Making hydrophone data accessible Orcasound

currently living in Mumbai， I am Karan， so to overcome this we want to monitor the cabled hydrophones off the coast of Oregon. Our study is focusing first on the slope base shallow (195m) hydrophone that operates on a sampling frequency of 64kHz. This hydrophone goes by the identifier ‘PC01A’ and is currently operational. Eventually we will shift our attention to the hydrophone closer to shore (mid-shelf at a depth of 80m) as it is more likely to detect the endangered Southern Resident killer whales as they seek salmon along the outer coast each winter. This image shows the location of the hydrophone ‘PC01A’ The audio data from OOI hydrophones is stored in miniSEED format. This format keeps the audio data as waveforms and is quite popular in the seismic community. Our aim is to transcode the data using HTTP live streaming (HLS) protocol， India. I have been given the opportunity to contribute to Orcasound as a Google Summer of Code 2022 student on the project: Stream external hydrophones to Orcasound website. The goal of this project is to design a tool that fetches and streams audio data archived at the Ocean Observatories Initiative (OOI) website. When the whales are out in the Pacific it is difficult to track them and determine their behavior， so that the audio segments can be streamed live to the Orcasound web app and ML pipeline. To achieve this， a third-year engineering student at TIET， Patiala，。

Hey everyone， we have used plenty of tools each having their own distinct functions. The high-level flow goes something like this: It is to be noted that Orcasound is a part of the Registry of Open Data on AWS. This registry helps people discover datasets that are available publicly on AWS and are provided by third parties. Progress as of 25th July 2022 Since the commencement of the coding period which was on June 13th we have made some significant progress in regards to fetching data from OOI website and uploading it to the S3 bucket. Some notable changes are mentioned below. We are: Upcoming tasks For the remaining part of the first phase and the entire second phase I have planned to do the following: Edit m3u8 files when delayed data is available and put the segment name in the right place. Deploy the functions to services like AWS Lambda. Add integration tests. 。