Overview Fab City Hamburg Agricultural Projects
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According to different sources, the world population is expected to reach 9.1 billion people by 2050, i.e., roughly 20% more than in 2021. Out of those 9.1 billion people, it is estimated that 70% of them will be living in urban areas, in contrast to the 55% observed today.
Additionally, the levels of extreme poverty have been significantly reduced during the last century, allowing more people to have access to a better and more varied nutrition. Together with the expected increase of more bio-based resources, such as plastics, bio-fuels, or fabrics, the agricultural production will need to increase around 70% to cover the demand.
If that were not enough, we should not forget the global climate crisis we are facing and its consequences for agriculture.
What are we doing?
In Fab City Hamburg we believe that new technologies, such as Artificial Intelligence (AI) and Machine Learning (ML), together with robotics, and Internet of Things (IoT) systems can help solve some of the challenges mentioned above.
However, in order for these technologies and their application to have a tangible impact, we need them to be globally accessible and not a privilege of the rich countries and farmers. This is the main reason why we are adopting an Open Source framework, which allows to easily share and have access to the information for anyone interested. Additionally, this allows a community-driven growth at a global scale, i.e., anyone in the planet can freely contribute and utilize, democratizing the knowledge.
One of our proposals is to automate some of the most laborious and exhausting farming tasks through AI/ML-based robotic systems, improving their overall working conditions. The implementation of an automatic weed detection and removal system would for instance allow the farmers to focus on other potentially more critical tasks, and would also enable them to contribute to the development of other innovative solutions to improve their daily work.
Most of the state-of-the-art AI and ML models used to solve image-related tasks require a significant amount of examples in order to learn the desired visual patterns. The collection of the aforementioned examples are the so-called datasets. The size and quality of the datasets are determining factors for the quality of the resulting AI/ML models, which is commonly phrased as "garbage in, garbage out".
Therefore, part of the efforts used to construct the smart agricultural robotic systems within the Fab City Hamburg will be tightly linked to the compilation of the open data-sources required for the training and evaluation of the developed AI/ML models.
How are we doing it?
We strongly believe that working together in multidisciplinary teams with people of diverse backgrounds is key to tackle this kind of challenging problems. Especially when it comes to agriculture, there is nothing more common across cultures and regions than the food we all need, and the health of the planet we all live in.
Hence, one of the first steps we have taken in this project has been creating a local, regional, and international community. The local and regional team is integrated by members representing the Fab City Hamburg, the Climate Protection Foundation of Hamburg, and the Helmut Schmidt University. At a more international scale, the Fab City network is the main gate for collaboration.
During the FabCity Summit that took place in August 2021, we as a team had the opportunity to share, not only our ambitions, but most importantly our mission and vision for this project. This exchange lead to a very enriching and constructive discussion with the international community and opened the chance for potential future interesting collaborations.