This week, I made significant progress on the project by completing most of the web scraping for plant data. I successfully gathered essential information such as scientific name, light requirements, watering needs, temperature, and humidity levels. The only remaining task for this aspect is to obtain pH levels and more precise water level data from additional sources. Alongside this, I worked with Yuna to implement the transmission of temperature and humidity sensor data from the Raspberry Pi to the web application. I also tested and verified the functionality of the light sensor code, ensuring it is correctly reading and processing data.
The Raspberry Pi is now deployed on campus, where I noticed that it tends to overheat when multiple sensor inputs are running simultaneously. To address this issue, I have ordered a cooling fan to help maintain optimal performance. In terms of overall logic, I also finalized the control flow payloads that will be sent back and forth from the RPi to the Web app with Jana and Yuna.
My progress is mostly on schedule, though I have fallen a bit behind on starting actuators, as I wanted to prioritize the integration of webapp for sensor data before implementing turning on and off the heater. By next week I hope to complete the code for the soil pH and nutrients sensor as well as having pH levels scraped online. I want to finalize sending all sensor data to the webapp integration in time for the upcoming demo and also get started on actuator code for the heater.