DETERMINING AUDIO OUTPUT FOR AQUACULTURE MONITORING MODELS
Methods, systems, and apparatus, including medium-encoded computer program products, for receiving outputs from a plurality of models that are each informed by real-time data provided by one or more sensors that are present in an aquaculture environment. An input is generated for an algorithmic music composer for algorithmically composing music that reflects multiple current conditions within the aquaculture environment, based at least on the received outputs from the plurality of models. The input is provided to the algorithmic music composer to algorithmically compose the music that reflects the multiple current conditions within the aquaculture environment.
1 . A computer-implemented method comprising:
receiving outputs from a plurality of models that are each informed by real-time data provided by one or more sensors that are present in an aquaculture environment;
generating an input for an algorithmic music composer for algorithmically composing music that reflects multiple current conditions within the aquaculture environment, based at least on the received outputs from the plurality of models; and
providing the input to the algorithmic music composer to algorithmically compose the music that reflects the multiple current conditions within the aquaculture environment.
2 . The computer-implemented method of claim 1 , wherein generating the input comprises processing one or more features using a machine learning model.
3 . The computer-implemented method of claim 2 , wherein the features include an indicator of one or more target users.
4 . The computer-implemented method of claim 1 , wherein the input is generated in real-time.
5 . The computer-implemented method of claim 1 , wherein the input describes characteristics of sound.
6 . The computer-implemented method of claim 1 , wherein the input identifies one or more songs.
7 . The computer-implemented method of claim 1 wherein generating the input comprises evaluating a plurality of rules.
8 . A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising:
receiving outputs from a plurality of models that are each informed by real-time data provided by one or more sensors that are present in an aquaculture environment;
generating an input for an algorithmic music composer for algorithmically composing music that reflects multiple current conditions within the aquaculture environment, based at least on the received outputs from the plurality of models; and
providing the input to the algorithmic music composer to algorithmically compose the music that reflects the multiple current conditions within the aquaculture environment.
9 . The system of claim 8 , wherein generating the input comprises processing one or more features using a machine learning model.
10 . The system claim 9 , wherein the features include an indicator of one or more target users.
11 . The system of claim 8 , wherein the input is generated in real-time.
12 . The system of claim 8 , wherein the input describes characteristics of sound.
13 . The system of claim 8 , wherein the input identifies one or more songs.
14 . The system of claim 8 , wherein generating the input comprises evaluating a plurality of rules.
15 . One or more non-transitory computer-readable storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:
receiving outputs from a plurality of models that are each informed by real-time data provided by one or more sensors that are present in an aquaculture environment;
generating an input for an algorithmic music composer for algorithmically composing music that reflects multiple current conditions within the aquaculture environment, based at least on the received outputs from the plurality of models; and
providing the input to the algorithmic music composer to algorithmically compose the music that reflects the multiple current conditions within the aquaculture environment.
16 . The one or more non-transitory computer-readable storage media of claim 15 , wherein generating the input comprises processing one or more features using a machine learning model.
17 . The one or more non-transitory computer-readable storage media of claim 16 , wherein the features include an indicator of one or more target users.
18 . The one or more non-transitory computer-readable storage media of claim 15 , wherein the input is generated in real-time.
19 . The one or more non-transitory computer-readable storage media of claim 15 , wherein the input describes characteristics of sound.
20 . The one or more non-transitory computer-readable storage media of claim 15 , wherein the input identifies one or more songs.