Agriculture, a fundamental pillar for the survival and development of human communities, today faces increasingly complex challenges on a global scale. Phenomena such as climate change, with unpredictable weather patterns, pest infestations, livestock diseases, and even political tensions,put food security and the livelihoods of farmers at risk. Additionally, there is growing difficulty in accessing essential resources, exacerbated by the lack of adequate tools to manage these challenges effectively. In this scenario, the integration of advanced scientific data could represent a crucial turning point to make agricultural practices more resilient and sustainable. It is in this context that Copernico was born, an innovative app designed to offer farmers a simple and intuitive tool that connects them to geospatial data and Earth observation data provided by NASA.
Through more accurate forecasts, tools for risk management, and decision support, the app aims to offer concrete and easily accessible solutions to farmers.Despite the opportunities provided by satellite data, translating complex information into practical advice usable by agricultural communities remains a challenge. Often, current technologies fail to adequately integrate the data into a "farmer-centric" context, limiting the adoption of such resources due to their complexity or the lack of an adequate design. Copernico aims to overcome these barriers by providing a tool that allows the visualization of data in a comprehensible, intuitive, and relevant way, thereby helping farmers make informed decisions based on real-time information.
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Impact
Copernico has a significant potential impact both in terms of quality and quantity, as the project aims to solve a central problem for global agriculture: resource management, a crucial issue for agricultural productivity and food security. Furthermore, Copernico aims to support not only small farmers but also large agricultural producers, helping them optimize water usage, manage environmental risks, and improve the sustainability of their practices. In this way, the project can inspire a broad audience and bring tangible benefits to many, as it provides a tool capable of influencing the efficiency of large-scale agricultural operations.
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Creativity
Copernico’s approach aims to be highly innovative. While there are solutions that use satellite data for agriculture, it stands out for its ability to translate complex data into accessible and usable information for farmers, particularly by providing practical and relevant advice. The app leverages a user-friendly interface, making information available on a local and temporal basis, integrating real-time forecasts and in-depth analyses. This novel approach not only improves existing technologies but also opens new opportunities for the use of satellite data by the agricultural community.
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Validity
The project is based on solid scientific data, utilizing datasets from NASA, one of the most reliable sources of Earth observation.
Copernico aims to provide accurate information on phenomena such as water availability and quality, using advanced predictive models to enhance farmers' decision-making abilities. Thanks to the use of established technologies such as satellite monitoring and data analysis tools, the project boasts a high level of scientific validity and can function effectively in the real world. -
Relevance
The project is highly relevant to the challenge for which it was created, directly addressing the need to provide farmers with better tools to understand and manage resources through the integration of NASA data. Copernico presents itself as a technically feasible and intuitive solution, which must be further developed to improve its scalability.
- Frontend: Next.js, Expo, Supabase, and tRPC
- UI/UX: Figma.
- Next.js web frontend
- Expo/React Native mobile app
- Supabase authentication
- Typesafe API with tRPC
- State management with React Query
- Styling with Tailwind CSS
- Customizable UI components
- TypeScript configuration
apps/next.js: Next.js web applicationapps/mobile: Expo/React Native mobile application
Requirements
Make sure you have Node.js and npm installed on your computer.
Follow these steps to execute the project:
- Clone the repository
- Install dependencies:
pnpm install - Set up environment variables
- Start web app:
pnpm run dev:web - Start mobile app:
pnpm run dev:mobile
Registration - Login
Registration and login allow the user to access advanced features, including:
- Integration into the community and access to the proximity chat
- Personalized and accurate statistics with practical advice on individual cultivated products and farmed livestock
- Monitoring of multiple specific areas of interest
- Real-time notification alerts to better manage crops and/or livestock
- Task Manager with Gamification
- Saving of preferences
- Personalized feedback
The registration process consists of a gradual onboarding that requires quick and simple data:
- Language selection and automatic setting of the corresponding unit of measurement
- Mandatory Data: First Name, Last Name, Email, Password, Phone Number
- Optional Data: Company Name
Next, users proceed with an easy identification of their area of interest through a geolocation and search system, allowing them to accurately and precisely trace the perimeter.
Home Page
The Home Page includes a brief summary of some features, such as:
- Advanced Reporting System with Daily/Monthly/Semi-Annual views
- Reports of the most relevant advice and practices to implement throughout the day
Through a bottom bar, users can navigate to the pages dedicated to specific features.
Statistics
The statistics section presents solutions and practical advice, including a limited amount of data, in such a way that the end user perceives a high degree of intuitiveness in utilizing and implementing actions taken based on informed decisions.
Each piece of data is accompanied by practical advice that can be implemented in the user's selected area of interest. Additionally, two advanced features are accessible within the statistics area:
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Agriculture Statistics: through the cataloging of each individual cultivated product and using a predictive model, users can receive advice on every cataloged product.
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Livestock Statistics: through the cataloging of each farmed animal and using a predictive model, users can receive a series of personalized actions aimed at increasing the well-being of the animals.
Proximity Chat
The Proximity Chat feature enables users to engage with a location-based social feed. It encourages community interactions by showing posts and media shared by individuals within a defined distance from the user’s location. The proximity range is configurable (e.g., within a 100 km radius), fostering local connectivity and real-time updates about the surrounding community.
Users can interact with posts in various ways:
- Like Posts: Show appreciation or agreement by liking posts.
- Comment on Posts: Join conversations by leaving comments.
- Text Posts: Share simple updates, such as “Today I found a FOX in my area… stay focused!”
- Media Posts: Upload images or videos relevant to the community (e.g., pictures of local events, projects).
Task Manager with Gamification
The Task Manager with Gamification is a tool designed to help farmers manage their daily and long-term tasks more effectively and in a more engaging way, turning farm work into a motivating experience through game mechanics.
Every time a user completes a task, they earn experience points (XP), which allow them to level up, unlock new features and receive badges that highlight their progress. For example, completing a week's worth of activities without delay can earn you a ‘Perfect Week’ badge. In addition to badges, users can receive virtual rewards, such as access to exclusive tips or advanced platform features. In addition, the Task Manager is integrated with the platform's farming community, allowing users to share their results, demonstrating their expertise.
Feedback Collection
After the system provides a prediction, users have the opportunity to offer feedback on the accuracy of the forecast. This could be done through a simple rating scale (for example, from 1 to 5, where 1 indicates a very inaccurate prediction and 5 a highly accurate one). Additionally, users could provide optional comments to give more context about what went wrong if needed.
The NASA POWER API provides meteorological data useful for various applications, including climate analysis, agricultural studies, and environmental monitoring. This documentation describes how to correctly construct URLs to access the data offered by the API and presents the main datasets available through NASA Earthdata.
The base URL for accessing daily data from the API is: https://power.larc.nasa.gov/api/temporal/daily/point
To construct a complete URL for data access, several parameters need to be specified. Below are the main parameters that can be used:
- lat: Latitude of the geographic point of interest.
- lon: Longitude of the geographic point of interest.
- start: Start date for data retrieval (format YYYY-MM-DD).
- end: End date for data retrieval (format YYYY-MM-DD).
- params: Specific parameters requested (e.g., temperature, precipitation, soil moisture).
- format: Format of the response (e.g., JSON, XML).
The NASA POWER API offers immediate benefits in terms of speed and ease of use. It is ideal for quick access to daily meteorological data for various applications. However, NASA Earthdata offers a more strategic option for the future, particularly for advanced research requiring complex, multidimensional datasets.
NASA Earthdata provides access to key datasets that are invaluable for advanced research and applications. Some of the main datasets include:
- Air Temperature (T2M): Near-surface air temperature in degrees Celsius, useful for understanding daily temperature variations and trends for agricultural applications.
- Precipitation (PRECTOT): Total daily precipitation in millimeters, essential for irrigation planning, drought monitoring, and water resource management.
- Soil Moisture (SOILM): Available as a percentage, providing crucial data for understanding soil water content, which is vital for crop health and irrigation management.
- Soil Temperature (SOILTEMP): Soil temperature at different depths (typically 0-10 cm), important for understanding planting conditions and crop root zone temperatures.
- Wind Speed (WS2M): Wind speed at 2 meters above ground in meters per second, useful for planning wind-sensitive agricultural activities or renewable energy applications.
- Relative Humidity (RH2M): Humidity at 2 meters above ground level, valuable for understanding atmospheric moisture levels and their impact on crop health and disease.
- Solar Radiation (ALLSKY_SFC_SW_DWN): Downward shortwave radiation (MJ/m²/day), crucial for solar energy applications and plant photosynthesis analysis.
- Dew/Frost Point (DEW2M): Dew point temperature, which is essential for understanding frost risk and its impact on crops.
These datasets provide real-time information that enhances our understanding of various environmental factors, supporting deeper analysis and applications.
Here are some examples that illustrate how the datasets from NASA can be used to derive important conditions and provide practical advice for farmers, resource managers, and environmental planners:
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Potential Evapotranspiration (ETP)
- Required Data: Air temperature, solar radiation, wind speed, relative humidity.
- Derived Condition: Potential evapotranspiration measures water loss through evaporation and plant transpiration. This is critical for irrigation planning and water resource management.
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Drought Index
- Required Data: Precipitation, soil moisture, air temperature.
- Derived Condition: By combining precipitation and soil moisture data, a drought index can be derived, helping to monitor periods of water stress for crops and managing agricultural risks.
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Frost Prediction
- Required Data: Air temperature, dew point temperature, relative humidity.
- Derived Condition: Monitoring minimum air temperatures and the dew point allows for frost prediction, which can help in taking preventive measures to protect crops from frost damage.
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Crop Growth Conditions
- Required Data: Soil temperature, air temperature, solar radiation.
- Derived Condition: Crop growth conditions can be estimated by analyzing soil temperature and solar radiation, providing insights into the optimal times for planting and harvesting.
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Plant Disease Risk Assessment
- Required Data: Relative humidity, air temperature, precipitation.
- Derived Condition: High humidity combined with specific temperature ranges can promote the development of fungi or other plant diseases. Monitoring these factors allows for proactive measures in plant disease prevention.
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Soil Water Balance
- Required Data: Soil moisture, precipitation, evapotranspiration.
- Derived Condition: With soil moisture, precipitation, and evapotranspiration data, the soil water balance can be calculated, aiding in irrigation strategy and water resource management.
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Solar Energy Forecast
- Required Data: Solar radiation (ALLSKY_SFC_SW_DWN).
- Derived Condition: Solar radiation data can be used to estimate solar energy production, optimizing the operation of photovoltaic systems and planning renewable energy usage.
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Livestock Climate Comfort Index
- Required Data: Air temperature, relative humidity, wind speed.
- Derived Condition: Using these data, a livestock comfort index can be derived, helping to assess the risk of heat stress in animals, improving welfare and management in farming.
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Flood Prediction
- Required Data: Total precipitation, soil moisture, wind speed.
- Derived Condition: Combining precipitation and soil moisture data allows for flood predictions, helping to make timely decisions for hydrological risk management.
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Plant Water Stress
- Required Data: Soil moisture, air temperature, evapotranspiration.
- Derived Condition: By monitoring soil moisture and calculating evapotranspiration, the water stress levels of plants can be derived, supporting decisions on whether irrigation is necessary.
Credits: This system was conceived and designed by: Carmine Gallo, Orazio Torre, Vittorio D'Alfonso, Gerardo Nastri.