|5min||Review Deadlines|| |
- Sprint completion 7/28/2017
- August 15th finish prototypes and final design
- July-Early August, purchasing for devices
- Early September begin build process of devices with ULL/David Thibodaux students
- We need to start thinking when and where we would deploy our next sensor prototypes, and what sensors those prototypes will include.
- Will discuss this at sensor placement planning meeting tomorrow
- Deploy new algorithm to sensor boxes after 7/17/2017 at 1pm central
- Log the current & new algorithms and compare the differences. (Will email LCG to gain access to the sensor boxes after meeting)
- Did not get to it last week, but will dedicate all work for this Sprint on Wednesday, 7/26/2017.
- Set up DEV API pointing to new keyspace in Cass cluster
- Create ticket for this sprint
- Duplicate steps used for Prod API
- Confirm steps needed for Thing token validation
- Hardware status:
- Alphasense higher quality PM sensors, 5 ordered
- Communicating, but not sure if correctly
- Still working on this
- Krulick, Daniel (CGI Federal) is looking at the power regulator
- Received power regulator evaluation board - testing now
- Inventory Management
| ||Firmware and device management|
- Add new datastreams to account for new sensors. (Possibly make new sample.py type of files for specific sensor boxes)
- LEARN-106: Cascade on deletion complete
- LEARN-154: Ensure HistoricalLocation is created for new locations
- LEARN-147: Request Bamboo CI build plan for API code
- Build plan is for Kinota repo, which won't be ready until LEARN-148 and LEARN-187 are complete.
- Created LEARN-188 as a follow-up issue.
- LEARN-148: Clean up code for OSS release
- Waiting for code review
- Due to upcoming vacation of Miles, Brian (CGI Federal) the code clean up has been broken into two issues. LEARN-187 details the remaining code clean up issues that need to be completed before open source release.
| ||Visualization and Use Cases|
| || Architecture & Analytics||Chepudira, Karthik (CGI Federal) |
- Worked on connectivity between sensors and azure IOT directly via MQTT - Done
- Setting up MQTT bridge with X.509 certificates - Done
- Validate mapping for Azure Iot Hub device endpoint and thingid (deviceid) in azure function -Done
- Plan to setup MQTT broker to map STA topics to Azure IoT topics - Done
- Automation of device authentication for Azure IoT Hub device - Done
- Create sensor deployment location plan and provide suggestions
see 'SensorDeploymentConfiguration.xlsx' file here Sensor locations
- Make Updates to sensor code (transmit.py) to allow communication directly to azure IoT hub.
- Creating API things, data streams etc from the device manifest.
- Create a POC for creating Air Quality Index for the streaming sensor data
- GitHub integration with Confluence
- Flat HTML page output finished
- Content links need to be filtered/removed/rewritten
- Dynamic menus filtering for GitHub Pages
- Then will automate using a cron job running on a VM hosting a Drupal instance
- This Drupal instance may be running as part of AgileIQ infrastructure
- GitHub integration with source code
- Code will be pushed from Bitbucket to GitHub manually for releases as appropriate
| ||Review Scrum Board|| |
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