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Implementation
Gardivent - Smart Climate Conditioner for Greenhouses
The Gardivent air conditioning system improves the operational efficiency of the greenhouse by providing optimal growing conditions for a variety of garden plants. Thanks to the intelligent control system of parameters and energy consumption from the solar panel system, it ensures savings and protects against wasting resources.
A small, local producer of garden and pot plants required a precise climate control system for their greenhouses to optimize plant growth and health. The Gardivent solution, based on climate conditioning technology and cloud system control was tailored to maintain optimal temperature, humidity, light intensity, and air quality. Additionaly, the integration with the system controlling the solar panels helped to lower the costs for our client.
Gardivent System Features
The Smart Climate Conditioner Gardivent, as we named the system created for our client, consists of three parts:
- The climators – a set of devices that monitor and enhance the conditions in the greenhouses according to the set parameters.
- Operation Center – a browser application that facilitates control.
- AI module – integrated with OC, external system used by solar panels, and weather forcasts.
Climate Control System
Temperature Management
The system maintains a stable temperature within the greenhouse, crucial for plant health and growth.
Humidity Control
Adjustable humidity levels prevent fungal growth and ensure the proper moisture levels for different plant species.
Light Intensity Regulation
Adjustable light settings simulate natural daylight cycles, promoting photosynthesis and healthy plant development. Also, for many plants unfamiliar to our climate it is possible to simulate cycles of day/night and seasons, making it possible to bloom and bear fruits which would be impossible without external light stimulation.
Air Quality Monitoring
The system ensures proper ventilation and air circulation, removing excess gases and bringing in fresh air to sustain plant respiration.
Cloud System Operation Center & AI module
System administrators can access the system remotely, allowing for real-time adjustments and monitoring from any location. The cloud platform supports grouping multiple greenhouses and collective parameter management.
Apart from real-time monitoring and control of the environment in greenhouses, the system allows viewing of historical data and the prognosis of the conditions inside based on local weather forecasts. This, in turn, helps to adjust the settings before bigger changes happen, reducing the time needed for the Climate System to react and saving energy. For example, suppose a big drop in the temperature is forecasted for the coming night. In that case, the system slowly builds up the temperature inside the greenhouses (but limits it to the set parameters, to not overheat the plants). This way, the heaters use less energy than when trying to reach the desired temperature after it drops outside already.
For the development of the Gardivent Smart Climate Conditioner, a combination of technologies from different categories would be essential to ensure seamless operation, real-time control, and efficient integration of components. For the web-based Operation Center, we could utilize HTML, CSS, and JavaScript to create the front-end interface, ensuring ease of use for system administrators. Node.js would be well-suited for server-side development, while Vue.js could be chosen as the front-end framework for building a dynamic and responsive user interface. Given the cloud integration, Python along with Flask would be ideal for developing APIs that interact with the system’s AI and database components. PostgreSQL could be selected as the database to handle the storage of real-time and historical data on climate conditions, ensuring robustness and scalability.
For the testing phase, Jest and Cypress would be suitable for ensuring the integrity of the user interface and the web application’s functionality, running both unit and end-to-end tests. To simulate varying environmental conditions and validate the performance of the AI-powered climate control, pyTest could be employed to test the backend logic, while Locust could be used for performance testing under different load conditions, ensuring the system can handle multiple greenhouses simultaneously. Sentry could also be integrated to monitor and track system errors, helping maintain system reliability post-deployment.
The Operation Center is also linked to the system that operates the energy gained from solar panels, which partially supply the greenhouses. When more energy is produced from the panels, more is redirected to the greenhouses and less from the municipal power plant, thus further reducing the cost of heating and making the system more environmentally friendly.
Benefits for the Producer
Enhanced Growth Conditions
Stable and controlled greenhouse conditions lead to healthier plants and improved growth rates, directly impacting yield and quality.
Long-Term Experimentation
Consistent environmental conditions allow for reliable long-term growth experiments and testing of new plant varieties.
Increased Efficiency & Lower costs
Remote monitoring and AI control reduce the need for constant on-site supervision, saving time, labor costs and resources.
Conclusion
The climate conditioning system has significantly enhanced the operational efficiency of the greenhouse, ensuring optimal growing conditions for various garden plants. This advanced system offers flexibility, reliability, and scalability, making it an essential tool for modern horticulture.
