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Drones and AI to Compliment Rescue Operations

Enterprise Technology Review | Wednesday, July 24, 2019

The recent technological transformations, such as the introduction of aerial robots or drones, can gear up the rescue and search operations.

FREMONT, CA: Outdoor enthusiasts love nature and regularly engage in activities such as hiking, camping, mountain biking, kayaking, skiing, rafting, and others. However, sometimes, the craving for adventures results in unwanted consequences, and the adventurer ends up stranded in a critical situation. Though the search and rescue professionals are skillfully trained, their task is still daunting, especially as they have to fight a dual battle against the situation as well as time. The survival chances of a lost person decline dramatically after the first 18 hours.

The recent technological transformations, such as the introduction of unmanned aerial robots or drones, can significantly gear up the rescue and search operations. Ryan Williams, an assistant professor at Bradley Department of Electrical and Computer Engineering, said that the drones would leverage autonomous algorithms and machine learning (ML) to aid in search and rescue operations. The drones can also suggest the next step and provide updated information to the human authority at the ground involved in the process.

Combining Drones and Rescuer’s Approach

Utilization of mathematical models that leverage historical data to understand the behavioral patterns of a lost person can provide significant insights into the rescue operations. The insights combined with a typical searcher’s approach can make searches more effective. Drones are also useful while scaling treacherous landscapes because investing in human efforts can be both dangerous and time-consuming. For instance, Nicole Abaid, an assistant professor of Biomedical Engineering and Mechanics, is utilizing data gathered from 50,000 cases of lost person scenarios. He is aiming to design a mathematical model that will assist the drones on where to go and search.

From the past search data, it is possible to understand the behavior and activities of a specific type of people when they are lost. For instance, a person with a cell phone might move up in elevation to get a better network, while an older person might not go far.

Though human-robot collaboration might seem abstract, a close partnership among the two will produce meaningful results for real-world rescue and search operations.

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