The population is growing and our planet’s natural resources are decreasing. As a result, there is an urgent call for sustainable solutions to keep us alive. The scarcity of food in the coming years will be one of the greatest challenges facing humankind. By 2050 we need to figure out how to feed 10 billion people in a sustainable way. Agricultural management still depends heavily on the manual work and cultural practices of farmers. And all of this knowledge and experience is still a long way from being transferred to machines. But imagine if we could create the digital twin of a farmer with even greater experience?
A digital twin of a farmer could be embedded in any robotic system, for example a drone or a human-borne sensing system. And it could significantly improve agricultural management practices, including faster and more accurate crop assessment. Consequently, the decision-making process could be more efficient, avoiding food waste, and increasing food quality and yield in a sustainable fashion.
This is now possible due to a unique and novel artefact that can be used by a farmer without interfering with their farming tasks: A special cap with several sensors. This cap/helmet will capture all of the farmer’s movements and vision when executing farming tasks. The recorded sensor data will allow for the building of a digital twin from a farmer cognitive system using advanced artificial intelligence approaches.
Hybrids look toward the future where humans do not coexist with machines, but instead, the human itself will be another intelligent agent. This project explores the idea of designing personal objects that result in something half human and half machine (cyborgs). Such superpowers could, for instance, augment our cognitive capacity and/or give us the capacity to interact more quickly with other machines (e.g., drones, humanoids) and collaborate in complex tasks with them. Through the design of a farmer cap that empowers the farming management tasks, the cyborg farmer is a step forward towards this vision.
