High-Level Project Summary
"Hatun qucha" is an application program plan developed by Allpa Kawsay equipment that aims to detect Marine Plastic Debris in real time, according to its spectral signature, over the marine area. It is necessary to point out the monitoring of marine debris by means of recent tools such as the use of remote sensing AI (artificial intelligence) and the monitoring by means of spectral signatures made by space stations around the world will primarily allow us immediate responses. before these inconveniences.
Link to Project "Demo"
Link to Final Project
Detailed Project Description
“Hatun qucha” is an application software project developed by the Allpa Kawsay team that aims to detect Marine Plastic Debris in real time, according to its spectral signature, on the sea surface. In this regard, the idea consists in the processing of satellite images (for this contest the Sentinel 2A / 2B images) using the code "Ocean Plastic Detector Prototype Script" in the Google Earth Engine platform, these results train them in AI / ML platforms to In order to identify, monitor, quantify and classify them according to their spectral signature, according to the international spectral signature data bank and those obtained in field work, this will facilitate their discrimination among other objects on the sea surface such as sediments, plankton, etc. The results and conclusions obtained with these techniques benefited from stakeholders interested in the monitoring and detection of marine pollution and decision-makers of actions on environmental issues. It is necessary to point out the monitoring of marine debris through current tools such as the use of remote sensing, artificial intelligence and monitoring through spectral signatures made by space stations worldwide will mainly allow us immediate responses to these problems.
Space Agency Data
In this regard, the idea consists in the processing of satellite images (for this contest the Sentinel 2A / 2B images) using the code "Ocean Plastic Detector Prototype Script" in the Google Earth Engine platform, these results train them in AI / ML platforms to In order to identify, monitor, quantify and classify them according to their spectral signature, this will facilitate their discrimination between other objects on the sea surface such as sediments, plankton, etc. in a good way we can collect field information, for example, from the survey by drones in areas that are close to the beach as well as images from the national satellite of Peru El Perú SAT, one of the space agency with ida that will allow us to have many more images accurate and up-to-date information on our territory in order to identify marine plastic debris, be able to vary its size, its composition, its class, as well as its behavior and predict in some way where it would go in order to take into account its impact on marine fauna, which allows us monitor in a better way with updated data and in real time the events on the marine coastline.
Hackathon Journey
It was a very enriching experience for all the members of the team that improved us to show our skills and abilities to be able to solve the challenges posed during the hackathon.
We learned technology knowledge from different media such as software, as well as the linking of satellite images that are currently available to free and public users, as well as the creation and management of algorithms based on artificial intelligence and linear regression.
Many setbacks were handled between them in being away and not together in the same environment, however, by organizing the schedule and working together and multidisciplinary, it was possible to face the pertinent challenges.
References
Marine Debris: Garbage Patch Experiment
EOSDIS Ocean Data
Tags
#Hatun_Qucha, #IA, #Sensoring_Remote
Global Judging
This project has been submitted for consideration during the Judging process.