In our agricultural project, we aim to address multiple challenges. Firstly, we focus on predicting and optimizing the operation costs in greenhouses, specifically electricity and water costs. By utilizing the capabilities of our digital twin, we track parameters such as 'fan on time' and 'mist on time', enabling us to accurately estimate the associated expenses for each trial. Secondly, we recognize the impact of frequent power cuts in our country, which hinders our understanding of greenhouse behavior under such circumstances. Through the digital twin simulation, we can gain valuable insights into how greenhouses perform during power outages, allowing us to prepare and optimize operations for such unpredictable situations. Finally, we incorporate weather forecast data into our system. By leveraging this information, smart farmers can make timely decisions to optimize their greenhouse operations, ensuring optimal resource utilization and crop productivity. Our solution empowers farmers with proactive planning, cost prediction, and resilience in the face of uncertain weather and power conditions
To install and run this project on your local machine, follow these steps:
git clone https://github.com/rasathuraikaran/CakeOrderApp.git
pip install -r requirements.txt
app.py
- Interactive UI