In this episode, we talk about how TUM researchers are trying to model the effects of climate change on forest fires using a neural network, why robots assisting with getting dressed is more challenging than it seems, and how drones are being used to safely evacuate the elderly in nursing homes during emergencies. As always, you can find these and other interesting & impactful engineering articles on Wevolver.com.
(0:45) - Modeling How Climate Change Impacts Forest Fires:
Wildfires have been wreaking havoc on the nation’s forests and it is now more important than ever to understand how our changing climate is impacting our most treasured ecosystems. Computer simulations can provide great insight but when considering the number of variables that contribute to forest fires it becomes clear that traditional approaches would be too computationally intensive to be feasible. That’s where the researchers at the Technical University of Munich come in: they’ve built a neural network capable of recognizing patterns between the key parameters that result in forest fires which uses only a fraction of the computational power required via the traditional approach.
(6:35) - Getting Dressed With Help From Robots:
Do you find yourself thinking “I wish a robot could do this” when dressing yourself in the morning? Well, soon you might be able to get one of those exact robots in your own home! MIT researchers have been developing a robot to assist people when getting dressed and although they’ve made some impressive progress, there are some bumps they’ve hit on their path all centered around one object: people. People’s varying preferences regarding getting clothed and safety in general has caused their algorithm to become overwhelmed. Regardless, the team is making great progress in the human-robot-interaction front and paving the way for similar future projects.
(15:15) - Drone To Evacuate Nursing Homes In Case Of Emergency:
A student group - named the ‘Blue Jays’ - from Technical University of Eindhoven have developed a drone to calmly guide the elderly out of nursing homes during emergencies. The drone is powered by a neural network to analyze the facial features of people and determine their emotions which it can respond to. Their hope is that this aerial companion can help provide a sense of comfort to those who are distressed while the first responders operating the drone can instruct those in the building on how to safely exit.
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About the podcast:
Every day, some of the most innovative universities, companies, and individual technology developers share their knowledge on Wevolver. To ensure we can also provide this knowledge for the growing group of podcast listeners, we started a collaboration with two young engineers, Daniel Scott Mitchell & Farbod Moghaddam who discuss the most interesting content in this podcast series.
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