Help Drones, Help Others During Pandemics with NXP


The NXP HoverGames 2 Challenge, which leverages NXP’s  HoverGames drone development kit, kicked off on June 18, 2020. The goal of the competition is for developers to use their coding skills to come up with pioneering ways to use drones to protect people and communities, help healthcare and essential workers, and prevent the spread of the pandemic. Entries can win up to $14,000 in prizes.

The NXP HoverGames is a series of hands-on virtual embedded hardware and coding challenges uniting developers around the world to address some of the biggest challenges facing society using the NXP HoverGames drone development platform. In every NXP HoverGames the challenge will focus on universal issues like disaster management, health crises, environmental protection, wildlife conservation and more. For challenge 2, the focus is on how drones can help others during pandemics.

“The current pandemic has exposed our vulnerability to disease and the general structural breakdown that can occur during a crisis,” said Iain Galloway, Drone Program Lead, Systems Innovation, NXP. “But we don’t have to feel powerless in its wake, we can harness technology to make a difference. We invite contestants to leverage a complete functional system of hardware and software for drone and rover development and to share your creative solutions.”

“A contest like the Hackster.io and NXP HoverGames Challenge demonstrates the powerful problem-solving capabilities of the millions of engineers in our online communities around the world,” said Bill Amelio, Avnet CEO. “We need to guide these brave thinkers to get their ideas through the product lifecycle so they can help with the critical needs in our society, such as the safety of first responders. It is not only our privilege, but our duty, to help give their vision the chance to become a reality.”

Hackster.io, an Avnet company, hosts the challenge on its community website. For more information and contest rules visit: https://www.hackster.io/contests/hovergames2

NXP HoverGames drone development kit

The NXP HoverGames drone development kit is a modular, open development platform which uses reliable automotive and industrial-grade components from NXP. Through the use of this kit, the drone will be PX4-enabled, the largest commercially deployed open-source flight stack worldwide with business-friendly licensing.

The kit contains:

  • Flight Management Unit (RDDRONE-FMUK66 FMU) that’s supported by the opensource PX4.org flight stack on top of NuttX RTOS.
  • Strong, rigid lightweight carbon fiber quadcopter frame with platform, mounting rails, landing gear, motor controllers, motors and props
  • Telemetry radio and remote control (RC) radio

Prizes

Tens of thousands of dollars in prizes will be given to the top 44 projects. The challenge judges will pick the best qualifying 44 projects based on the judging criteria outlined in the rules section.

About Hackster.io

Hackster.io, an Avnet company, is an online developer community with more than 1.4 million members for learning, programming and building hardware.

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Recap of the Top Three NXP HoverGames Challenge 1 Winners

The inaugural NXP HoverGames Challenge “Fight Fire with Flyers”, inspired participants to address the high stakes of urban and rural fires. Contestants considered the challenges facing firefighters and developed unique and disruptive solutions to the problems firefighters face.

First place: Dobrea Dan Marius’s Autonomous Human Detector Drone

One of the main objectives in firefighting is to prevent loss of life. Further it is critical to quickly identify and assist people who have succumbed to the fumes or are lost in debris. The objective of this project is to develop a real-time drone technology system capable of detecting humans in catastrophic conditions such as fires.

In addition to autonomously flying, Dobrea Dan Marius’ drone derives position data from NXP’s FMU RDDRONE-FMUK66 which feeds information to the attached subsystems. With this position information available as a reference, onboard cameras feed video material through a machine learning model that recognizes the human with high accuracy. The drone further has a sonar object-detection system, which is essential to enable it to work autonomously. This project shows that even a limited processor can be of great benefit for edge computing.

Second place: AK’s Machine Learning Fire-class Analyser

Different types of fire need different responses. AK’s entry helps firefighters identify the cause of a fire, then recommends the most appropriate means of putting it out and the size of crew required. His drone includes a range of fume sensors that feed data into a machine learning model, which in turn predicts the type of material that’s burning. Particularly impressive was the way AK trained the machine learning system, rather than using a pre-trained model, and continually refined it to drive up the accuracy of its predictions.

Third place: Tatsuya Iwai’s Lightning-detection System

Tatsuya points out that lighting is a significant cause of wildfires – and it can happen pretty much anytime, anywhere, including in very remote locations. Tatsuya’s drone helps authorities keep their fingers on the pulse by sensing lightning at distances of up to 40 km. He also tested a means of detecting burning fires with the drone, including using image recognition and thermal sensors.


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