Project timeline
Hydroponic Farming Automation
Hydroponic growing automation with sensors and control logic.
Main tools and layers
Project category and focus
Worked on sensor data, pump/light control, timing, threshold logic and dashboard scenarios. Contribution scope: breaking requir...
Used technologies
Technologies used in this project
Key technologies in this project are matched automatically from its technology list and category structure.
ESP32 Advanced
Arduino Advanced
Raspberry Pi Advanced
LoRa Intermediate
OTA Intermediate
MQTT Intermediate
Sensors Advanced
PlatformIO Intermediate
Robotics & Automation Advanced
Siemens TIA Portal Intermediate
Blender Basic
Details
Project overview
Hydroponic farming automation is based on connecting water, nutrients, light, temperature and sensor data to a controllable growing process. Success in this kind of system is not only running a motor or pump, but balancing measurement, thresholds, timing, records and user settings. The project shows how automation can be designed as a decision layer supporting a biological process.
System perspective: The project was considered not as a single technical output, but together with requirements, data flow, user interaction, failure scenarios, maintainability and future extensibility. This makes both the engineering decisions and software architecture choices easier to understand.
Implementation detail: The content was expanded to explain not only the technologies used, but also how the problem was approached, which layers were separated, how data and control flow were considered, and which competency the project represents inside the CV.
Portfolio depth: This record highlights not only the technologies used, but also how the requirement was decomposed, how data or control flow was considered, what output is presented to the user and how the project can be extended later. This turns the project card from a short showcase into a readable case study that explains engineering decisions.
Case Study
The technical story from problem to outcome
In hydroponic systems, plant growth depends on multiple variables such as water quality, nutrient concentration, temperature, humidity and lighting. Manual tracking is error prone and late detected deviations can affect yield.
A sensor based monitoring and time/threshold controlled automation flow was designed.
The sensor layer collects environment data, the control layer decides pump/light actions and the panel layer manages status and settings.
The project shows the value of data driven monitoring and early warning in agricultural automation. The hydroponic environment becomes more measurable and the system can later expand with dosing, irrigation or climate control.
Architecture
Block-based system flow
In hydroponic systems, plant growth depends on multiple variables such as water quality, nutrient concentration, temperature, humidity and lighting. Manual tracking is error prone and late detected deviations can affect yield.
The sensor layer collects environment data, the control layer decides pump/light actions and the panel layer manages status and settings.
A sensor based monitoring and time/threshold controlled automation flow was designed.
The project shows the value of data driven monitoring and early warning in agricultural automation. The hydroponic environment becomes more measurable and the system can later expand with dosing, irrigation or climate control.
Live showcase
Demo, output and visual story
In hydroponic systems, plant growth depends on multiple variables such as water quality, nutrient concentration, temperature, humidity and lighting. Manual tracking is error prone and late detected deviations can affect yield.
The project shows the value of data driven monitoring and early warning in agricultural automation. The hydroponic environment becomes more measurable and the system can later expand with dosing, irrigation or climate control.
The sensor layer collects environment data, the control layer decides pump/light actions and the panel layer manages status and settings.
The project shows the value of data driven monitoring and early warning in agricultural automation. The hydroponic environment becomes more measurable and the system can later expand with dosing, irrigation or climate control.