US20170168487A1 - System and method for tracking pollution - Google Patents

System and method for tracking pollution Download PDF

Info

Publication number
US20170168487A1
US20170168487A1 US14/966,038 US201514966038A US2017168487A1 US 20170168487 A1 US20170168487 A1 US 20170168487A1 US 201514966038 A US201514966038 A US 201514966038A US 2017168487 A1 US2017168487 A1 US 2017168487A1
Authority
US
United States
Prior art keywords
pollution
automated vehicle
automated
concentration
source
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
US14/966,038
Inventor
Kiran Mantripragada
Ulisses Mello
Rafael Horschutz Nemoto
Nicole Barbosa Sultanum
Lucas Correia Villa Real
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
International Business Machines Corp
Original Assignee
International Business Machines Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by International Business Machines Corp filed Critical International Business Machines Corp
Priority to US14/966,038 priority Critical patent/US20170168487A1/en
Assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION reassignment INTERNATIONAL BUSINESS MACHINES CORPORATION ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: VILLA REAL, LUCAS CORREIA, MELLO, ULISSES, MANTRIPRAGADA, KIRAN, NEMOTO, RAFAEL HORSCHUTZ, SULTANUM, NICOLE BARBOSA
Publication of US20170168487A1 publication Critical patent/US20170168487A1/en
Priority to US15/840,470 priority patent/US10268198B2/en
Abandoned legal-status Critical Current

Links

Images

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/02Analysing fluids
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/44Processing the detected response signal, e.g. electronic circuits specially adapted therefor
    • G01N29/4454Signal recognition, e.g. specific values or portions, signal events, signatures
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004Gaseous mixtures, e.g. polluted air
    • G01N33/0009General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0027General constructional details of gas analysers, e.g. portable test equipment concerning the detector
    • G01N33/0036General constructional details of gas analysers, e.g. portable test equipment concerning the detector specially adapted to detect a particular component
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004Gaseous mixtures, e.g. polluted air
    • G01N33/0009General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0062General constructional details of gas analysers, e.g. portable test equipment concerning the measuring method or the display, e.g. intermittent measurement or digital display
    • G01N33/0067General constructional details of gas analysers, e.g. portable test equipment concerning the measuring method or the display, e.g. intermittent measurement or digital display by measuring the rate of variation of the concentration
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0287Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
    • G05D1/0291Fleet control
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/10Simultaneous control of position or course in three dimensions
    • G05D1/101Simultaneous control of position or course in three dimensions specially adapted for aircraft
    • G05D1/104Simultaneous control of position or course in three dimensions specially adapted for aircraft involving a plurality of aircrafts, e.g. formation flying
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2291/00Indexing codes associated with group G01N29/00
    • G01N2291/02Indexing codes associated with the analysed material
    • G01N2291/021Gases
    • G05D2201/0207

Definitions

  • Exemplary embodiments of the present invention relate to tracking pollution. More particularly, exemplary embodiments of the present invention relate to a system and method for tracking pollution by determining pollution concentration gradients with unmanned vehicles.
  • pollution such as air, water, soil or noise pollution
  • Pollution detection equipment may also be mounted at fixed positions in different locations or geographic areas. Pollution may be emitted from a wide array of locations and the pollution may spread over a large geographic area. Spreading pollution may be present at a large range of concentrations in different areas. Pollution may also spread according to patterns that are not readily predicted, such as according to shifting wind patterns or shifting water currents.
  • pollution detection equipment may be disposed in fixed positions over a wide geographic area to detect pollution emitted from a single source. For example, emissions from industrial equipment or a power plant may travel relatively large distances according to wind patterns and pollution emitted from such a source may be present at varying concentrations at varying distances from the emission source.
  • Pollution may be detected at relatively low concentrations in a particular geographic area and the source of the detected solution may be unknown. Thus, it may be desirable to have pollution detection equipment present over a large geographic area to determine pollution concentrations in different areas to determine an origin or source of a particular form of pollution.
  • Exemplary embodiments of the present invention provide a pollution source detection system including an automated vehicle including a position sensor that detects a geographic position of the automated vehicle and at least one pollution detection sensor that measures a concentration of pollution at the automated vehicle.
  • the pollution source detection system includes a back-end system.
  • the back-end system includes a network interface that receives the geographic position and the concentration of the pollution from the automated vehicle.
  • the back-end system includes a database that stores the geographic position and the concentration of the pollution received via the network interface.
  • the back-end system includes a processor that measures a gradient of the concentration of the pollution and controls a movement of the automated vehicle based on the gradient to guide the automated vehicle toward a source of the pollution.
  • the processor may measure the gradient using a numerical model.
  • the processor may measure the gradient in real-time as the automated vehicle moves.
  • the pollution source detection system may include a plurality of automated vehicles including the automated vehicle.
  • Each of the plurality of automated vehicles may include a position sensor that detects a geographic position of the corresponding automated vehicle and at least one pollution detection sensor that measures a concentration of pollution at the corresponding automated vehicle.
  • the processor may aggregate the concentration of the pollution measured by the plurality of automated vehicles, measure an aggregated gradient of the aggregated concentration of the pollution, and control a movement of the plurality of automated vehicles based on the aggregated gradient to guide the plurality of automated vehicles toward the source of the pollution.
  • At least one pollution detection sensor may include a microphone.
  • the pollution may include noise pollution, and the microphone may detect the concentration of the noise pollution.
  • At least one of the pollution sensors may include an air quality sensor.
  • the pollution may include air pollution.
  • the air quality sensor may detect a concentration of the air pollution by detecting a concentration of at least one of O 3 , NO 2 , CO, SO 2 , PM10, PM2.5 and C 6 H 6 .
  • At least one of the pollution detection sensors may include a camera, a hyperspectral sensor, an ultrasound sensor, a thermal sensor, a humidity sensor, a temperature sensor, a pressure sensor, or a corrosion sensor.
  • the position sensor may include a GPS sensor.
  • the position sensor may detect the geographic position in three dimensions.
  • the automated vehicle may be an automated air vehicle that moves through air without contacting ground, an automated ground vehicle that moves on the ground while contacting the ground, or an automated water vehicle that moves in water.
  • the network interface may initially receive a general location at which the pollution is present from a source other than the automated vehicle.
  • the processor may subsequently guide the automated vehicle to the general location and may control the movement of the automated vehicle based on the gradient to guide the automated vehicle toward the source of the pollution within the general location.
  • the processor may perform an inverse geocoding query to detect a company or individual responsible for the source of the pollution.
  • Exemplary embodiments of the present invention provide a method of detecting a source of pollution including detecting a geographic position of an automated vehicle by a position sensor disposed on the automated vehicle.
  • a concentration of the pollution is measured by at least one pollution detection sensor disposed on the automated vehicle.
  • the geographic position and the concentration of the pollution are received via a network interface disposed at a back-end system from the automated vehicle.
  • the geographic position and the concentration of the pollution received via the network interface are stored in a database disposed at the back-end system.
  • the method of detection of a source of pollution includes measuring, by a processor disposed at the back-end system, a gradient of the concentration of the pollution.
  • the method of detection of a source of pollution includes controlling, by the processor, a movement of the automated vehicle based on the gradient to guide the automated vehicle toward the source of the pollution.
  • the processor may measure the gradient using a numerical model.
  • the processor may measure the gradient in real-time as the automated vehicle moves.
  • the method of detection of a source of pollution may include detecting a geographic position of each of a plurality of automated vehicles, including the automated vehicle, by a position sensor disposed on each of the plurality of automated vehicles.
  • a concentration of the pollution may be measured by at least one pollution detection sensor disposed on each of the plurality of automated vehicles.
  • the concentration of the pollution measured by the plurality of automated vehicles may be aggregated.
  • An aggregated gradient of the aggregated concentration of the pollution may be measured.
  • a movement of the plurality of automated vehicles may be controlled based on the aggregated gradient to guide the plurality of automated vehicles toward the source of the pollution.
  • the method of detection of a source of pollution may include initially receiving a general location at which the pollution is present from a source other than the automated vehicle and subsequently guiding the automated vehicle to the general location.
  • the movement of the automated vehicle may be controlled based on the gradient to guide the automated vehicle toward the source of the pollution within the general location.
  • the method of detection of a source of pollution may include performing, by the processor, an inverse geocoding query to detect a company or individual responsible for the source of the pollution.
  • Exemplary embodiments of the present invention provide a computer program product for detecting a source of pollution.
  • the computer program product may include a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to detect a geographic position of an automated vehicle by a position sensor disposed on the automated vehicle.
  • the program instructions executable by the processor cause the processor to measure a concentration of the pollution by at least one pollution detection sensor disposed on the automated vehicle.
  • the program instructions executable by the processor cause the processor to receive the geographic position and the concentration of the pollution via a network interface disposed at a back-end system from the automated vehicle.
  • the program instructions executable by the processor cause the processor to store the geographic position and the concentration of the pollution received via the network interface in a database disposed at the back-end system.
  • the program instructions executable by the processor cause the processor to measure a gradient of the concentration of the pollution and control a movement of the automated vehicle based on the gradient to guide the automated vehicle toward the source of the pollution.
  • FIG. 1 illustrates an example of a pollution source detection system according to an exemplary embodiment of the present invention.
  • FIG. 2 illustrates an example of a pollution source detection system according to an exemplary embodiment of the present invention.
  • FIG. 3 illustrates an example of a pollution concentration gradient of emitted pollution according to an exemplary embodiment of the present invention.
  • FIG. 4 illustrates an example of automated vehicles tracking a source of pollution by a pollution concentration gradient according to an exemplary embodiment of the present invention.
  • FIG. 5 illustrates an example of a dynamic path of an automated vehicle moving toward a pollution source according to an exemplary embodiment of the present invention.
  • FIG. 6 illustrates a flow chart of a method of detecting a source of pollution according to an exemplary embodiment of the present invention.
  • FIG. 7 illustrates an example of a computer system capable of implementing the method according to exemplary embodiments of the present invention.
  • Exemplary embodiments of the present invention relate to tracking pollution.
  • Exemplary embodiments of the present invention may provide a system and method for automatically tracking pollution using automated vehicles. More particularly, exemplary embodiments of the present invention relate to a system and method for tracking pollution by tracking gradient concentration with unmanned vehicles.
  • Pollution may be emitted from a variety of sources and the emitted pollution may spread over a large geographic area.
  • the source of pollution may be a known source, such as a power plant, or an industrial area, or a source of a particular type of solution may be unknown.
  • the emitted pollution may be present at a relatively large range of concentrations. For example, pollution emitted from a particular source may dissipate as distance increases from the emission source. Additionally, concentrations of pollution may vary unevenly with distance from a particular emission source. For example, strong winds in a particular direction may spread air pollution unevenly over a particular geographic area. Thus, concentrations of pollution spreading over a particular geographic area may be difficult to predict and installing or placing emission detection equipment in appropriate locations may be difficult.
  • the concentration of the pollution may be useful for detecting the source of the pollution.
  • pollution may be tracked and/or the source of pollution may be determined by tracking the concentration of pollution using automated or unmanned vehicles according to exemplary embodiments of the present invention.
  • a source of pollution may be a moving source, such as a motorized vehicle.
  • a moving source such as a motorized vehicle.
  • cars, trucks, boats or plains may emit pollution such as air or water pollution and thus the source of this pollution might not be fixed in a specific geographic location.
  • Automated or unmanned vehicles according to exemplary embodiments of the present invention may determine a source of pollution when the source of pollution is such a moving source.
  • the automated or unmanned vehicles according to exemplary embodiments of the present invention may detect the concentration gradient of the pollution emitted from the moving source and may track the emitted pollution by following the concentration gradient toward the mobile pollution source. That is, the automated or unmanned vehicles according to exemplary embodiments of the present invention may continually move toward a higher concentration gradient to identify the mobile pollution source.
  • Pollution may be in the form of air pollution such as ozone or carbon monoxide which may spread according to wind or air currents. Pollution may also be in the form of noise pollution or water or soil pollution.
  • exemplary embodiments of the present invention are not limited to a particular type of pollution and the system and method according to exemplary embodiments of the present invention may identify and track any type of detectable pollution, as desired.
  • Unmanned or automated vehicles may reach substantially any geographic location in terms of latitude, longitude and altitude and pollution may be identified at substantially any geographic location using unmanned or automated vehicles, for example, by detecting and tracking the concentration gradient of the pollution. Geographic locations of pollution sources may be identified in terms of latitude, longitude and altitude. Thus, any desired form of pollution may be tracked, and the source of any desired form of pollution may be identified.
  • the pollution When pollution is noise pollution, the pollution may be in the form of relatively loud or high decibel sound emitted into the environment.
  • the concentration gradient may be a gradient of higher decibel or relatively louder sound to lower decibel or relatively lower sound.
  • the concentration gradient of sound may be used according to exemplary embodiments of the present invention to identify a source of emitted sound, and thus the sound emitter may be adjusted to reduce the volume of the sound emitted. For example, sound may be emitted at a level which violates a local ordinance or a state or federal law, either knowingly or unknowingly, and identification of the sound source may allow for reduction of the sound to reduce or eliminate noise pollution.
  • One form of pollution according to an exemplary embodiment of the present invention may be increased temperature pollution. That is, a pollution source may artificially heat a geographic region by emitting heat into the environment. The gradient at any location or geographic point may be combined to direct the automated vehicle in the direction of the higher temperature increase (e.g., the highest gradient of concentration). Thus, the gradient of concentration may be used to direct the automated vehicle toward the pollution source.
  • a pollution source may artificially heat a geographic region by emitting heat into the environment.
  • the gradient at any location or geographic point may be combined to direct the automated vehicle in the direction of the higher temperature increase (e.g., the highest gradient of concentration).
  • the gradient of concentration may be used to direct the automated vehicle toward the pollution source.
  • Unmanned or automated vehicles may include vehicles traveling on air, water or the ground.
  • vehicles traveling on air may include aerial vehicles such as drones, balloons, planes, helicopters or other aircraft.
  • Vehicles traveling on water may include boats and/or personal watercraft.
  • Vehicles traveling on the ground may include cars, truck or all terrain vehicles, for example.
  • exemplary embodiments of the present invention are not limited to a particular type of automated or unmanned vehicle and any desired automated or unmanned vehicle may be used.
  • Automated vehicles detecting or tracking water pollution may detect and track water or air pollution on a surface of a body of water or below a surface of the body of water. That is, unmanned or automated vehicles may travel above or below the surface of the body of water. Unmanned or automated vehicles traveling below the surface of water may include submersible vehicles such as submarines. Submersible vehicles according to exemplary embodiments of the present invention may travel to any desired depth and may track pollution at any desired depth.
  • the source of pollution may be modified in any desired way to reduce or eliminate the emission of pollution.
  • a damaged or broken gas or liquid pipe may have an unknown leak which emits pollution.
  • the broken pipe may be repaired or replaced to reduce or eliminate the emission of pollution.
  • FIG. 1 illustrates an example of a pollution source detection system according to an exemplary embodiment of the present invention.
  • a pollution source detection system 100 may include an automated vehicle 101 including a position sensor 102 that detects a geographic position of the automated vehicle 101 and at least one pollution detection sensor 103 that measures a concentration of pollution at the automated vehicle 101 .
  • the pollution source detection system 100 may include a back-end system 105 .
  • the back-end system 105 may include a network interface 106 that receives the geographic position and the concentration of the pollution from the automated vehicle 101 .
  • the back-end system 105 may include a database 107 that stores the geographic position and the concentration of the pollution received via the network interface 106 .
  • the back-end system 105 may include a processor 108 that measures a gradient of the concentration of the pollution and controls a movement of the automated vehicle 101 based on the gradient to guide the automated vehicle 101 toward a source of the pollution.
  • the automated vehicle 101 of the pollution source detection system 100 may include a GPS unit 104 (e.g., GPS sensor).
  • the position sensor 102 may include the GPS unit 104 . That is, the GPS unit (e.g., GPS sensor) may be connected to the position sensor 102 or the position sensor 102 may operate as the GPS unit.
  • the GPS unit 104 may detect a geographic location of the automated vehicle 101 .
  • the GPS unit 104 may detect a latitude, longitude, and/or altitude of the automated vehicle 101 .
  • the GPS unit 104 may communicate with one or more satellites to determine the latitude, longitude, and/or altitude of the automated vehicle 101 and the source of the pollution.
  • the pollution source detection system 100 may include one or more relay towers 109 .
  • the relay towers 109 may communicate with the automated vehicle 101 and may relay a signal from the automated vehicle 101 to the back-end system 105 .
  • the relay tower 109 may communicate with the back-end system 105 and may relay a signal from the back-end system 105 to the automated vehicle 101 .
  • the automated vehicle 101 may communicate with the back-end system 105 directly without relaying a signal through the relay tower 109 .
  • the relay tower 109 may be a cell phone tower.
  • the relay tower 109 according to exemplary embodiments of the present invention may increase the intensity of a signal transmitted by the automated vehicle 101 .
  • the relay tower 109 according to exemplary embodiments of the present invention may reduce the amount of power consumed by the automated vehicle 101 and may increase the range of the automated vehicle 101 .
  • the back-end system 105 may be disposed in the automated vehicle 101 .
  • back-end system 105 may be disposed in at least one of a plurality of automated vehicles 101 and may communicate with each of the plurality of automated vehicles 101 .
  • a plurality of automated vehicles 101 will be described in more detail below.
  • the processor 108 may measure the gradient using a numerical model.
  • the processor 108 may measure the gradient in real-time as the automated vehicle 101 moves.
  • the gradient may be reported to the back-end system 105 in real-time and the back-end system 105 may communicate with the automated vehicle 101 in real-time.
  • FIG. 2 illustrates an example of a pollution source detection system according to an exemplary embodiment of the present invention.
  • the pollution source detection system 100 may include a plurality of automated vehicles including the automated vehicle 101 .
  • Each of the plurality of automated vehicles 101 may include the position sensor 102 that detects a geographic position of the corresponding automated vehicle 101 and at least one pollution detection sensor 103 that measures a concentration of pollution at the corresponding automated vehicle 101 .
  • the processor 108 may aggregate the concentration of the pollution measured by the plurality of automated vehicles 101 , measure an aggregated gradient of the aggregated concentration of the pollution, and control a movement of the plurality of automated vehicles 101 based on the aggregated gradient to guide the plurality of automated vehicles 101 toward the source of the pollution.
  • At least one pollution detection sensor 103 may include a microphone.
  • the pollution may include noise pollution, and the microphone may detect the concentration of the noise pollution.
  • At least one of the pollution sensors 103 may include an air quality sensor.
  • the pollution may include air pollution.
  • the air quality sensor may detect a concentration of the air pollution by detecting a concentration of at least one of O 3 , NO 2 , CO, SO 2 , PM10, PM2.5 and C 6 H 6 .
  • the air quality sensor may detect a concentration of the air pollution by detecting a concentration of at least one of hydrocarbons (HC), nitrogen oxides (NO x ), particulate matter (PM), volatile organic compounds (VOCs), hydrogen sulfide (H 2 S) or other toxic air contaminants such as lead (Pb).
  • At least one of the pollution detection sensors 103 may include a camera, a hyperspectral sensor, an ultrasound sensor, a thermal sensor, a humidity sensor, a temperature sensor, a pressure sensor, or a corrosion sensor.
  • each of the automated vehicles 101 of the pollution source detection system 100 may include the GPS unit 104 (e.g., GPS sensor).
  • the position sensor may include the GPS unit 104 . That is, the GPS unit (e.g., GPS sensor) may be connected to the position sensor 102 or the position sensor 103 may operate as the GPS unit.
  • the position sensor 102 and/or the GPS unit 104 may detect the geographic position in three dimensions.
  • the GPS unit 104 may detect a geographic location of each of the automated vehicles 101 .
  • the GPS unit 104 may detect a latitude, longitude, and/or altitude of each of the automated vehicle 101 .
  • the GPS unit 104 may communicate with one or more satellites to determine the latitude, longitude, and/or altitude of each of the automated vehicles 101 .
  • the pollution source detection system 100 may include one or more relay towers 109 .
  • the relay towers 109 may communicate with the plurality of automated vehicles 101 and may relay a signal from the automated vehicles 101 to the back-end system 105 .
  • the relay tower 109 may communicate with the back-end system 105 and may relay a signal from the back-end system 105 to each of the plurality of automated vehicles 101 .
  • the plurality of automated vehicles 101 may communicate with the back-end system 105 directly without relaying a signal through the relay tower 109 .
  • the relay tower 109 may be a cell phone tower.
  • the relay tower 109 according to exemplary embodiments of the present invention may increase the intensity of a signal transmitted by each of the automated vehicles 101 .
  • the relay tower 109 according to exemplary embodiments of the present invention may reduce the amount of power consumed by the automated vehicles 101 and may increase the range of the automated vehicles 101 .
  • the automated vehicle 101 may be an automated air vehicle that moves through air without contacting ground, an automated ground vehicle that moves on the ground while contacting the ground, or an automated water vehicle that moves in water.
  • the network interface 106 may initially receive a general location at which the pollution is present from a source other than the automated vehicle 101 .
  • the processor 108 may subsequently guide the automated vehicle 101 to the general location and may control the movement of the automated vehicle 101 based on the gradient to guide the automated vehicle 101 toward the source of the pollution within the general location.
  • the processor 108 may perform an inverse geocoding query to detect a company or individual responsible for the source of the pollution. That is, the processor 108 may determine an owner of a parcel of land on which pollution is being emitted or an owner of a particular item of equipment emitting pollution.
  • FIG. 3 illustrates an example of a pollution concentration gradient of emitted pollution according to an exemplary embodiment of the present invention.
  • FIG. 4 illustrates an example of automated vehicles tracking a source of pollution by a pollution concentration gradient according to an exemplary embodiment of the present invention.
  • a pollution source 301 may emit pollution and the emitted pollution may have a pollution concentration gradient 302 .
  • the pollution concentration gradient 302 may increase across a geographic area when moving closer to the pollution source 301 .
  • the gradient of the concentration may be used by the processor 108 to direct the direction of movement of the automated vehicle 101 to continually and dynamically move toward a direction of higher gradient.
  • the concentration may refer to a concentration of air, noise, water or temperature pollution, for example. Moving toward the higher concentration gradient continually may move the automated vehicle 101 gradually closer to the pollution source 301 .
  • the following formula may be employed by the processor 108 to direct the direction of movement of the automated vehicle 101 to continually and dynamically move toward a direction of higher gradient:
  • the automated vehicle 101 may determine the pollution concentration gradient 302 and may determine a direction of increasing concentration gradient 401 .
  • the automated vehicle 101 may move along the direction of increasing concentration gradient 401 toward the pollution source 301 to detect the location of the pollution source 301 .
  • the automated vehicle 101 may determine the location of the pollution source 301 according to a grid pattern 402 .
  • the grid pattern 402 may be used to geo-locate data points for each detected pollution concentration. That is, the system according to exemplary embodiments of the present invention may plot the pollution concentration for a particular pollution source across a defined geographic area.
  • a global maximum concentration value and local maximum concentration values may be detected in each segment of the grid pattern 402 .
  • the global and local maximum pollution concentrations may be continually detected by predetermined algorithms.
  • the global and local maximum pollution concentrations may be detected by a black box search algorithm, a finite search difference method, a hill climbing method, optimization methods and Nurbs, Splines or surface estimation.
  • exemplary embodiments of the present invention are not limited to a particular algorithm, and any algorithm that searches for optimal, global maximum, local maximum, local minimum, and global minimum values can be used to search for the highest concentration of pollutants in the atmosphere.
  • the automated vehicle 101 may look for Maxima (pollutant concentration) or Minima (air density or O2 concentration).
  • FIG. 5 illustrates an example of a dynamic path of an automated vehicle moving toward a pollution source according to an exemplary embodiment of the present invention.
  • the automated vehicle 101 may continually adjust its path by detecting the gradient of concentration of the detected pollution.
  • the path of the automated vehicle 101 may be adjusted at a plurality of detection points 502 .
  • the automated vehicle 101 may detect a plurality of concentration gradients along a plurality of directions with respect to the automated vehicle 101 and the automated vehicle 101 may move toward the highest detected concentration gradient.
  • the gradient of the concentration may be used by the processor 108 to direct the direction of movement of the automated vehicle 101 to continually and dynamically move toward a direction of higher gradient.
  • the concentration may refer to a concentration of air, noise, water or temperature pollution, for example. Moving toward the higher concentration gradient continually may move the automated vehicle 101 gradually closer to the pollution source 301 .
  • the direction of movement of the automated vehicle 101 may be continually adjusted according to a detected concentration gradient in a plurality of directions. For example, the direction of movement may be adjusted at predetermined time points, such as every 30 or 60 seconds, for example. Thus, a number of concentration gradients in a number of potential directions of movement around the automated vehicle 101 may be detected and the direction of movement of the automated vehicle 101 may be adjusted to move toward the highest gradient of concentration and thus toward the pollution source 301 .
  • the dynamic and continual directional adjustment of the automated vehicle might not direct the automated vehicle in a straight line toward the pollution source 301 because the direction of movement of the automated vehicle 101 may be adjusted at a series of detection points 502 .
  • the path of the automated vehicle 101 may follow an approximately zig zag pattern, as illustrated, for example, in FIG. 5 .
  • FIG. 6 illustrates a flow chart of a method of detecting a source of pollution according to an exemplary embodiment of the present invention.
  • a method of detecting a source of pollution may include detecting a geographic position of the automated vehicle by the position sensor disposed on the automated vehicle 601 .
  • a concentration of the pollution may be measured by at least one pollution detection sensor disposed on the automated vehicle 602 .
  • the geographic position and the concentration of the pollution may be received via the network interface disposed at a back-end system from the automated vehicle 603 .
  • the geographic position and the concentration of the pollution received via the network interface may be stored in the database disposed at the back-end system 604 .
  • the method of detection of a source of pollution may include measuring, by a processor disposed at the back-end system, a gradient of the concentration of the pollution 605 .
  • the method of detection of a source of pollution may include controlling, by the processor, a movement of the automated vehicle based on the gradient to guide the automated vehicle toward the source of the pollution 606 .
  • the processor 108 may measure the gradient using a numerical model.
  • the processor 108 may measure the gradient in real-time as the automated vehicle 101 moves.
  • the method of detection of a source of pollution may include detecting a geographic position of each of a plurality of automated vehicles 101 by a position sensor disposed on each of the plurality of automated vehicles 101 .
  • a concentration of the pollution may be measured by at least one pollution detection sensor 103 disposed on each of the plurality of automated vehicles 101 .
  • the concentration of the pollution measured by the plurality of automated vehicles 101 may be aggregated.
  • An aggregated gradient of the aggregated concentration of the pollution may be measured.
  • a movement of the plurality of automated vehicles 101 may be controlled based on the aggregated gradient to guide the plurality of automated vehicles 101 toward the source of the pollution.
  • the method of detection of a source of pollution may include initially receiving a general location at which the pollution is present from a source other than the automated vehicle 101 and subsequently guiding the automated vehicle 101 to the general location.
  • the movement of the automated vehicle 101 may be controlled based on the gradient to guide the automated vehicle 101 toward the source of the pollution within the general location.
  • the general location of the pollution may be initially received by reports identifying pollution in a particular area, such as complaints by citizens or visitors to a particular location.
  • the general location of the pollution may be initially received from fixed location detectors that are present in a particular area having detectable pollution.
  • the method of detection of a source of pollution may include performing, by the processor 108 , an inverse geocoding query to detect a company or individual responsible for the source of the pollution. That is, the processor 108 may determine an owner of a parcel of land on which pollution is being emitted or an owner of a particular item of equipment emitting pollution.
  • Exemplary embodiments of the present invention provide a computer program product for detecting a source of pollution.
  • the computer program product may include a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to detect a geographic position of the automated vehicle 101 by the position sensor 102 disposed on the automated vehicle 101 .
  • the program instructions executable by a processor cause the processor to measure a concentration of the pollution by at least one pollution detection sensor disposed on the automated vehicle 101 .
  • the program instructions executable by a processor cause the processor to receive the geographic position and the concentration of the pollution via a network interface disposed at a back-end system from the automated vehicle.
  • the program instructions executable by a processor may cause the processor to store the geographic position and the concentration of the pollution received via the network interface in a database disposed at the back-end system 105 .
  • the program instructions executable by a processor cause the processor to measure a gradient of the concentration of the pollution and control a movement of the automated vehicle 101 based on the gradient to guide the automated vehicle 101 toward the source of the pollution.
  • FIG. 7 illustrates an example of a computer system capable of implementing the methods according to exemplary embodiments of the present invention.
  • the system and method of the present disclosure may be implemented in the form of a software application running on a computer system, for example, a mainframe, personal computer (PC), handheld computer, server, etc.
  • the software application may be stored on a recording media locally accessible by the computer system and accessible via a hard wired or wireless connection to a network, for example, a local area network, or the Internet.
  • the computer system referred to generally as system 700 may include, for example, a central processing unit (CPU) 701 , random access memory (RAM) 704 , a printer interface 710 , a display unit 711 , a local area network (LAN) data transmission controller 705 , a LAN interface 706 , a network controller 703 , an internal bus 702 , and one or more input devices 709 , for example, a keyboard, mouse etc.
  • the system 700 may be connected to a data storage device, for example, a hard disk, 708 via a link 707 .
  • each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s).
  • the functions noted in the block may occur out of the order noted in the figures.
  • two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved.
  • Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service.
  • This cloud model may include at least five characteristics, at least three service models, and at least four deployment models.
  • On-demand self-service a cloud consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with the service's provider.
  • Resource pooling the provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of location independence in that the consumer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (e.g., country, state, or datacenter).
  • Rapid elasticity capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time.

Landscapes

  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Pathology (AREA)
  • Immunology (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Remote Sensing (AREA)
  • Automation & Control Theory (AREA)
  • Medicinal Chemistry (AREA)
  • Food Science & Technology (AREA)
  • Combustion & Propulsion (AREA)
  • Acoustics & Sound (AREA)
  • Signal Processing (AREA)
  • Traffic Control Systems (AREA)

Abstract

A pollution source detection system includes an automated vehicle including a position sensor that detects a geographic position of the automated vehicle and at least one pollution detection sensor that measures a concentration of pollution at the automated vehicle. The pollution source detection system includes a back-end system. The back-end system includes a network interface that receives the geographic position and the concentration of the pollution from the automated vehicle. The back-end system includes a database that stores the geographic position and the concentration of the pollution received via the network interface. The back-end system includes a processor that measures a gradient of the concentration of the pollution and controls a movement of the automated vehicle based on the gradient to guide the automated vehicle toward a source of the pollution.

Description

    BACKGROUND
  • Exemplary embodiments of the present invention relate to tracking pollution. More particularly, exemplary embodiments of the present invention relate to a system and method for tracking pollution by determining pollution concentration gradients with unmanned vehicles.
  • Generally, pollution, such as air, water, soil or noise pollution, may be detected using manual instrumentation that is operated by individual human operators in an area expected to have pollution. Pollution detection equipment may also be mounted at fixed positions in different locations or geographic areas. Pollution may be emitted from a wide array of locations and the pollution may spread over a large geographic area. Spreading pollution may be present at a large range of concentrations in different areas. Pollution may also spread according to patterns that are not readily predicted, such as according to shifting wind patterns or shifting water currents. Thus, pollution detection equipment may be disposed in fixed positions over a wide geographic area to detect pollution emitted from a single source. For example, emissions from industrial equipment or a power plant may travel relatively large distances according to wind patterns and pollution emitted from such a source may be present at varying concentrations at varying distances from the emission source.
  • Pollution may be detected at relatively low concentrations in a particular geographic area and the source of the detected solution may be unknown. Thus, it may be desirable to have pollution detection equipment present over a large geographic area to determine pollution concentrations in different areas to determine an origin or source of a particular form of pollution.
  • SUMMARY
  • Exemplary embodiments of the present invention provide a pollution source detection system including an automated vehicle including a position sensor that detects a geographic position of the automated vehicle and at least one pollution detection sensor that measures a concentration of pollution at the automated vehicle. The pollution source detection system includes a back-end system. The back-end system includes a network interface that receives the geographic position and the concentration of the pollution from the automated vehicle. The back-end system includes a database that stores the geographic position and the concentration of the pollution received via the network interface. The back-end system includes a processor that measures a gradient of the concentration of the pollution and controls a movement of the automated vehicle based on the gradient to guide the automated vehicle toward a source of the pollution.
  • According to an exemplary embodiment of the present invention the processor may measure the gradient using a numerical model.
  • According to an exemplary embodiment of the present invention the processor may measure the gradient in real-time as the automated vehicle moves.
  • According to an exemplary embodiment of the present invention the pollution source detection system may include a plurality of automated vehicles including the automated vehicle. Each of the plurality of automated vehicles may include a position sensor that detects a geographic position of the corresponding automated vehicle and at least one pollution detection sensor that measures a concentration of pollution at the corresponding automated vehicle. The processor may aggregate the concentration of the pollution measured by the plurality of automated vehicles, measure an aggregated gradient of the aggregated concentration of the pollution, and control a movement of the plurality of automated vehicles based on the aggregated gradient to guide the plurality of automated vehicles toward the source of the pollution.
  • According to an exemplary embodiment of the present invention at least one pollution detection sensor may include a microphone. The pollution may include noise pollution, and the microphone may detect the concentration of the noise pollution.
  • According to an exemplary embodiment of the present invention at least one of the pollution sensors may include an air quality sensor. The pollution may include air pollution. The air quality sensor may detect a concentration of the air pollution by detecting a concentration of at least one of O3, NO2, CO, SO2, PM10, PM2.5 and C6H6.
  • According to an exemplary embodiment of the present invention at least one of the pollution detection sensors may include a camera, a hyperspectral sensor, an ultrasound sensor, a thermal sensor, a humidity sensor, a temperature sensor, a pressure sensor, or a corrosion sensor.
  • According to an exemplary embodiment of the present invention the position sensor may include a GPS sensor.
  • According to an exemplary embodiment of the present invention the position sensor may detect the geographic position in three dimensions.
  • According to an exemplary embodiment of the present invention the automated vehicle may be an automated air vehicle that moves through air without contacting ground, an automated ground vehicle that moves on the ground while contacting the ground, or an automated water vehicle that moves in water.
  • According to an exemplary embodiment of the present invention the network interface may initially receive a general location at which the pollution is present from a source other than the automated vehicle. The processor may subsequently guide the automated vehicle to the general location and may control the movement of the automated vehicle based on the gradient to guide the automated vehicle toward the source of the pollution within the general location.
  • According to an exemplary embodiment of the present invention the processor may perform an inverse geocoding query to detect a company or individual responsible for the source of the pollution.
  • Exemplary embodiments of the present invention provide a method of detecting a source of pollution including detecting a geographic position of an automated vehicle by a position sensor disposed on the automated vehicle. A concentration of the pollution is measured by at least one pollution detection sensor disposed on the automated vehicle. The geographic position and the concentration of the pollution are received via a network interface disposed at a back-end system from the automated vehicle. The geographic position and the concentration of the pollution received via the network interface are stored in a database disposed at the back-end system. The method of detection of a source of pollution includes measuring, by a processor disposed at the back-end system, a gradient of the concentration of the pollution. The method of detection of a source of pollution includes controlling, by the processor, a movement of the automated vehicle based on the gradient to guide the automated vehicle toward the source of the pollution.
  • According to an exemplary embodiment of the present invention the processor may measure the gradient using a numerical model.
  • According to an exemplary embodiment of the present invention the processor may measure the gradient in real-time as the automated vehicle moves.
  • According to an exemplary embodiment of the present invention the method of detection of a source of pollution may include detecting a geographic position of each of a plurality of automated vehicles, including the automated vehicle, by a position sensor disposed on each of the plurality of automated vehicles. A concentration of the pollution may be measured by at least one pollution detection sensor disposed on each of the plurality of automated vehicles. The concentration of the pollution measured by the plurality of automated vehicles may be aggregated. An aggregated gradient of the aggregated concentration of the pollution may be measured. A movement of the plurality of automated vehicles may be controlled based on the aggregated gradient to guide the plurality of automated vehicles toward the source of the pollution.
  • According to an exemplary embodiment of the present invention the method of detection of a source of pollution may include initially receiving a general location at which the pollution is present from a source other than the automated vehicle and subsequently guiding the automated vehicle to the general location. The movement of the automated vehicle may be controlled based on the gradient to guide the automated vehicle toward the source of the pollution within the general location.
  • According to an exemplary embodiment of the present invention the method of detection of a source of pollution may include performing, by the processor, an inverse geocoding query to detect a company or individual responsible for the source of the pollution.
  • Exemplary embodiments of the present invention provide a computer program product for detecting a source of pollution. The computer program product may include a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to detect a geographic position of an automated vehicle by a position sensor disposed on the automated vehicle. The program instructions executable by the processor cause the processor to measure a concentration of the pollution by at least one pollution detection sensor disposed on the automated vehicle. The program instructions executable by the processor cause the processor to receive the geographic position and the concentration of the pollution via a network interface disposed at a back-end system from the automated vehicle. The program instructions executable by the processor cause the processor to store the geographic position and the concentration of the pollution received via the network interface in a database disposed at the back-end system. The program instructions executable by the processor cause the processor to measure a gradient of the concentration of the pollution and control a movement of the automated vehicle based on the gradient to guide the automated vehicle toward the source of the pollution.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • The above and other features of the present invention will become more apparent by describing in detail exemplary embodiments thereof, with reference to the accompanying drawings, in which:
  • FIG. 1 illustrates an example of a pollution source detection system according to an exemplary embodiment of the present invention.
  • FIG. 2 illustrates an example of a pollution source detection system according to an exemplary embodiment of the present invention.
  • FIG. 3 illustrates an example of a pollution concentration gradient of emitted pollution according to an exemplary embodiment of the present invention.
  • FIG. 4 illustrates an example of automated vehicles tracking a source of pollution by a pollution concentration gradient according to an exemplary embodiment of the present invention.
  • FIG. 5 illustrates an example of a dynamic path of an automated vehicle moving toward a pollution source according to an exemplary embodiment of the present invention.
  • FIG. 6 illustrates a flow chart of a method of detecting a source of pollution according to an exemplary embodiment of the present invention.
  • FIG. 7 illustrates an example of a computer system capable of implementing the method according to exemplary embodiments of the present invention.
  • DETAILED DESCRIPTION
  • Exemplary embodiments of the present invention will be described more fully hereinafter with reference to the accompanying drawings. Like reference numerals may refer to like elements throughout the specification and drawings.
  • Exemplary embodiments of the present invention relate to tracking pollution. Exemplary embodiments of the present invention may provide a system and method for automatically tracking pollution using automated vehicles. More particularly, exemplary embodiments of the present invention relate to a system and method for tracking pollution by tracking gradient concentration with unmanned vehicles.
  • Pollution may be emitted from a variety of sources and the emitted pollution may spread over a large geographic area. The source of pollution may be a known source, such as a power plant, or an industrial area, or a source of a particular type of solution may be unknown. The emitted pollution may be present at a relatively large range of concentrations. For example, pollution emitted from a particular source may dissipate as distance increases from the emission source. Additionally, concentrations of pollution may vary unevenly with distance from a particular emission source. For example, strong winds in a particular direction may spread air pollution unevenly over a particular geographic area. Thus, concentrations of pollution spreading over a particular geographic area may be difficult to predict and installing or placing emission detection equipment in appropriate locations may be difficult. When the source of pollution is unknown the concentration of the pollution may be useful for detecting the source of the pollution. For example, pollution may be tracked and/or the source of pollution may be determined by tracking the concentration of pollution using automated or unmanned vehicles according to exemplary embodiments of the present invention.
  • A source of pollution may be a moving source, such as a motorized vehicle. For example, cars, trucks, boats or plains may emit pollution such as air or water pollution and thus the source of this pollution might not be fixed in a specific geographic location. Automated or unmanned vehicles according to exemplary embodiments of the present invention may determine a source of pollution when the source of pollution is such a moving source. The automated or unmanned vehicles according to exemplary embodiments of the present invention may detect the concentration gradient of the pollution emitted from the moving source and may track the emitted pollution by following the concentration gradient toward the mobile pollution source. That is, the automated or unmanned vehicles according to exemplary embodiments of the present invention may continually move toward a higher concentration gradient to identify the mobile pollution source.
  • Pollution may be in the form of air pollution such as ozone or carbon monoxide which may spread according to wind or air currents. Pollution may also be in the form of noise pollution or water or soil pollution. However, exemplary embodiments of the present invention are not limited to a particular type of pollution and the system and method according to exemplary embodiments of the present invention may identify and track any type of detectable pollution, as desired. Unmanned or automated vehicles may reach substantially any geographic location in terms of latitude, longitude and altitude and pollution may be identified at substantially any geographic location using unmanned or automated vehicles, for example, by detecting and tracking the concentration gradient of the pollution. Geographic locations of pollution sources may be identified in terms of latitude, longitude and altitude. Thus, any desired form of pollution may be tracked, and the source of any desired form of pollution may be identified.
  • When pollution is noise pollution, the pollution may be in the form of relatively loud or high decibel sound emitted into the environment. In the case of noise, the concentration gradient may be a gradient of higher decibel or relatively louder sound to lower decibel or relatively lower sound. The concentration gradient of sound may be used according to exemplary embodiments of the present invention to identify a source of emitted sound, and thus the sound emitter may be adjusted to reduce the volume of the sound emitted. For example, sound may be emitted at a level which violates a local ordinance or a state or federal law, either knowingly or unknowingly, and identification of the sound source may allow for reduction of the sound to reduce or eliminate noise pollution.
  • One form of pollution according to an exemplary embodiment of the present invention may be increased temperature pollution. That is, a pollution source may artificially heat a geographic region by emitting heat into the environment. The gradient at any location or geographic point may be combined to direct the automated vehicle in the direction of the higher temperature increase (e.g., the highest gradient of concentration). Thus, the gradient of concentration may be used to direct the automated vehicle toward the pollution source.
  • Unmanned or automated vehicles according to exemplary embodiments of the present invention may include vehicles traveling on air, water or the ground. For example, vehicles traveling on air may include aerial vehicles such as drones, balloons, planes, helicopters or other aircraft. Vehicles traveling on water may include boats and/or personal watercraft. Vehicles traveling on the ground may include cars, truck or all terrain vehicles, for example. However, exemplary embodiments of the present invention are not limited to a particular type of automated or unmanned vehicle and any desired automated or unmanned vehicle may be used.
  • Automated vehicles detecting or tracking water pollution according to an exemplary embodiment of the present invention may detect and track water or air pollution on a surface of a body of water or below a surface of the body of water. That is, unmanned or automated vehicles may travel above or below the surface of the body of water. Unmanned or automated vehicles traveling below the surface of water may include submersible vehicles such as submarines. Submersible vehicles according to exemplary embodiments of the present invention may travel to any desired depth and may track pollution at any desired depth.
  • By identifying a source of pollution according to exemplary embodiments of the present invention, the source of pollution may be modified in any desired way to reduce or eliminate the emission of pollution. For example, a damaged or broken gas or liquid pipe may have an unknown leak which emits pollution. When the source of such pollution is identified the broken pipe may be repaired or replaced to reduce or eliminate the emission of pollution.
  • FIG. 1 illustrates an example of a pollution source detection system according to an exemplary embodiment of the present invention.
  • Referring to FIG. 1, a pollution source detection system 100 according to an exemplary embodiment of the present invention may include an automated vehicle 101 including a position sensor 102 that detects a geographic position of the automated vehicle 101 and at least one pollution detection sensor 103 that measures a concentration of pollution at the automated vehicle 101. The pollution source detection system 100 may include a back-end system 105. The back-end system 105 may include a network interface 106 that receives the geographic position and the concentration of the pollution from the automated vehicle 101. The back-end system 105 may include a database 107 that stores the geographic position and the concentration of the pollution received via the network interface 106. The back-end system 105 may include a processor 108 that measures a gradient of the concentration of the pollution and controls a movement of the automated vehicle 101 based on the gradient to guide the automated vehicle 101 toward a source of the pollution.
  • According to an exemplary embodiment of the present invention, the automated vehicle 101 of the pollution source detection system 100 may include a GPS unit 104 (e.g., GPS sensor). According to an exemplary embodiment of the present invention the position sensor 102 may include the GPS unit 104. That is, the GPS unit (e.g., GPS sensor) may be connected to the position sensor 102 or the position sensor 102 may operate as the GPS unit.
  • The GPS unit 104 may detect a geographic location of the automated vehicle 101. The GPS unit 104 may detect a latitude, longitude, and/or altitude of the automated vehicle 101. The GPS unit 104 may communicate with one or more satellites to determine the latitude, longitude, and/or altitude of the automated vehicle 101 and the source of the pollution.
  • The pollution source detection system 100 according to an exemplary embodiment of the present invention may include one or more relay towers 109. The relay towers 109 may communicate with the automated vehicle 101 and may relay a signal from the automated vehicle 101 to the back-end system 105. The relay tower 109 may communicate with the back-end system 105 and may relay a signal from the back-end system 105 to the automated vehicle 101. The automated vehicle 101 may communicate with the back-end system 105 directly without relaying a signal through the relay tower 109.
  • The relay tower 109 according to exemplary embodiments of the present invention may be a cell phone tower. The relay tower 109 according to exemplary embodiments of the present invention may increase the intensity of a signal transmitted by the automated vehicle 101. Thus, the relay tower 109 according to exemplary embodiments of the present invention may reduce the amount of power consumed by the automated vehicle 101 and may increase the range of the automated vehicle 101.
  • The back-end system 105 according to an exemplary embodiment of the present invention may be disposed in the automated vehicle 101. For example, back-end system 105 may be disposed in at least one of a plurality of automated vehicles 101 and may communicate with each of the plurality of automated vehicles 101. A plurality of automated vehicles 101 will be described in more detail below.
  • According to an exemplary embodiment of the present invention the processor 108 may measure the gradient using a numerical model.
  • According to an exemplary embodiment of the present invention the processor 108 may measure the gradient in real-time as the automated vehicle 101 moves. The gradient may be reported to the back-end system 105 in real-time and the back-end system 105 may communicate with the automated vehicle 101 in real-time.
  • FIG. 2 illustrates an example of a pollution source detection system according to an exemplary embodiment of the present invention.
  • Referring to FIG. 2, the pollution source detection system 100 may include a plurality of automated vehicles including the automated vehicle 101. Each of the plurality of automated vehicles 101 may include the position sensor 102 that detects a geographic position of the corresponding automated vehicle 101 and at least one pollution detection sensor 103 that measures a concentration of pollution at the corresponding automated vehicle 101. The processor 108 may aggregate the concentration of the pollution measured by the plurality of automated vehicles 101, measure an aggregated gradient of the aggregated concentration of the pollution, and control a movement of the plurality of automated vehicles 101 based on the aggregated gradient to guide the plurality of automated vehicles 101 toward the source of the pollution.
  • According to an exemplary embodiment of the present invention at least one pollution detection sensor 103 may include a microphone. The pollution may include noise pollution, and the microphone may detect the concentration of the noise pollution.
  • According to an exemplary embodiment of the present invention at least one of the pollution sensors 103 may include an air quality sensor. The pollution may include air pollution. The air quality sensor may detect a concentration of the air pollution by detecting a concentration of at least one of O3, NO2, CO, SO2, PM10, PM2.5 and C6H6. The air quality sensor may detect a concentration of the air pollution by detecting a concentration of at least one of hydrocarbons (HC), nitrogen oxides (NOx), particulate matter (PM), volatile organic compounds (VOCs), hydrogen sulfide (H2S) or other toxic air contaminants such as lead (Pb).
  • According to an exemplary embodiment of the present invention at least one of the pollution detection sensors 103 may include a camera, a hyperspectral sensor, an ultrasound sensor, a thermal sensor, a humidity sensor, a temperature sensor, a pressure sensor, or a corrosion sensor.
  • According to an exemplary embodiment of the present invention, each of the automated vehicles 101 of the pollution source detection system 100 may include the GPS unit 104 (e.g., GPS sensor). According to an exemplary embodiment of the present invention the position sensor may include the GPS unit 104. That is, the GPS unit (e.g., GPS sensor) may be connected to the position sensor 102 or the position sensor 103 may operate as the GPS unit.
  • According to an exemplary embodiment of the present invention the position sensor 102 and/or the GPS unit 104 may detect the geographic position in three dimensions.
  • The GPS unit 104 may detect a geographic location of each of the automated vehicles 101. The GPS unit 104 may detect a latitude, longitude, and/or altitude of each of the automated vehicle 101. The GPS unit 104 may communicate with one or more satellites to determine the latitude, longitude, and/or altitude of each of the automated vehicles 101.
  • The pollution source detection system 100 according to an exemplary embodiment of the present invention may include one or more relay towers 109. The relay towers 109 may communicate with the plurality of automated vehicles 101 and may relay a signal from the automated vehicles 101 to the back-end system 105. The relay tower 109 may communicate with the back-end system 105 and may relay a signal from the back-end system 105 to each of the plurality of automated vehicles 101. The plurality of automated vehicles 101 may communicate with the back-end system 105 directly without relaying a signal through the relay tower 109.
  • The relay tower 109 according to exemplary embodiments of the present invention may be a cell phone tower. The relay tower 109 according to exemplary embodiments of the present invention may increase the intensity of a signal transmitted by each of the automated vehicles 101. Thus, the relay tower 109 according to exemplary embodiments of the present invention may reduce the amount of power consumed by the automated vehicles 101 and may increase the range of the automated vehicles 101.
  • According to an exemplary embodiment of the present invention the automated vehicle 101 may be an automated air vehicle that moves through air without contacting ground, an automated ground vehicle that moves on the ground while contacting the ground, or an automated water vehicle that moves in water.
  • According to an exemplary embodiment of the present invention the network interface 106 may initially receive a general location at which the pollution is present from a source other than the automated vehicle 101. The processor 108 may subsequently guide the automated vehicle 101 to the general location and may control the movement of the automated vehicle 101 based on the gradient to guide the automated vehicle 101 toward the source of the pollution within the general location.
  • According to an exemplary embodiment of the present invention the processor 108 may perform an inverse geocoding query to detect a company or individual responsible for the source of the pollution. That is, the processor 108 may determine an owner of a parcel of land on which pollution is being emitted or an owner of a particular item of equipment emitting pollution.
  • FIG. 3 illustrates an example of a pollution concentration gradient of emitted pollution according to an exemplary embodiment of the present invention. FIG. 4 illustrates an example of automated vehicles tracking a source of pollution by a pollution concentration gradient according to an exemplary embodiment of the present invention.
  • Referring to FIGS. 3 and 4, a pollution source 301 may emit pollution and the emitted pollution may have a pollution concentration gradient 302. The pollution concentration gradient 302 may increase across a geographic area when moving closer to the pollution source 301.
  • The gradient of the concentration according to exemplary embodiments of the present invention may be used by the processor 108 to direct the direction of movement of the automated vehicle 101 to continually and dynamically move toward a direction of higher gradient. The concentration may refer to a concentration of air, noise, water or temperature pollution, for example. Moving toward the higher concentration gradient continually may move the automated vehicle 101 gradually closer to the pollution source 301. The following formula may be employed by the processor 108 to direct the direction of movement of the automated vehicle 101 to continually and dynamically move toward a direction of higher gradient:
  • J = - D [ φ X + φ Y + φ Z ]
  • Referring to FIG. 4, the automated vehicle 101 may determine the pollution concentration gradient 302 and may determine a direction of increasing concentration gradient 401. The automated vehicle 101 may move along the direction of increasing concentration gradient 401 toward the pollution source 301 to detect the location of the pollution source 301. The automated vehicle 101 may determine the location of the pollution source 301 according to a grid pattern 402. The grid pattern 402 may be used to geo-locate data points for each detected pollution concentration. That is, the system according to exemplary embodiments of the present invention may plot the pollution concentration for a particular pollution source across a defined geographic area.
  • A global maximum concentration value and local maximum concentration values may be detected in each segment of the grid pattern 402. The global and local maximum pollution concentrations may be continually detected by predetermined algorithms. For example, the global and local maximum pollution concentrations may be detected by a black box search algorithm, a finite search difference method, a hill climbing method, optimization methods and Nurbs, Splines or surface estimation. However, exemplary embodiments of the present invention are not limited to a particular algorithm, and any algorithm that searches for optimal, global maximum, local maximum, local minimum, and global minimum values can be used to search for the highest concentration of pollutants in the atmosphere. For example, the automated vehicle 101 according to exemplary embodiments of the present invention may look for Maxima (pollutant concentration) or Minima (air density or O2 concentration).
  • FIG. 5 illustrates an example of a dynamic path of an automated vehicle moving toward a pollution source according to an exemplary embodiment of the present invention.
  • Referring to FIG. 5, the automated vehicle 101 may continually adjust its path by detecting the gradient of concentration of the detected pollution. The path of the automated vehicle 101 may be adjusted at a plurality of detection points 502. At each of the plurality of detection points 502 the automated vehicle 101 may detect a plurality of concentration gradients along a plurality of directions with respect to the automated vehicle 101 and the automated vehicle 101 may move toward the highest detected concentration gradient.
  • The gradient of the concentration according to exemplary embodiments of the present invention may be used by the processor 108 to direct the direction of movement of the automated vehicle 101 to continually and dynamically move toward a direction of higher gradient. The concentration may refer to a concentration of air, noise, water or temperature pollution, for example. Moving toward the higher concentration gradient continually may move the automated vehicle 101 gradually closer to the pollution source 301. The direction of movement of the automated vehicle 101 may be continually adjusted according to a detected concentration gradient in a plurality of directions. For example, the direction of movement may be adjusted at predetermined time points, such as every 30 or 60 seconds, for example. Thus, a number of concentration gradients in a number of potential directions of movement around the automated vehicle 101 may be detected and the direction of movement of the automated vehicle 101 may be adjusted to move toward the highest gradient of concentration and thus toward the pollution source 301.
  • According to an exemplary embodiment of the present invention, the dynamic and continual directional adjustment of the automated vehicle might not direct the automated vehicle in a straight line toward the pollution source 301 because the direction of movement of the automated vehicle 101 may be adjusted at a series of detection points 502. Thus, while the automated vehicle 101 may make continual progress toward the pollution source 301, the path of the automated vehicle 101 may follow an approximately zig zag pattern, as illustrated, for example, in FIG. 5.
  • FIG. 6 illustrates a flow chart of a method of detecting a source of pollution according to an exemplary embodiment of the present invention.
  • Referring to FIG. 6, a method of detecting a source of pollution may include detecting a geographic position of the automated vehicle by the position sensor disposed on the automated vehicle 601. A concentration of the pollution may be measured by at least one pollution detection sensor disposed on the automated vehicle 602. The geographic position and the concentration of the pollution may be received via the network interface disposed at a back-end system from the automated vehicle 603. The geographic position and the concentration of the pollution received via the network interface may be stored in the database disposed at the back-end system 604. The method of detection of a source of pollution may include measuring, by a processor disposed at the back-end system, a gradient of the concentration of the pollution 605. The method of detection of a source of pollution may include controlling, by the processor, a movement of the automated vehicle based on the gradient to guide the automated vehicle toward the source of the pollution 606.
  • According to an exemplary embodiment of the present invention the processor 108 may measure the gradient using a numerical model.
  • According to an exemplary embodiment of the present invention the processor 108 may measure the gradient in real-time as the automated vehicle 101 moves.
  • According to an exemplary embodiment of the present invention the method of detection of a source of pollution may include detecting a geographic position of each of a plurality of automated vehicles 101 by a position sensor disposed on each of the plurality of automated vehicles 101. A concentration of the pollution may be measured by at least one pollution detection sensor 103 disposed on each of the plurality of automated vehicles 101. The concentration of the pollution measured by the plurality of automated vehicles 101 may be aggregated. An aggregated gradient of the aggregated concentration of the pollution may be measured. A movement of the plurality of automated vehicles 101 may be controlled based on the aggregated gradient to guide the plurality of automated vehicles 101 toward the source of the pollution.
  • According to an exemplary embodiment of the present invention the method of detection of a source of pollution may include initially receiving a general location at which the pollution is present from a source other than the automated vehicle 101 and subsequently guiding the automated vehicle 101 to the general location. The movement of the automated vehicle 101 may be controlled based on the gradient to guide the automated vehicle 101 toward the source of the pollution within the general location. For example, the general location of the pollution may be initially received by reports identifying pollution in a particular area, such as complaints by citizens or visitors to a particular location. The general location of the pollution may be initially received from fixed location detectors that are present in a particular area having detectable pollution.
  • According to an exemplary embodiment of the present invention the method of detection of a source of pollution may include performing, by the processor 108, an inverse geocoding query to detect a company or individual responsible for the source of the pollution. That is, the processor 108 may determine an owner of a parcel of land on which pollution is being emitted or an owner of a particular item of equipment emitting pollution.
  • Exemplary embodiments of the present invention provide a computer program product for detecting a source of pollution. The computer program product may include a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to detect a geographic position of the automated vehicle 101 by the position sensor 102 disposed on the automated vehicle 101. The program instructions executable by a processor cause the processor to measure a concentration of the pollution by at least one pollution detection sensor disposed on the automated vehicle 101. The program instructions executable by a processor cause the processor to receive the geographic position and the concentration of the pollution via a network interface disposed at a back-end system from the automated vehicle. The program instructions executable by a processor may cause the processor to store the geographic position and the concentration of the pollution received via the network interface in a database disposed at the back-end system 105. The program instructions executable by a processor cause the processor to measure a gradient of the concentration of the pollution and control a movement of the automated vehicle 101 based on the gradient to guide the automated vehicle 101 toward the source of the pollution.
  • FIG. 7 illustrates an example of a computer system capable of implementing the methods according to exemplary embodiments of the present invention. The system and method of the present disclosure may be implemented in the form of a software application running on a computer system, for example, a mainframe, personal computer (PC), handheld computer, server, etc. The software application may be stored on a recording media locally accessible by the computer system and accessible via a hard wired or wireless connection to a network, for example, a local area network, or the Internet.
  • The computer system referred to generally as system 700 may include, for example, a central processing unit (CPU) 701, random access memory (RAM) 704, a printer interface 710, a display unit 711, a local area network (LAN) data transmission controller 705, a LAN interface 706, a network controller 703, an internal bus 702, and one or more input devices 709, for example, a keyboard, mouse etc. As shown, the system 700 may be connected to a data storage device, for example, a hard disk, 708 via a link 707.
  • The descriptions of the various exemplary embodiments of the present invention have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the exemplary embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described exemplary embodiments. The terminology used herein was chosen to best explain the principles of the exemplary embodiments, or to enable others of ordinary skill in the art to understand exemplary embodiments described herein.
  • The flowcharts and/or block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various exemplary embodiments of the inventive concept. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.
  • It is understood that although exemplary embodiments of this invention may relate to cloud computing, implementation of the teachings recited herein are not limited to a cloud computing environment. Rather, embodiments of the present invention are capable of being implemented in conjunction with any other type of computing environment now known or later developed.
  • Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. This cloud model may include at least five characteristics, at least three service models, and at least four deployment models.
  • Characteristics are as follows:
  • On-demand self-service: a cloud consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with the service's provider.
  • Broad network access: capabilities are available over a network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops, and PDAs).
  • Resource pooling: the provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of location independence in that the consumer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (e.g., country, state, or datacenter).
  • Rapid elasticity: capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time.
  • While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it will be understood by those of ordinary skill in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the present invention as defined by the following claims.

Claims (20)

1. A pollution source detection system, comprising:
an automated vehicle comprising a position sensor that detects a geographic position of the automated vehicle and at least one pollution detection sensor that measures a concentration of pollution at the automated vehicle; and
a back-end system, comprising:
a network interface that receives the geographic position and the concentration of the pollution from the automated vehicle;
a database that stores the geographic position and the concentration of the pollution received via the network interface; and
a processor that measures a gradient of the concentration of the pollution and controls a movement of the automated vehicle based on the gradient to guide the automated vehicle toward a source of the pollution.
2. The pollution source detection system of claim 1, wherein the processor measures the gradient using a numerical model.
3. The pollution source detection system of claim 1, wherein the processor measures the gradient in real-time as the automated vehicle moves.
4. The pollution source detection system of claim 1, further comprising:
a plurality of automated vehicles including the automated vehicle,
wherein each of the plurality of automated vehicles comprises a position sensor that detects a geographic position of the corresponding automated vehicle and at least one pollution detection sensor that measures a concentration of pollution at the corresponding automated vehicle,
wherein the processor aggregates the concentration of the pollution measured by the plurality of automated vehicles, measures an aggregated gradient of the aggregated concentration of the pollution, and controls a movement of the plurality of automated vehicles based on the aggregated gradient to guide the plurality of automated vehicles toward the source of the pollution.
5. The pollution source detection system of claim 1, wherein the at least one pollution detection sensor comprises a microphone, the pollution comprises noise pollution, and the microphone detects the concentration of the noise pollution.
6. The pollution detection system of claim 1, wherein the at least one pollution sensor comprises an air quality sensor, the pollution comprises air pollution, and the air quality sensor detects a concentration of the air pollution by detecting a concentration of at least one of O3, NO2, CO, SO2, PM10, PM2.5 and C6H6.
7. The pollution sensor detection system of claim 1, wherein the at least one pollution detection sensor comprises a camera, a hyperspectral sensor, an ultrasound sensor, a thermal sensor, a humidity sensor, a temperature sensor, a pressure sensor, or a corrosion sensor.
8. The pollution detection system of claim 1, wherein the position sensor comprises a GPS sensor.
9. The pollution detection system of claim 1, wherein the position sensor detects the geographic position in three dimensions.
10. The pollution detection system of claim 1, wherein the network interface is a cellular interface that receives the geographic position and the concentration of the pollution from the automated vehicle via a cellular connection.
11. The pollution detection system of claim 1, wherein the automated vehicle is an automated air vehicle that moves through air without contacting ground, an automated ground vehicle that moves on the ground while contacting the ground, or an automated water vehicle that moves in water.
12. The pollution detection system of claim 1, wherein the network interface initially receives a general location at which the pollution is present from a source other than the automated vehicle, and the processor subsequently guides the automated vehicle to the general location and controls the movement of the automated vehicle based on the gradient to guide the automated vehicle toward the source of the pollution within the general location.
13. The pollution detection system of claim 1, wherein the processor performs an inverse geocoding query to detect a company or individual responsible for the source of the pollution.
14. A method of detecting a source of pollution, comprising:
detecting a geographic position of an automated vehicle by a position sensor disposed on the automated vehicle;
measuring a concentration of the pollution by at least one pollution detection sensor disposed on the automated vehicle;
receiving the geographic position and the concentration of the pollution via a network interface disposed at a back-end system from the automated vehicle;
storing the geographic position and the concentration of the pollution received via the network interface in a database disposed at the back-end system;
measuring, by a processor disposed at the back-end system, a gradient of the concentration of the pollution; and
controlling, by the processor, a movement of the automated vehicle based on the gradient to guide the automated vehicle toward the source of the pollution.
15. The method of claim 14, wherein the processor measures the gradient using a numerical model.
16. The method of claim 14, wherein the processor measures the gradient in real-time as the automated vehicle moves.
17. The method of claim 14, further comprising:
detecting a geographic position of each of a plurality of automated vehicles, including the automated vehicle, by a position sensor disposed on each of the plurality of automated vehicles;
measuring a concentration of the pollution by at least one pollution detection sensor disposed on each of the plurality of automated vehicles;
aggregating the concentration of the pollution measured by the plurality of automated vehicles;
measuring an aggregated gradient of the aggregated concentration of the pollution; and
controlling a movement of the plurality of automated vehicles based on the aggregated gradient to guide the plurality of automated vehicles toward the source of the pollution.
18. The method of claim 14, further comprising:
initially receiving a general location at which the pollution is present from a source other than the automated vehicle;
subsequently guiding the automated vehicle to the general location; and
controlling the movement of the automated vehicle based on the gradient to guide the automated vehicle toward the source of the pollution within the general location.
19. The method of claim 14, further comprising:
performing, by the processor, an inverse geocoding query to detect a company or individual responsible for the source of the pollution.
20. A computer program product for detecting a source of pollution, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:
detect a geographic position of an automated vehicle by a position sensor disposed on the automated vehicle;
measure a concentration of the pollution by at least one pollution detection sensor disposed on the automated vehicle;
receive the geographic position and the concentration of the pollution via a network interface disposed at a back-end system from the automated vehicle;
store the geographic position and the concentration of the pollution received via the network interface in a database disposed at the back-end system;
measure a gradient of the concentration of the pollution; and
control a movement of the automated vehicle based on the gradient to guide the automated vehicle toward the source of the pollution.
US14/966,038 2015-12-11 2015-12-11 System and method for tracking pollution Abandoned US20170168487A1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
US14/966,038 US20170168487A1 (en) 2015-12-11 2015-12-11 System and method for tracking pollution
US15/840,470 US10268198B2 (en) 2015-12-11 2017-12-13 System and method for tracking pollution

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
US14/966,038 US20170168487A1 (en) 2015-12-11 2015-12-11 System and method for tracking pollution

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US15/840,470 Division US10268198B2 (en) 2015-12-11 2017-12-13 System and method for tracking pollution

Publications (1)

Publication Number Publication Date
US20170168487A1 true US20170168487A1 (en) 2017-06-15

Family

ID=59020407

Family Applications (2)

Application Number Title Priority Date Filing Date
US14/966,038 Abandoned US20170168487A1 (en) 2015-12-11 2015-12-11 System and method for tracking pollution
US15/840,470 Active US10268198B2 (en) 2015-12-11 2017-12-13 System and method for tracking pollution

Family Applications After (1)

Application Number Title Priority Date Filing Date
US15/840,470 Active US10268198B2 (en) 2015-12-11 2017-12-13 System and method for tracking pollution

Country Status (1)

Country Link
US (2) US20170168487A1 (en)

Cited By (19)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170349282A1 (en) * 2016-06-03 2017-12-07 Wal-Mart Stores, Inc. Unmanned Aerial Vehicle Apparatus and Method
US20180245935A1 (en) * 2017-02-28 2018-08-30 International Business Machines Corporation Monitoring air pollution
CN108896713A (en) * 2018-06-26 2018-11-27 珠海市万顺睿通科技有限公司 For the method for governing pollution and governing system in gaseous contamination source
KR101968087B1 (en) * 2018-12-10 2019-04-11 대한민국 Apparatus for retrieving column amounts of ozone and nitrogen dioxide in the air using observation data of hyperspectral imaging sensor
US10268198B2 (en) 2015-12-11 2019-04-23 International Business Machines Corporation System and method for tracking pollution
CN110954658A (en) * 2019-12-02 2020-04-03 上海宝钢工业技术服务有限公司 Gridding tracing investigation method for volatile organic compounds in industrial park
TWI700593B (en) * 2018-10-15 2020-08-01 碁曄科技股份有限公司 Pollution source searching system and method using flying vehicle
US10760512B2 (en) 2018-04-25 2020-09-01 Ford Global Technologies, Llc Methods and systems for an aftertreatment system
US10851755B2 (en) 2017-11-30 2020-12-01 Bosch Automotive Service Solutions, Inc Vehicle operation adjustment using internal and external data
US10866226B1 (en) * 2017-02-07 2020-12-15 Air Stations Llc/Elevated Analytics Llc Joint Venture Multi-point ground emission source sensor system
CN112924622A (en) * 2021-01-26 2021-06-08 武汉工程大学 Unmanned aerial vehicle gas sensing and AIS information vector fusion ship tail gas tracking method
CN113655176A (en) * 2021-08-12 2021-11-16 平安国际智慧城市科技股份有限公司 Method, device and equipment for detecting pollution standard exceeding of garbage incineration and storage medium
CN113777236A (en) * 2021-09-08 2021-12-10 中科三清科技有限公司 Air quality monitoring method and device based on emission source
IT202000017158A1 (en) 2020-07-15 2022-01-15 Ecologia E Servizi Italia S R L ROAD AND ENVIRONMENTAL DATA DETECTION SYSTEM FOR URBAN SANITATION PUBLIC SERVICE VEHICLES
US11276253B2 (en) * 2016-04-05 2022-03-15 Affin As Present invention concerns a system for controlling traffic
US20220107189A1 (en) * 2020-10-06 2022-04-07 Abb Schweiz Ag Technologies for producing efficient investigation routes for identifying gas leak locations
US11379766B2 (en) * 2017-02-21 2022-07-05 International Business Machines Corporation Sensor deployment
US20230007082A1 (en) * 2021-06-30 2023-01-05 Microsoft Technology Licensing, Llc Pollutant sensor placement
CN116934101A (en) * 2023-09-19 2023-10-24 湖北君邦环境技术有限责任公司 Intelligent park auxiliary law enforcement management method and device, storage medium and electronic equipment

Families Citing this family (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3830533A4 (en) 2018-07-30 2022-04-20 SeekOps Inc. Ultra-lightweight, handheld gas leak detection device
US11144779B2 (en) * 2018-10-16 2021-10-12 International Business Machines Corporation Real-time micro air-quality indexing
EP3949039A4 (en) 2019-04-05 2022-11-30 SeekOps Inc. Analog signal processing for a lightweight and compact laser-based trace gas sensor
US20210109074A1 (en) * 2019-10-14 2021-04-15 Seekops Inc. Gas measurement instrument on unmanned vehicle
US11988598B2 (en) 2019-12-31 2024-05-21 Seekops Inc. Optical cell cleaner
US12055485B2 (en) 2020-02-05 2024-08-06 Seekops Inc. Multispecies measurement platform using absorption spectroscopy for measurement of co-emitted trace gases
US12015386B2 (en) 2020-03-25 2024-06-18 Seekops Inc. Logarithmic demodulator for laser Wavelength-Modulaton Spectroscopy
CN111220781A (en) * 2020-03-26 2020-06-02 泛测(北京)环境科技有限公司 Method for grading atmospheric pollutants on road
CN111650336A (en) * 2020-06-09 2020-09-11 新石器慧通(北京)科技有限公司 Atmospheric pollution detection method, device and system for unmanned vehicle
US11748866B2 (en) 2020-07-17 2023-09-05 Seekops Inc. Systems and methods of automated detection of gas plumes using optical imaging
CN113358817B (en) * 2021-04-22 2023-06-06 上海工程技术大学 Gas source positioning device based on gas concentration gradient driving
CN114509539B (en) * 2022-02-23 2024-06-14 广州市灏瀚环保科技有限公司 Method and system for detecting air pollution factor in living environment
US11988091B2 (en) * 2022-07-25 2024-05-21 Saudi Arabian Oil Company Subsurface contamination source detection and tracking device using artificial intelligence

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040090628A1 (en) * 2002-11-13 2004-05-13 Oleg Ershov Mappable atmospheric pollutant detection system
US20050222933A1 (en) * 2002-05-21 2005-10-06 Wesby Philip B System and method for monitoring and control of wireless modules linked to assets
US20110208414A1 (en) * 2010-02-25 2011-08-25 Siemens Aktiengesellschaft Method and determining system for automatically determining emission locations, and method and traffic control system based thereon for immission-dependent traffic control
US20150286785A1 (en) * 2012-11-21 2015-10-08 The Trustees Of Columbia University In The City Of New York Systems, methods, and devices for image reconstruction using combined pde-constrained and simplified spherical harmonics algorithm
US20170076509A1 (en) * 2014-03-03 2017-03-16 Inrix Inc. Assessing environmental impact of vehicle transit

Family Cites Families (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE3802337C1 (en) 1988-01-27 1989-07-13 Messerschmitt-Boelkow-Blohm Gmbh, 8012 Ottobrunn, De
US5927648A (en) 1996-10-17 1999-07-27 Woodland; Richard Lawrence Ken Aircraft based sensing, detection, targeting, communications and response apparatus
US5726450A (en) 1996-10-26 1998-03-10 Envirotest Systems Corp. Unmanned integrated optical remote emissions sensor (RES) for motor vehicles
FR2758200B1 (en) * 1997-01-09 1999-02-12 Schlumberger Ind Sa AUTOMOTIVE POLLUTION MONITORING DEVICE IN URBAN AREAS
JP2007500638A (en) 2003-07-31 2007-01-18 ソーラー セーラー ピーティーワイ リミテッド Unmanned marine boat
US20100265329A1 (en) 2006-10-06 2010-10-21 Doneker Robert L Lightweight platform for remote sensing of point source mixing and system for mixing model validation and calibration
EP2199790A1 (en) 2008-12-19 2010-06-23 Duvas Technologies Limited System and apparatus for measurement and mapping of pollutants
US8269971B1 (en) 2009-11-12 2012-09-18 Exelis, Inc. System and method for simultaneous detection of a gas using a mode-locked based transmitter
EP2699888A4 (en) 2010-08-15 2015-08-26 Airbase Systems Ltd Device, system and method for personal health monitoring based on multitude-points environmental data
IT1401884B1 (en) 2010-10-06 2013-08-28 Tea Sistemi S P A METHOD FOR QUANTIFYING A FLOW OF GAS FUGITIVE BY MEANS OF VERTICAL CONCENTRATION MEASUREMENTS
KR102035693B1 (en) 2010-12-23 2019-10-23 한국전자통신연구원 Method of monitoring air pollution and system for the same
US20120271561A1 (en) 2011-04-22 2012-10-25 Andrew Keller-Goralczyk System and method for aircraft pollution accountability and compliance tracking
US20130278427A1 (en) 2012-04-22 2013-10-24 Michael Setton Method and system for visually reporting a local environmental condition
US9251698B2 (en) 2012-09-19 2016-02-02 The Boeing Company Forest sensor deployment and monitoring system
CN102980977A (en) 2012-12-10 2013-03-20 环境保护部卫星环境应用中心 Unmanned pollution gas monitoring system
US20170168487A1 (en) 2015-12-11 2017-06-15 International Business Machines Corporation System and method for tracking pollution

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050222933A1 (en) * 2002-05-21 2005-10-06 Wesby Philip B System and method for monitoring and control of wireless modules linked to assets
US20040090628A1 (en) * 2002-11-13 2004-05-13 Oleg Ershov Mappable atmospheric pollutant detection system
US20110208414A1 (en) * 2010-02-25 2011-08-25 Siemens Aktiengesellschaft Method and determining system for automatically determining emission locations, and method and traffic control system based thereon for immission-dependent traffic control
US8903646B2 (en) * 2010-02-25 2014-12-02 Siemens Aktiengesellschaft Method and determining system for automatically determining emission locations, and method and traffic control system based thereon for immission-dependent traffic control
US20150286785A1 (en) * 2012-11-21 2015-10-08 The Trustees Of Columbia University In The City Of New York Systems, methods, and devices for image reconstruction using combined pde-constrained and simplified spherical harmonics algorithm
US20170076509A1 (en) * 2014-03-03 2017-03-16 Inrix Inc. Assessing environmental impact of vehicle transit

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
Ferrite Gas Sensors; Ashok B. Gadkari; Tukaram J. Shinde; Pramod Nivrutti Vasambekar; IEEE Sensors Journal; Year: 2011, Volume: 11, Issue: 4; Pages: 849 - 861, DOI: 10.1109/JSEN.2010.2068285 *
NIUST - Deepwater horizon oil spill response cruise; A. -R. Diercks; V. L. Asper; R. Highsmith; M. Woolsey; S. Lohrenz; K. McLetchie; A. Gossett; M. Lowe; D. Joung; L. McKay; S. Joye; A. Teske ;OCEANS 2010 MTS/IEEE SEATTLE Year: 2010; Pages: 1 - 7, DOI: 10.1109/OCEANS.2010.5664443 *
Sustainable transport in Tunisia: An analysis of the environmental Kuznets curve; Rafaa Mraihi; Riadh Harizi; Sondes Alaouia 2013 International Conference on Advanced Logistics and Transport; Year: 2013; Pages: 30 - 34, DOI: 10.1109/ICAdLT.2013.6568430 *
Tunable diode laser absorption spectroscopy for sensing CO and CO2 of vehicle emissions based on temperature tuning; Nan Gao; Zhen-hui Du; Jin-yi Li; Xue-hong Zhao; Yan Wang; 2011 International Conference on Business Management and Electronic Information; Year: 2011, Volume: 4; Pages: 853 - 856, DOI: 10.1109/ICBMEI.2011.5914237 *

Cited By (23)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10268198B2 (en) 2015-12-11 2019-04-23 International Business Machines Corporation System and method for tracking pollution
US11276253B2 (en) * 2016-04-05 2022-03-15 Affin As Present invention concerns a system for controlling traffic
US20170349282A1 (en) * 2016-06-03 2017-12-07 Wal-Mart Stores, Inc. Unmanned Aerial Vehicle Apparatus and Method
US10866226B1 (en) * 2017-02-07 2020-12-15 Air Stations Llc/Elevated Analytics Llc Joint Venture Multi-point ground emission source sensor system
US11379766B2 (en) * 2017-02-21 2022-07-05 International Business Machines Corporation Sensor deployment
US10578448B2 (en) * 2017-02-28 2020-03-03 International Business Machines Corporation Monitoring air pollution using a mobile pollution detecting device
US20180245935A1 (en) * 2017-02-28 2018-08-30 International Business Machines Corporation Monitoring air pollution
US10851755B2 (en) 2017-11-30 2020-12-01 Bosch Automotive Service Solutions, Inc Vehicle operation adjustment using internal and external data
US10760512B2 (en) 2018-04-25 2020-09-01 Ford Global Technologies, Llc Methods and systems for an aftertreatment system
CN108896713A (en) * 2018-06-26 2018-11-27 珠海市万顺睿通科技有限公司 For the method for governing pollution and governing system in gaseous contamination source
TWI700593B (en) * 2018-10-15 2020-08-01 碁曄科技股份有限公司 Pollution source searching system and method using flying vehicle
KR101968087B1 (en) * 2018-12-10 2019-04-11 대한민국 Apparatus for retrieving column amounts of ozone and nitrogen dioxide in the air using observation data of hyperspectral imaging sensor
CN110954658A (en) * 2019-12-02 2020-04-03 上海宝钢工业技术服务有限公司 Gridding tracing investigation method for volatile organic compounds in industrial park
IT202000017158A1 (en) 2020-07-15 2022-01-15 Ecologia E Servizi Italia S R L ROAD AND ENVIRONMENTAL DATA DETECTION SYSTEM FOR URBAN SANITATION PUBLIC SERVICE VEHICLES
US20220107189A1 (en) * 2020-10-06 2022-04-07 Abb Schweiz Ag Technologies for producing efficient investigation routes for identifying gas leak locations
US11761590B2 (en) * 2020-10-06 2023-09-19 Abb Schweiz Ag Technologies for producing efficient investigation routes for identifying gas leak locations
EP3982099B1 (en) * 2020-10-06 2024-07-24 ABB Schweiz AG Technologies for producing efficient investigation routes for identifying gas leak locations
CN112924622A (en) * 2021-01-26 2021-06-08 武汉工程大学 Unmanned aerial vehicle gas sensing and AIS information vector fusion ship tail gas tracking method
US20230007082A1 (en) * 2021-06-30 2023-01-05 Microsoft Technology Licensing, Llc Pollutant sensor placement
CN113655176A (en) * 2021-08-12 2021-11-16 平安国际智慧城市科技股份有限公司 Method, device and equipment for detecting pollution standard exceeding of garbage incineration and storage medium
CN113777236A (en) * 2021-09-08 2021-12-10 中科三清科技有限公司 Air quality monitoring method and device based on emission source
CN113777236B (en) * 2021-09-08 2022-04-26 中科三清科技有限公司 Air quality monitoring method and device based on emission source
CN116934101A (en) * 2023-09-19 2023-10-24 湖北君邦环境技术有限责任公司 Intelligent park auxiliary law enforcement management method and device, storage medium and electronic equipment

Also Published As

Publication number Publication date
US10268198B2 (en) 2019-04-23
US20180101175A1 (en) 2018-04-12

Similar Documents

Publication Publication Date Title
US10268198B2 (en) System and method for tracking pollution
Boubrima et al. On the deployment of wireless sensor networks for air quality mapping: Optimization models and algorithms
US10830922B2 (en) Air quality forecast by adapting pollutant emission inventory
CN106441354B (en) The method and apparatus for assessing the operation of onboard navigation system for using lateral shift data
JP7048928B2 (en) Air pollution source recognition based on dynamic pairing and comparison
US10386258B1 (en) Systems and methods for detecting changes in emission rates of gas leaks in ensembles
KR101900777B1 (en) Server for city enviromental analysis, and control method thereof
EP3523995B1 (en) Method and system for remote processing and analysis of industrial asset inspection data
Payra et al. Multirule based diagnostic approach for the fog predictions using WRF modelling tool
CN103370601A (en) System and method for determining altitude
US20170328522A1 (en) Automated Gas Detection and Reporting System
US11309921B2 (en) Interference level map of radio frequency signals
US20220357231A1 (en) Technologies for improved visualization of gas leak detection data
Stengel et al. The impact of cloud‐affected IR radiances on forecast accuracy of a limited‐area NWP model
Ulil et al. The vehicle as a mobile sensor network base IoT and big data for pothole detection caused by flood disaster
KR20140024541A (en) System for providing atmospheric modeling system service
US20230007082A1 (en) Pollutant sensor placement
EP4038357A1 (en) Closed surface flight pattern generation for unmanned aerial vehicle (uav) flux plane assessment
Boubrima et al. Robust mission planning of UAV networks for environmental sensing
Tian et al. Estimating methane emissions from underground natural gas pipelines using an atmospheric dispersion-based method
CN115455814A (en) Pollution source searching and pollutant distribution predicting method and system based on deep learning
Fridelin et al. Implementation of microservice architectures on SEMAR extension for air quality monitoring
Zhao et al. Scalar flux–gradient relationships under unstable conditions over water in coastal regions
US20230169222A1 (en) Pollutant sensor placement
Boubrima et al. Error-bounded air quality mapping using wireless sensor networks

Legal Events

Date Code Title Description
AS Assignment

Owner name: INTERNATIONAL BUSINESS MACHINES CORPORATION, NEW Y

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:MANTRIPRAGADA, KIRAN;MELLO, ULISSES;NEMOTO, RAFAEL HORSCHUTZ;AND OTHERS;SIGNING DATES FROM 20151112 TO 20151123;REEL/FRAME:037268/0020

STCB Information on status: application discontinuation

Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION