Progress I made this week:
- Plant Species Detection: When the user tries to add a new plant and they don’t know what the species is, the web app now detects the plant species using ML.
- Manual Auto-scheduling: I added a manual auto-scheduling page for users to manually control the plant care conditions if their plant is not in the webscraped database. The user can now set their own auto-schedule.
- Chrome Notifications: I implemented a notification system using Chrome Notifications API to notify the users whenever the plant conditions are unhealthy or the sensor data goes beyond the ideal threshold. (The original plan of using Twilio API for notifications have been changed to chrome notifications due to cost issues.)
- Camera On/Off: The camera can be now turned on and off using a switch on the web app, allowing users to control security.
- Deployment on RPi: The web app has been deployed to RPi. It was initially using http, but I realized chrome notifications API requires https instead. Now the website can be accessed in https url.
I am currently a little behind schedule because some of the features in the web app were not fully implemented and verified, but I’ll make sure to finish everything by early next week to leave time for testing.
Next week’s deliverables:
- Auto-scheduling Feature: fully implement the auto-scheduling feature and verify it works. Currently there is code for making sure the conditions change according to the schedule, but haven’t tested if it works.
- More Sensors/Actuators Integration: Our team has some sensors and actuators that haven’t been fully integrated to the system yet, so I’ll work on integrating them with web app.
- Focus on details: fix small details in the web app – for example, currently the switches for turning on/off the actuators do not know the current status of the actuators. I will make sure the web app gets notified of the current on/off status of the actuators from RPi.
- Tests: write tests for the web app code. Test if the system works.