In the past 20 years, more than 600.000 lives were lost to natural catastrophes 2. The golden period to rescue trapped survivors is between six and twelve hours after the sudden impact. Despite this fact, most of the rescue teams arrive much later, thus often the amount of rescued people is minimal.
RESCUE is a platform developed to reduce the response times in natural disasters.
Deploying a network of economic and self-flying drones, the city is explored and analyzed in real time through a video sequence, and with the use of computer algorithms and machine learning algorithms, can be detected possible threats and immediate emergency situations, such as large fires and people trapped.
In conjunction with a web platform available to suitable civil defense organization, RESCUE has a map with various markers that represent real-time emergency situations, allowing operators to detect them and react quickly, thus saving countless lives.
Our goal is to minimize the number of victims and reduce costs to ensure that no region is excluded because of a lack of financial resources, so we want to be a non-profit organization offering the platform for free and the drones at their cost.
We are a group of 3 software engineering students. We’re passionate about developing solutions using exponential technologies. Through tools offered by fields of study such as Machine Learning, Deep Learning, Natural Language Processing and Computer Vision, we seek to create products that can improve societies, reducing inconveniences and enhancing the ways to solve major problems.
Our current topic of interest is Health and Education, disruptive ideas that break down the walls imposed by antiquated solutions that nowadays only obstruct the path to a better future.