AI and Applications

Farm-to-Plate AI: Enhance Freshness and Reduce Waste with Robotics and Computer Vision

In the Sustainable Development Goals report for 2022, the United Nations found that nearly 1 in 3 people lacked regular access to adequate food in 2020. At the same time, nearly 13% of food is lost in the food supply chain from harvesting to transport to storage to processing. When food is wasted, so are the energy, land, and resources that were used to create it. We can use emerging technology to develop more sustainable food chains.

Autonomous robots, artificial intelligence and remote sensing technology can optimize farm operations using precision farming, automate harvesting and grading, and monitor food quality during transportation. Reducing waste at each of these stages increases throughput.

In three hands-on exercises, you track the journey of mangoes from a farm that uses autonomous robots to the market while monitoring mango ripeness using hyperspectral images and deep learning. The first exercise introduces a physical model of a robot that surveys a virtual mango farm using an obstacle-avoidance algorithm. In the second exercise, you use images captured by the robot to count mangoes and estimate the harvest yield. In the final exercise, you use hyperspectral images and a machine learning model to monitor the ripeness of the mangoes.

Getting Started with Streamlit for Data Science

Streamlit is a fantastic Python package that allows us to use native Python to create beautiful interactive front-ends for our data science projects. This tutorial will show you how to get started with Streamlit, so you can start creating your own interactive apps.

Seeking Humanity via Technology: How AI Can Be Used to Reduce Maternal Mortality

Maternal mortality continues to be a global issue however, studies over the past 5 years identify a growing alarming trend in the United States with respect to maternal mortality. According to several studies from the Centers for Disease Control, “Black women are three times more likely to die from a pregnancy-related cause than White women”. Many of these same studies have also acknowledged that most pregnancy-related deaths are preventable and that this alarming trend continues to grow. This session will entail providing an overview of historical approaches to this issue. The emphasis of this presentation will identify that Artificial Intelligence (AI) could be used to reduce maternal mortality and how AI could be used to reduce maternal mortality.