have been used to store all necessary sensor data and for communication between IoT devices and the Amazon Echo.

C++ is used to gather sensor data from our three sensors, temperature, sound, and light. Python scripts are then used to upload this data to DynamoDB tables accessible through a Lambda function for use by the Alexa Skill.

Challenges we ran into

Setting up the Qualcomm Snapdragon 410C proves difficult. Recommended libraries proved buggy and inconsistent therefore requiring us to use the Base Board and the Qualcomm like an Arduino with C++ gathering the sensor data and Python being used to upload the data to DynamoDB.

We got the board successfully communicating with AWS, but never got the system fully setup to correctly implement data into the DynamoDB.

Accomplishments that we're proud of

Successfully pulling data from a DynamoDB tables using an Amazon Echo and learning about Amazon Web Services.

What we learned

  • Amazon Web Services
  • Alexa Skills
  • IoT Development

What's next for MultiSense

  • Accessibility to more kinds of sensors.
  • Ability to add more IoT devices using the Amazon Echo.
  • Improved coding efficiency and flexibility.
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