Ensuring food security through improved crop yield is essential for sustainable agriculture. Precision agriculture has the potential to enhance productivity by enabling better-informed decisions, but accurate crop yield estimation remains a challenge due to numerous agro-climatic variables and diverse farming practices. Crop yield is, however, strongly related to how well a crop is doing and knowledge on crop conditions, along with knowledge on the factors influencing current conditions, allows stakeholders to make more informed decisions on how to improve agricultural practices to maximize crop yield. Monitoring crop health plays a pivotal role in predicting yield outcomes, as it helps to identify issues like pest infestations or diseases early, allowing timely intervention.

The objective of this competition is to build a machine learning model that can classify the health conditions of various crops in the Telangana state of South-Central India using data on cultivation practices along with historical Sentinel-2 time series data. This model will help both farmers and government bodies monitor crop conditions and take proactive measures to mitigate any adverse effects on crop health, and consequently improve crop yield.

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH (German Development Cooperation)

The initiative “FAIR Forward – Artificial Intelligence for All“ contributes to democratizing artificial intelligence (AI) worldwide. It uses AI to fight poverty, reduce inequalities and achieve a Just Transition in the areas of climate change and agriculture. Globally and together with seven partner countries in Africa and Asia, FAIR Forward implements Germany’s AI strategy internationally. The initiative promotes local AI innovation through access to open source AI training data, strengthened AI skills and policy frameworks for responsible AI.

FAIR Forward is one of the initiatives of the global project “Digital Transformation”. It is implemented by the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) on behalf of the German Federal Ministry for Economic Cooperation and Development (BMZ). For more information on FAIR forward see: https://www.bmz-digital.global/en/overview-of-initiatives/fair-forward/. On the global project, see https://www.bmz-digital.global/en/.

Emerging Technologies Wing, Information Technology, Electronics & Communications Department, Government of Telangana

The IT, E&C Department leverages Information Technology not just for effective and efficient governance, but also for sustainable economic development and inclusive social development. Its vision is to be a leader in emerging technologies and to translate that vision into a reality through several initiatives in the State. The government has created a vertical for emerging technologies with a two-fold objective - (i) to develop the ecosystem required for the industry and (ii) to make the government departments leverage or adopt emerging technologies.

ADeX: The Agricultural Data Exchange Platform

ADeX, India's first Agriculture Data Exchange, is a collaborative initiative by the Government of Telangana, the Indian Institute of Science (IISc), Bengaluru, and the World Economic Forum. This platform facilitates data sharing in the agricultural sector through a secure, cloud-based environment. Built on the India Urban Data Exchange (IUDX), ADeX standardizes access to agricultural data, empowering innovators to create solutions for the farming ecosystem. By connecting agricultural data providers such as government agencies, private companies, NGOs, and universities with application developers, ADeX fosters collaboration that enhances data driven decision making and innovation in agriculture.

The error metric for this competition is F1 Multi Class.

There are four categories:

1. Diseased
2. Pests
3. Stressed
4. Healthy: Encompasses healthy and good conditions.

Your submission file will look like this

For every row in the dataset, submission files should contain 2 columns: ID and Target. Take not of the column names.

Your submission file should look like this (numbers to show format only):

ID         Target

17289          Pest

27766          Healthy

Fairness Metric

The top 20 on the leaderboard at the close of the challenge will have their top 2 public score submissions or their 2 selected submissions scored against holisticai.bias.metrics.multiclass_equality_of_opp based on crop district.

The final rank will be calculated as: Final Rank = 0.75 * Private LB + 0.25 * Fairness score.

Code will be requested from the top 10 on this combined leaderboard.

Qualitative Report

If you are ranked in the top 10 on the combined leaderboard after the challenge, you will be required to submit a PDF document containing your answers to these questions. Each answer should be between 100-300 words in length, and including references in your responses will strengthen your submission.

These questions are designed to challenge your thinking around fairness and the practical application of AI.

Please note that your solution will not be eligible for review by the code review team until all questions have been answered with sufficient detail, each part of the question is addressed thoughtfully, and clear reasoning or examples are provided.

1. How would you perceive the usefulness of an AI model that predicts crop health based on the variables available in this challenge (i.e. healthy, diseased, pest infested or stressed) and what shortcomings do you see arising from using these variables?
2. What shortcomings or potential harms do you perceive such an AI model to create when a farmer or extension officer applies it in the field? If you had resources available: What strategies would you implement to mitigate such potential harms?
3. After calculating the required metrices, please critically evaluate what the results would mean for your developed AI model in terms of necessary adjustments and mitigation strategies (e.g. data set imbalances, renewed data collection, model development).
4. For the F1 score: Could you expand on the district-wise difference of predictive quality for the different crops? If anything is to be observed here what can you derive from it? What could lead to a difference in predictive quality in between districts? Note: You may simply sort and compare the (average) prediction performance for the different districts in Telangana (use the district variable for this).
5. For this use case: would you perceive false positives or negatives as more harmful or do you perceive them as equally harmful?
6. Based on your consideration: Which 1-2 additional performance, evaluation or fairness metrics would you suggest to test for and why?

🥇 1st Place: TEAM Encode Nature

🥈 2nd Place: @private_1x

🥉 3rd Place: @marching_learning

1st prize: 3 100 EUR

2nd prize: 2 400 EUR

3rd prize: 1 400 EUR

There are 7 000 Zindi points available. You can read more about Zindi points here.

Competition closes on 9 February 2025.

Final submissions must be received by 11:59 PM GMT.

The private leaderboard will be revealed on 13 February 2025.

We reserve the right to update the contest timeline if necessary.

How to enroll in your first Zindi competition

How to create a team on Zindi

How to update your profile on Zindi

How to use Colab on Zindi

How to mount a drive on Colab

• Languages and tools: You may only use open-source languages and tools in building models for this challenge.
• Who can compete: Open to all
• Submission Limits: 10 submissions per day, 300 submissions overall.
• Team size: Max team size of 4
• Public-Private Split: Zindi maintains a public leaderboard and a private leaderboard for each challenge. The Public Leaderboard includes approximately 30% of the test dataset. The private leaderboard will be revealed at the close of the challenge and contains the remaining 70% of the test set.
• Data Sharing: CC-BY SA 4.0 license
• Platform abuse: Multiple accounts, or sharing of code and information across accounts not in teams, or any other forms of platform abuse are not allowed, and will lead to disqualification.
• Code Review: Top 10 on the private leaderboard will receive an email requesting their code at the close of the challenge. You will have 48 hours to submit your code.

ENTRY INTO THIS CHALLENGE CONSTITUTES YOUR ACCEPTANCE OF THESE OFFICIAL CHALLENGE RULES.

Full Challenge Rules

This challenge is open to all.

Teams and collaboration

You may participate in challenges as an individual or in a team of up to four people. When creating a team, the team must have a total submission count less than or equal to the maximum allowable submissions as of the formation date. A team will be allowed the maximum number of submissions for the challenge, minus the total number of submissions among team members at team formation. Prizes are transferred only to the individual players or to the team leader.

Multiple accounts per user are not permitted, and neither is collaboration or membership across multiple teams. Individuals and their submissions originating from multiple accounts will be immediately disqualified from the platform.

Code must not be shared privately outside of a team. Any code that is shared, must be made available to all challenge participants through the platform. (i.e. on the discussion boards).

The Zindi data scientist who sets up a team is the default Team Leader but they can transfer leadership to another data scientist on the team. The Team Leader can invite other data scientists to their team. Invited data scientists can accept or reject invitations. Until a second data scientist accepts an invitation to join a team, the data scientist who initiated a team remains an individual on the leaderboard. No additional members may be added to teams within the final 5 days of the challenge or last hour of a hackathon.

The team leader can initiate a merge with another team. Only the team leader of the second team can accept the invite. The default team leader is the leader from the team who initiated the invite. Teams can only merge if the total number of members is less than or equal to the maximum team size of the challenge.

A team can be disbanded if it has not yet made a submission. Once a submission is made individual members cannot leave the team.

All members in the team receive points associated with their ranking in the challenge and there is no split or division of the points between team members.

Datasets and packages

The solution must use publicly-available, open-source packages only.

You may use only the datasets provided for this challenge. Automated machine learning tools such as automl are not permitted.

You may use pretrained models as long as they are openly available to everyone.

You are allowed to access, use and share challenge data for any commercial,. non-commercial, research or education purposes, under a CC-BY SA 4.0 license.

You must notify Zindi immediately upon learning of any unauthorised transmission of or unauthorised access to the challenge data, and work with Zindi to rectify any unauthorised transmission or access.

Your solution must not infringe the rights of any third party and you must be legally entitled to assign ownership of all rights of copyright in and to the winning solution code to Zindi.

Submissions and winning

You may make a maximum of 10 submissions per day.

You may make a maximum of 300 submissions for this challenge.

Before the end of the challenge you need to choose 2 submissions to be judged on for the private leaderboard. If you do not make a selection your 2 best public leaderboard submissions will be used to score on the private leaderboard.

During the challenge, your best public score will be displayed regardless of the submissions you have selected. When the challenge closes your best private score out of the 2 selected submissions will be displayed.

Zindi maintains a public leaderboard and a private leaderboard for each challenge. The Public Leaderboard includes approximately 30% of the test dataset. While the challenge is open, the Public Leaderboard will rank the submitted solutions by the accuracy score they achieve. Upon close of the challenge, the Private Leaderboard, which covers the other 70% of the test dataset, will be made public and will constitute the final ranking for the challenge.

Note that to count, your submission must first pass processing. If your submission fails during the processing step, it will not be counted and not receive a score; nor will it count against your daily submission limit. If you encounter problems with your submission file, your best course of action is to ask for advice on the Competition’s discussion forum.

If resource restrictions are indicated on the challenge page you must adhere to them.

If you are in the top 10 at the time the leaderboard closes, we will email you to request your code. On receipt of email, you will have 48 hours to respond and submit your code following the Reproducibility of submitted code guidelines detailed below. Failure to respond will result in disqualification.

If your solution places 1st, 2nd, or 3rd on the final leaderboard, you will be required to submit your winning solution code to us for verification, and you thereby agree to assign all worldwide rights of copyright in and to such winning solution to Zindi.

If two solutions earn identical scores on the leaderboard, the tiebreaker will be the date and time in which the submission was made (the earlier solution will win).

The winners will be paid via bank transfer, PayPal if payment is less than or equivalent to $100, or other international money transfer platform. International transfer fees will be deducted from the total prize amount, unless the prize money is under $500, in which case the international transfer fees will be covered by Zindi. In all cases, the winners are responsible for any other fees applied by their own bank or other institution for receiving the prize money. All taxes imposed on prizes are the sole responsibility of the winners. The top winners or team leaders will be required to present Zindi with proof of identification, proof of residence and a letter from your bank confirming your banking details. Winners will be paid in USD or the currency of the challenge. If your account cannot receive US Dollars or the currency of the challenge then your bank will need to provide proof of this and Zindi will try to accommodate this.

Please note that due to the ongoing Russia-Ukraine conflict, we are not currently able to make prize payments to winners located in Russia. We apologise for any inconvenience that may cause, and will handle any issues that arise on a case-by-case basis.

Payment will be made after code review and sealing the leaderboard.

You acknowledge and agree that Zindi may, without any obligation to do so, remove or disqualify an individual, team, or account if Zindi believes that such individual, team, or account is in violation of these rules. Entry into this challenge constitutes your acceptance of these official challenge rules.

Zindi is committed to providing solutions of value to our clients and partners. To this end, we reserve the right to disqualify your submission on the grounds of usability or value. This includes but is not limited to the use of data leaks or any other practices that we deem to compromise the inherent value of your solution.

Zindi also reserves the right to disqualify you and/or your submissions from any challenge if we believe that you violated the rules or violated the spirit of the challenge or the platform in any other way. The disqualifications are irrespective of your position on the leaderboard and completely at the discretion of Zindi.

Please refer to the FAQs and Terms of Use for additional rules that may apply to this challenge. We reserve the right to update these rules at any time.

Reproducibility of submitted code

• If your submitted code does not reproduce your score on the leaderboard, we reserve the right to adjust your rank to the score generated by the code you submitted.
• If your code does not run you will be dropped from the top 10. Please make sure your code runs before submitting your solution.
• Always set the seed. Rerunning your model should always place you at the same position on the leaderboard. When running your solution, if randomness shifts you down the leaderboard we reserve the right to adjust your rank to the closest score that your submission reproduces.
• Custom packages in your submission notebook will not be accepted.
• You may only use tools available to everyone i.e. no paid services or free trials that require a credit card.

Documentation

A README markdown file is required

It should cover:

• How to set up folders and where each file is saved
• Order in which to run code
• Explanations of features used
• Environment for the code to be run (conda environment.yml file or an environment.txt file)
• Hardware needed (e.g. Google Colab or the specifications of your local machine)
• Expected run time for each notebook. This will be useful to the review team for time and resource allocation.

Your code needs to run properly, code reviewers do not have time to debug code. If code does not run easily you will be bumped down the leaderboard.

Consequences of breaking any rules of the challenge or submission guidelines:

• First offence: No prizes for 6 months and 2000 points will be removed from your profile (probation period). If you are caught cheating, all individuals involved in cheating will be disqualified from the challenge(s) you were caught in and you will be disqualified from winning any challenges for the next six months and 2000 points will be removed from your profile. If you have less than 2000 points to your profile your points will be set to 0.
• Second offence: Banned from the platform. If you are caught for a second time your Zindi account will be disabled and you will be disqualified from winning any challenges or Zindi points using any other account.
• Teams with individuals who are caught cheating will not be eligible to win prizes or points in the challenge in which the cheating occurred, regardless of the individuals’ knowledge of or participation in the offence.
• Teams with individuals who have previously committed an offence will not be eligible for any prizes for any challenges during the 6-month probation period.

Monitoring of submissions

• We will review the top 10 solutions of every challenge when the challenge ends.
• We reserve the right to request code from any user at any time during a challenge. You will have 24 hours to submit your code following the rules for code review (see above). Zindi reserves the right not to explain our reasons for requesting code. If you do not submit your code within 24 hours you will be disqualified from winning any challenges or Zindi points for the next six months. If you fall under suspicion again and your code is requested and you fail to submit your code within 24 hours, your Zindi account will be disabled and you will be disqualified from winning any challenges or Zindi points with any other account.