Preferred learners
- Anywhere
- Academic experience
Categories
Skills
Project scope
- What is the main goal for this project?
-
The main goal for the project is to develop a system using satellite remote sensing technology and machine learning models to estimate soil carbon sequestration, which is important for climate change mitigation. This will involve several different steps for the learners, including:
- Understanding the principles of soil carbon sequestration and its importance in agriculture.
- Familiarizing with satellite remote sensing technology and its application in agriculture.
- Collecting and analyzing relevant data sets for soil carbon sequestration estimation.
- Developing and training machine learning models for accurate estimation.
- Integrating the developed models into a user-friendly interface for farmers.
- What tasks will learners need to complete to achieve the project goal?
-
By the end of the project, learners should complete the following tasks:
- A comprehensive understanding of soil carbon sequestration and its estimation using remote sensing and machine learning.
- Collection and analysis of relevant data sets for the project.
- Development and training of machine learning models for accurate estimation.
- Integration of the models into a user-friendly interface for farmers.
Final deliverables should include:
- A detailed report outlining the methodology, findings, and recommendations.
- The developed machine learning models and the user interface.
- What is the main goal for this project?
-
The main goal for the project is to develop a system using satellite remote sensing technology and machine learning models to estimate soil carbon sequestration, which is important for climate change mitigation. This will involve several different steps for the learners, including:
- Understanding the principles of soil carbon sequestration and its importance in agriculture.
- Familiarizing with satellite remote sensing technology and its application in agriculture.
- Collecting and analyzing relevant data sets for soil carbon sequestration estimation.
- Developing and training machine learning models for accurate estimation.
- Integrating the developed models into a user-friendly interface for farmers.
- What tasks will learners need to complete to achieve the project goal?
-
By the end of the project, learners should complete the following tasks:
- A comprehensive understanding of soil carbon sequestration and its estimation using remote sensing and machine learning.
- Collection and analysis of relevant data sets for the project.
- Development and training of machine learning models for accurate estimation.
- Integration of the models into a user-friendly interface for farmers.
Final deliverables should include:
- A detailed report outlining the methodology, findings, and recommendations.
- The developed machine learning models and the user interface.
- How will you support learners in completing the project?
-
The company will provide any necessary guidance and mentorship to learners to complete the project.
Regular check-in sessions to make sure the project is proceeding in the right path.
Supported causes
About the company
- https://cropinno.com/
- 2 - 10 employees
- Agriculture, It & computing
Cropinno is an Agri-tech company using satellite and AI technology to help farmers monitor and identify potential issues on the farm to prevent yield loss and boost their productivity.
Our solutions provide near real-time understanding of agricultural farms to identify potential issues early on. This information allows farmers to gain insights into crop conditions, thereby eliminating the need for time-consuming and costly manual data collection.