System for air composition estimation

1 . A computing platform comprising:

at least one processor;

a communication interface communicatively coupled to the at least one processor; and

memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

train, based on historical sets of environment information, and known air compositions, an environment analysis model, wherein the training of the environment analysis model configures the environment analysis model to output estimated air compositions;

receive, via the communication interface from one or more environment information sources, a set of environment information corresponding to an environment, wherein the set of environment information comprises:

one or more measured variables corresponding to one or more attributes of a known particle, and

one or more additional environment variables;

provide the one or more measured variables and the one or more additional environment variables as input to the environment analysis model, to generate an estimated air composition;

generate, based on the estimated air composition, a cumulative particle score;

determine whether or not the cumulative particle score satisfies a criteria, wherein the criteria indicates whether the environment is a compliant environment or an outlier environment; and

send, based on the determination, one or more commands directing a user device to display a user interface, wherein the user interface comprises a notification indicating a result of the determination.

2 . The computing platform of claim 1 , wherein the estimated air composition identifies, based on the one or more additional environment variables, one of two or more different particle types corresponding to the same one of the one or more attributes of the known particle.

3 . The computing platform of claim 1 , wherein the one or more additional environment variables comprise one or more of:

wind speed, wind direction, particle concentration, gas concentration, temperature, relative humidity, air pressure, dew point, vibration frequency, noise level, ventilation status, altitude, topographical information, occupancy, traffic counts, mold growth information, mildew growth information, population information, luminosity information, precipitation information, or virus detection information.

4 . The computing platform of claim 1 , wherein the one or more attributes of the known particle comprise a measurable attribute of a particle in the environment, including:

particle size,

particle count,

particle concentration,

particle vibration frequency, or

particle movement speed.

5 . The computing platform of claim 1 , wherein the estimated air composition comprises one or more particle types, wherein each of the one or more particle types corresponds to one of the one or more attributes.

6 . The computing platform of claim 1 , wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

receive, from the one or more environment information sources, sets of additional environment information corresponding to the environment, wherein each of the sets of additional environment information further corresponds to a specific period of time;

generate, based on the sets of additional environment information and the set of environment information, one or more expected particle score bands corresponding to one or more additional periods of time; and

cause, based on one or more commands directing the user device to display a particle score interface, wherein the particle score interface comprises the one or more expected particle score bands and the cumulative particle score.

7 . The computing platform of claim 6 , wherein determining whether or not the cumulative particle score satisfies the criteria comprises determining whether or not the cumulative particle score is within the one or more expected particle score bands.

8 . The computing platform of claim 1 , wherein the one or more additional environment variables comprise information indicating compositions of particles.

9 . The computing platform of claim 1 , wherein the one or more environment information sources comprise one or more non-static devices, and wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

send, to the one or more non-static devices, one or more additional commands directing the one or more non-static devices to display an additional user interface, wherein the additional user interface comprises an additional notification indicating the result of the determination.

10 . The computing platform of claim 9 , wherein the one or more non-static devices comprise one or more mobile communication devices or one or more wearable devices.

11 . The computing platform of claim 1 , wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to: determine a calibration of a particle sensor based on the set of environment information.

12 . The computing platform of claim 1 , wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

determine, based on the set of environment information and using the environment analysis model, a source of one or more particles identified in the estimated air composition; and

update, based on the source of the one or more particles identified in the estimated air composition, the estimated air composition.

13 . The computing platform of claim 1 , wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

determine the user device corresponds to a specific geographic location, wherein the sending of the one or more commands is based on the determination that the user device corresponds to the specific geographic location.

14 . The computing platform of claim 1 , wherein the one or more environment information sources comprise one or more of:

a particle sensor, a network of sensors located at different geographical locations, a repository of information gathered by multiple unassociated sensors, satellites gathering environmental information, a repository of automotive traffic information, one or more devices gathering environment information of an interior of a building, one or more devices gathering environment information from a moving vehicle, one or more anemometers, or a database corresponding to an enterprise organization.

15 . The computing platform of claim 1 , wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

cause, based on the determination, activation of an air filtration device corresponding to an installation location of the one or more environment information sources.

16 . The computing platform of claim 1 , wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

based on determining whether the cumulative particle score satisfies the criteria, updating an environmental profile to include an indication of whether the environment is a compliant environment.

17 . The computing platform of claim 1 , wherein the notification indicating the result of the determination comprises a haptic response.

18 . A method comprising, by a computing platform comprising at least one processor, a communication interface, and memory:

training, based on historical sets of environment information, and known air compositions, an environment analysis model, wherein the training of the environment analysis model configures the environment analysis model to output estimated air compositions

receiving, from one or more information sources and via the communication interface, a set of environment information corresponding to an environment, wherein the set of environment information comprises:

one or more measured variables corresponding to one or more attributes of a known particle, and

one or more additional environment variables;

providing the one or more measured variables and the one or more additional environment variables as input to the environment analysis model to generate an estimated air composition;

generating, based on the estimated air composition, a cumulative particle score;

determining whether or not the cumulative particle score satisfies a criteria, wherein the criteria indicates whether the environment is a compliant environment or an outlier environment; and

sending, based on the determination, one or more commands directing a user device to display a user interface, wherein the user interface comprises a notification indicating a result of the determination.

19 . The method of claim 18 , further comprising, by the computing platform:

determining, based on the set of environment information and using the environment analysis model, a source of one or more particles identified in the estimated air composition; and

updating, based on the source of the one or more particles identified in the estimated air composition, the estimated air composition.

20 . A system comprising a plurality of sensors and a computing platform:

wherein each sensor of the plurality of sensors comprises a transmitter and a detector, is located in a respective one of a plurality of geographic locations, and is configured to:

determine, using the detector, one or more measured variables corresponding to one or more attributes of a known particle in the respective one of the plurality of geographic locations of the sensor, and

transmit information indicating the one or more measured variables and the one or more attributes of the known particle to the computing platform; and

wherein the computing platform comprises a receiver, a processor, and a memory storing computer-readable instructions that, when executed by the processor, causes the computing platform to:

train, based on historical sets of environment information, and known air compositions, an environment analysis model, wherein training the environment analysis model configures the environment analysis model to output estimated air compositions;

receive, via the receiver, the information from each of the plurality of sensors;

receive an additional environment variable;

provide the one or more measured variables and the additional environment variable as input to the environment analysis model, to generate an estimated air composition of the plurality of geographic locations;

generate, based on the estimated air composition, a cumulative particle score;

determine, based on the estimated air composition, whether the plurality of geographic locations is a compliant environment or an outlier environment; and

send, based on the determination of whether the plurality of geographic locations is a compliant environment or an outlier environment, one or more commands directing a user device to display a user interface, wherein the user interface comprises a notification indicating a result of the determination of whether the plurality of geographic locations is a compliant environment or an outlier environment.