Multi-sensor synergy
Disclosed herein are methods, apparatuses, non-transitory computer readable media, and systems for performing synergistic sensing an attribute of an environment of a facility. Sensing may be performed by sensors of a facility from which a first sensor measures a first attribute at its first sampling rate. Due to a correlation of the first sensor and a second sensor that measures a second attribute at a second sampling rate slower than the first sampling rate, the second attribute can be determined and/or predicted at least in part by using measurements of the first attribute by the first sensor.
1 . A method of determining an attribute, the method comprising:
using a first sensor to measure a first attribute at a first sampling rate, the first sampling rate being faster than a second sampling rate of a second sensor configured to sense a second attribute;
using the first sensor to collect first sensed data during a period of time at the first sampling rate;
using a third sensor to measure a third attribute at a third sampling rate, the third sampling rate being faster than the second sampling rate of the second sensor;
using the third sensor to collect third sensed data during the period of time at the third sampling rate, wherein the third sensor comprises a different sensor type than the first sensor;
obtaining data indicative of an occurrence of an activity during the period of time;
responsive to obtaining the data indicative of the occurrence of the activity:
(i) evaluating, by an artificial intelligence, the first sensed data to determine a first correlation between the activity and a first range of values of the first sensed data, and
(ii) evaluating, by the artificial intelligence, the third sensed data to determine a second correlation between the activity and a third range of values of the third sensed data;
determining, by the artificial intelligence, a relationship between the activity, the first range of values, and the third range of values, wherein determining the relationship is based at least in part on the first correlation and the second correlation; and
determining, by the artificial intelligence, the second attribute at least in part by using measurements of the first attribute by the first sensor and the third attribute by the third sensor rather than measurements of the second sensor, the first, second, and third sensors being of a facility.
2 . The method of claim 1 , wherein the second attribute comprises an activity.
3 . The method of claim 2 , wherein the activity comprises (i) cleaning of an enclosure, (ii) movement of one or more personnel in the enclosure, (iii) a change in an environmental condition, (iv) one or more personnel entering into the enclosure, (v) one or more personnel exiting the enclosure, (vi) activity in the enclosure, (vii) exceeding of a maximum occupancy of the enclosure, or (viii) an arrival of a vehicle at a transportation hub.
4 . The method of claim 3 wherein the environmental condition comprises a weather condition, a sound level, an electromagnetic radiation level, an air quality level, a gas level, a particulate matter level, or a volatile organic compound level.
5 . The method of claim 3 wherein the transportation hub comprises an airport, a train station, a bus station, a tram stop, a ferry slip, a pilot station, a sailing station, or any other transit station; and wherein optionally the other transit station comprises a rapid transition station.
6 . The method of claim 3 wherein the vehicle comprises an airplane, a train, a bus, a car, a subway car, a light rail car, a tram, a ferry, a boat, a ship, a helicopter, or a rocket; and optionally wherein the car comprises a taxi car.
7 . The method of claim 1 , wherein the second attribute comprises occupancy status of an enclosure, number of occupants in the enclosure, sound, electromagnetic radiation, an indicator of a level of comfort, an indicator of energy efficiency, air quality, temperature, gas, particulate matter, or volatile organic compounds.
8 . The method of claim 7 , wherein the second attribute that comprises gas comprises one or more of: gas type, velocity, and pressure.
9 . The method of claim 7 , wherein the second attribute that comprises gas comprises one or more of: humidity, carbon dioxide, carbon monoxide, hydrogen sulfide, radon, nitrogen oxides, halogen, organic halogens, and formaldehyde.
10 . The method of claim 1 , wherein the second sensor and the first sensor are disposed in the facility.
11 . The method of claim 1 , wherein the second attribute comprises temperature, sound, pressure, humidity, gas, particulate matter, volatile organic compound, or electromagnetic radiation.
12 . The method of claim 11 , wherein the gas comprises carbon dioxide, carbon monoxide, radon, or hydrogen sulfide.
13 . The method of claim 1 , wherein the second attribute is associated with an activity that comprises a human activity or a mechanical activity.
14 . The method of claim 1 , wherein the first sensor is utilized to control an environment of the facility.
15 . The method of claim 1 , wherein the first sensor and the third sensor are disposed in a housing, and the method further comprising synergistically and/or symbiotically evaluating measurements of the first sensor and measurements of the third sensor to determine and/or predict the second attribute.
16 . The method of claim 1 , wherein the artificial intelligence comprises machine learning.
17 . The method of claim 1 , wherein (i) the first sensed data, (ii) the third sensed data, or both the first sensed data and the third sensed data, occur prior to and/or during the occurrence of the activity.
18 . The method of claim 1 , further comprising:
modeling a relationship between the second attribute and the first sensed data and the third sensed data for a specific environmental type; and
establishing, by the artificial intelligence, an environmental profile for the specific environmental type based on the modeled relationship.
19 . A non-transitory computer readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform an operation, the operation comprising:
using, or directing use of, a first sensor to measure a first attribute at a first sampling rate, the first sampling rate being faster than a second sampling rate of a second sensor configured to sense a second attribute;
collecting, or directing collection of, the first sensor to collect first sensed data during a period of time at the first sampling rate;
using, or directing use of, a third sensor to measure a third attribute at a third sampling rate, the third sampling rate being faster than the second sampling rate of the second sensor;
collecting, or directing collection of, the third sensor to collect third sensed data during the period of time at the third sampling rate, wherein the third sensor comprises a different sensor type than the first sensor;
obtaining, or directing obtaining of, data indicative of an occurrence of an activity during the period of time;
responsive to obtaining the data indicative of the occurrence of the activity:
(i) evaluating, or directing evaluation of, by an artificial intelligence, the first sensed data to determine a first correlation between the activity and a first range of values of the first sensed data; and
(ii) evaluating, or directing evaluation of, by the artificial intelligence, the third sensed data to determine a second correlation between the activity and a third range of values of the third sensed data;
determining, or directing determination of, by the artificial intelligence, a relationship between the activity, the first range of values, and the third range of values, wherein determining the relationship is based at least in part on the first correlation and the second correlation; and
determining, or directing determination of, by the artificial intelligence, the second attribute at least in part by using measurements of the first attribute by the first sensor and the third attribute by the third sensor rather than measurements of the second sensor, the first, second, and third sensors being of an environment.
20 . An apparatus, comprising:
a device ensemble comprising a first sensor, a second sensor, a third sensor, and at least one processor, the device ensemble being configured to:
measure a first attribute by the first sensor at a first sampling rate, the first sampling rate being faster than a second sampling rate of the second sensor configured to sense a second attribute;
collect, using the first sensor, first sensed data during a period of time at the first sampling rate;
measure a third attribute by the third sensor at a third sampling rate, the third sampling rate being faster than the second sampling rate of the second sensor;
collect, using the third sensor, third sensed data during the period of time at the third sampling rate, wherein the third sensor comprises a different sensor type than the first sensor;
obtaining, by the at least one processor, data indicative of an occurrence of an activity during the period of time; and
responsive to obtaining the data indicative of the occurrence of the activity, the at least one processor is configured to:
(i) evaluate, implementing an artificial intelligence, the first sensed data to determine a first correlation between the activity and a first range of values of the first sensed data;
(ii) evaluate, by implementing the artificial intelligence, the third sensed data to determine a second correlation between the activity and a third range of values of the third sensed data;
(iii) determine, by implementing the artificial intelligence, a relationship between the activity, the first range of values, and the third range of values, wherein determining the relationship is based at least in part on the first correlation and the second correlation; and
(iv) determine, by implementing the artificial intelligence, the second attribute at least in part by using measurements of the first attribute by the first sensor and the third attribute by the third sensor rather than measurements of the second sensor, the first, second, and third sensors being of an enclosure.