Code Black - Space Apps Challenge

Code Black | Spot That Fire V3.0

Spot That Fire V3.0

Recent wildfires worldwide have demonstrated the importance of rapid wildfire detection, mitigation, and community impact assessment analysis. Your challenge is to develop and/or augment an existing application to detect, predict, and assess the economic impacts from actual or potential wildfires by leveraging high-frequency data from a new generation of geostationary satellites, data from polar-orbiting environmental satellites, and other open-source datasets.

Exferno

Summary

IntroductionBased on unmanned aerial vehicles assisted Internet of things (UAV-IoT) networks and Artificial intelligenceStudies general behavior of animalsDevelops drones by increasing the efficiency and quality of their fire detectionAble to extinguish the fire and prevent the spread of the fire in the surrounding areas.Develops a new system to use drones in wildfires.Provides Popular fire detection techniques such as satellite imaging and remote camera-based sensing suffer from late detection and low reliability while early wildfire detection is a key to prevent massive fires.Provides solar cells as solar energy is renewable clean energy, also we thought that if we collect more sun

How We Addressed This Challenge

In recent years, the frequency, intensity, and extent of forest fires, as well as the economic and human health impacts, have increased dramatically worldwide, and to mitigate future losses and the overall impact on societies We have developed and are addressing solutions that are appropriate to these impacts because delayed detection of forest fires; we have proposed a new forest fire detection solution based on unmanned aerial vehicles assisted by IoAV-IoT and artificial intelligence.

Our project will reduce fire detection time by reducing false alarms and issuing timely responses and notifications to fire services in the event of real forest fires and based on early fire detection, we can respond quickly from fire departments or other ways to start the fire classification process and try to extinguish it most appropriately.

This will be accomplished by using two types of drones (a fixed-wing drone-a drone with circuit-wings), both of which will be equipped with cameras, which will be visual, thermal, or both. The fixed-wing drone will conduct continuous patrols in the observation area, if the fixed-wing drone detects a fire, it will sound an alarm. The drone with its rotating wings will examine the area closely, and the role of the second drone is to either confirm or reject the alarm rules when it monitors the area and then returns to its station

If the fire is confirmed, another alert will be launched by the rotary-wing drone at that time, a signal from the drone will be sent to repair the drone. This signal will require the drone to release carbon dioxide contained in cylinders in drones that hold the wings surrounding the detected fire area, to extinguish the fire, and prevent the spread of the fire in the surrounding areas. This is based on the aircraft's communication with ground control centers and satellites to consolidate and analyze data to reduce the risks expected based on data analysis,

This is based on the fact that these aircraft are connected to ground control centers and satellites to consolidate and analyze data to reduce the risks expected based on data analysis. One of the most common problems encountered is the short-term limit that drones can spend airborne because batteries run out of charge. We have used solar energy as a sustainable energy source for drones and use solar batteries to store and use it overnight. We have thus provided fully all-day control, GPS positioning, data analysis, and integration. After the fire classification, we have proposed a new fire extinguishing cylinder, using a CO2-laden compressed gas cylinder, which will be used to enclose and extinguish the entire fire area.

How We Developed This Project

We are working on associating machine learning fire prediction models using drones. It will detect potential fire locations, as they are likely areas with current weather conditions as warm temperatures, and animals escape; it might be with fire history besides. This will help to early warn the users for precautions and firefighting stations to mostly prevent damages estimated at billion dollars!

Software

Notepad++ (programming)
Arduino IDE (programming)
Adobe Photoshop 2019
SolidWorks (creating demo project)
Animaker (presentation video edit)

Hardware

An average drone
A solar cell (battery charge of the drone)
2x high-powered 9V battery (power source)
MQ-2 Smoke Sensor (detection of smoke, methane leaks, butane leaks, etc.)
Flame Sensor (detects a wavelength range of 760nm - 1100nm, used for detecting signs of fire)
GPS Module NEO-6M (to find longitude and latitude of the drone)
DHT22 Temperature Sensor (to measure ambient temperature, humidity level, and heat index)
Camera module (takes a picture of an area every 30 seconds, and stores it to the SD card for further image processing)

We encountered many problems at the beginning when we started using drones

problem 1: The short time of drone flies due to the lack of battery power

Achievement 1: replaced it with solar cells To keep it longer in the sky.

Problem 2: Drones used only to detect fire

Achievement 2: Have changed the system in which the drones fly after they were working to discover the location of the fire only. It has also been used in surveying the place by monitoring the movement of animals in the forest because of the remoteness of the drones used in extinguishing the fireplace, we made the large drones capable of carrying them.

Problem 3: Find a substance used in firefighting

Achievement 3: Found a substance that works with a light mechanism to help us extinguish so we used CO2.

How We Used Space Agency Data in This Project

Knowing more about wildfires in the last period And the systems used to extinguish forest fires. -Knowing about drones, their working and flying mechanism, their places of landing and ascending over time or during their work, and ways to keep them safe, etc.

Learn about some operational scenarios that simulate a variety of drones use cases including video surveillance.

With a review of the UTM flight system, we have defined the flight mechanism of both drones in our solution.

Create a general perception about our "solution" idea, where to learn about fire hazards in forests, and learn more about early detection of fires in forests specifically using UAVs, which work depending on artificial intelligence (AI).

The appropriate classification of fires, and quick response to them,

More about the mechanism of the way drones work and the common mistakes during use, as the problem of false alarms, and the late detection of fires, which helped to start creative thinking to solve these problems

Based on various fundamentals and concepts we got from sources

And learn more information on how to use NASA data, use GPS, and link it to satellites to facilitate locating drones.