How can we offload data from drones more effectively?

$1,000 USD

Challenge overview

Scholars propose a way to help mobile robots choose when to communicate with the cloud without latency or lost data issues.

Futurists imagine skies someday buzzing with autonomous drones that use artificial intelligence algorithms to monitor traffic, deliver packages, and keep tabs on the world in myriad other ways. Lacking the energy or computational horsepower for the intense mathematics required to analyze all that information, many drones can send visual data to massive central servers that crunch the numbers and beam back results when they are uncertain what they are seeing. Unfortunately, transferring this data takes precious time and bandwidth that can slow or even stop a drone dead in its tracks

In such autonomous applications, there are two types of visual data analysis. One occurs in real time and helps a drone navigate and avoid accidents. The second, called continual learning, helps the drone improve its recognition skills so it can learn when confronted with new or confusing information. This second analysis is more computationally intensive and may require human intervention to annotate imagery or identify objects and actions new to the robot.

In this challenge we will be looking for solutions for more effective data offloading.

Add your solutions by September 2022! 

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