Author: zmansoor

This week I first worked with Jana on making the greenhouse water-resistant as we sprayed water-resistant sealant over it and put the components back in. We have tidied up the system and secured the lights and the water pump. I also got the 7-in-1 soil sensor working fully and is incorporated into the main function. There were a few issues in getting it working at the same time as the temperature sensor, however, I managed to resolve them by using different packages for the code. I have now incorporated all sensor data to be sent on the webapp and they are running constantly now to collect data. For the RPI camera, I have also laser-cut a mount for it so it can be stuck on the greenhouse and the angle of the camera may be adjustable depending on the plant inserted.

My progress is mostly on track, I will need to resolve the finalissues with the heater thisweek. I have also received the final water pump for the nutrients so I will set it up in the upcoming week. In terms of actuator code control, I will need to record the water flow rate so I can set up automated water pumping and nutrient pumping.

This week I made progress on getting the water pump actuator to work through the RPi, as well as the soil moisture sensor (HW080) to collect plant data. The actuator code for the heater works as well, though it overheats the wires and smokes so it becomes unsafe. Thus I have decided to not demo that and wait to retry with thicker wires for more safety in the future. I have researched more into the soil moisture, pH, and nutrients sensors, however, due to lack of documentation am still struggling to make it work so will be using the HW080 for the demo instead. We have also instilled all the current working components into our greenhouse so that it is together, and I have added an extra Arduino to the system to reduce the stress on the Raspberry Pi.

By next week, I hope to get the soil moisture, nutrients, pH sensor working as well as the heater without safety issues so that full data can be collected. I also want to start the control code with a pid so that the system will respond to ideal conditions.

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.

This week, I worked on the ethics assignment to evaluate the ethical considerations related to our project. On the technical side, I continued developing the API code and discovered that the initial API we intended to use was no longer actively maintained, though some calls were still functional. Upon further investigation, I found the API’s database but determined that it lacked the necessary data for our project.

To address this, I implemented an alternative API to retrieve the required information. However, certain critical details, such as plant watering and lighting schedules, were locked behind a paywall. As a workaround, I explored web scraping as a potential solution and identified several websites with relevant plant data, though they cover a limited selection of houseplants.

My progress remains on schedule, and I am now shifting my focus to setting up the heater. By next week, I aim to finalize the heater’s control code and complete the web scraping implementation to gather the necessary plant data.

This week, I helped work on the design status report, which has helped further solidify our project plans. I focused on reworking the system architecture, specifically the flow chart diagram, to incorporate the new decision to use a PID controller for managing the system’s environment. Additionally, I updated the system implementation plan, bill of materials, and prepared a summary to align our project’s direction moving forward. On the sensor front, I conducted tests on various temperature and humidity sensors to identify the most accurate one, replacing the initially tested model. I also began implementing the light sensor into our system. For the plant API call, I am still in the process of finalizing the code to ensure smooth integration and functionality.

In terms of schedule, I am mostly on track; however, I have encountered a delay in implementing the heater. This is due to shipping issues, as the heater has yet to arrive, which is preventing me from progressing as planned

Looking ahead, my deliverables for next week include completing the implementation of the soil nutrients, pH, and moisture sensors, as well as finalizing the light sensor integration. If the heater arrives as expected, I aim to complete its implementation as well.

This week, I focused on setting up the Raspberry Pi at home and configuring it for our project. I successfully set up a Git repository for the team so we can track our code and collaborate efficiently. I also wrote initial code to collect temperature and humidity sensor data. The temperature readings appeared accurate, but the humidity values seemed off. To investigate further, I plan to rerun tests and, if the issue persists, compare results with backup sensors to determine whether the problem is with the sensor itself or the way the data is being processed. In addition to working on the sensor data, I also started implementing the Plant API data retrieval code, though I haven’t finished it yet. Here is an image of the sensor output data:

As a team, we received most of our components and assembled the greenhouse, ensuring that all parts fit together correctly. We also finished ordering the remaining components, including the plants, so we can begin testing as soon as they arrive with the sensors and start collecting training data for the ML models. My progress is currently on schedule since I have been able to start testing the sensors, though I still need to complete the Plant API integration this week.

Next week, I plan to set up and test the remaining sensors to ensure they are providing accurate readings. I also need to configure the Raspberry Pi to connect to the school’s Wi-Fi so that I can work on it remotely while on campus. Additionally, I aim to complete the integration of the Plant API so we can start using the data in our system.

This week, I focused on ordering all the necessary parts for our project and ensuring that the components we selected are fully compatible with our Raspberry Pi 5. I spent time carefully planning how the sensors and actuators will connect to the Raspberry Pi on the pinout, including how they will be powered and controlled. Additionally, I researched various water pump systems to determine the best way to integrate one into our design.

With the upcoming design presentation, I also worked closely with my team to refine our slides. I finalized the block diagram to visually present how the system components will connect and interact. To address previous confusion about the role of our machine learning model, I created a detailed flow diagram to clearly outline its function and integration within our system. My goal was to ensure that our audience would fully understand how our data inputs contribute to plant health classification.

Currently, we are on schedule, and our progress aligns with our planned timeline. However, I am slightly concerned that some of our ordered components may take longer than expected to arrive, which could delay the integration of certain parts. Fortunately, none of these delays seem significant enough to disrupt our overall schedule. Another potential issue is the soil nutrient and pH sensor we selected, as it has limited reviews and its reliability is uncertain. Due to budget constraints, we opted for a more affordable sensor, but if testing reveals any issues, we will order an alternative model as soon as possible.

By next week, I hope to have the temperature and humidity sensor set up and fully integrated with the RPi 5 to establish a working model for collecting environmental data. Additionally, I plan to begin testing other hardware components as they arrive to ensure a smooth transition into the next phase of our project.