WO2009089281A1 - Système et procédé pour conditionner un signal reçu au niveau d'un dispositif d'acquisition à base de mems - Google Patents

Système et procédé pour conditionner un signal reçu au niveau d'un dispositif d'acquisition à base de mems Download PDF

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Publication number
WO2009089281A1
WO2009089281A1 PCT/US2009/030330 US2009030330W WO2009089281A1 WO 2009089281 A1 WO2009089281 A1 WO 2009089281A1 US 2009030330 W US2009030330 W US 2009030330W WO 2009089281 A1 WO2009089281 A1 WO 2009089281A1
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WIPO (PCT)
Prior art keywords
input signal
event
signal
acquisition device
computer
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PCT/US2009/030330
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English (en)
Inventor
Cory James Stephanson
Original Assignee
Broadband Discovery Systems, Inc.
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
Priority claimed from US12/008,491 external-priority patent/US20100283849A1/en
Priority claimed from US12/008,551 external-priority patent/US8050413B2/en
Priority claimed from US12/008,492 external-priority patent/US20090182524A1/en
Application filed by Broadband Discovery Systems, Inc. filed Critical Broadband Discovery Systems, Inc.
Publication of WO2009089281A1 publication Critical patent/WO2009089281A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/0082—Monitoring; Testing using service channels; using auxiliary channels
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/20—Monitoring; Testing of receivers
    • H04B17/23—Indication means, e.g. displays, alarms, audible means
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters

Definitions

  • the invention relates to the field of signal acquisition and processing.
  • computing systems are used throughout daily life including both work and entertainment.
  • Examples of well known computing systems include personal computers, server computers and network computers.
  • Many home computers are used for various forms of entertainment, such as listening to music and surfing the Internet.
  • Many businesses provide their employees with computing systems in order to perform various office tasks, such as database entry and word processing.
  • a system and method for monitoring for a specified frequency band is disclosed.
  • the technology initially utilizes a micro-electromechanical system (“MEMS") based acquisition device to monitor an environment.
  • MEMS micro-electromechanical system
  • the MEMS device receives a signal from the environment, and generates an input signal comprising an electronic representation of the received environmental signal.
  • This input signal is then conditioned for at least one frequency band.
  • Embodiments of the invention next allow the conditioned signal to be compared to various pre-defined events in order to determine the signal's origin.
  • a system and method of event detection involves prequalifying an input signal received from an environmental monitoring device for a specific frequency band.
  • the input signal is compared to a database of reference signals each having an associated event frequency range, and conditioned to generate a conditioned signal with a refined frequency spectrum when the comparison results in a match.
  • the conditioned signal is then utilized to identify at least one event attribute corresponding to an event associated with the input signal, and the identified event attribute is outputted.
  • a system and method of environmental monitoring and event detection utilizes a micro-electromechanical system ("MEMS") based acquisition device to monitor an environment.
  • An environmental input signal is received at the MEMS based acquisition device, and an electronic input signal is generated that corresponds to the environmental input signal.
  • This electronic input signal is prequalified for a specific frequency band, compared to a database of reference signals each having an associated event frequency range, and conditioned to generate a conditioned signal with a refined frequency spectrum when the comparison results in a match.
  • the conditioned signal is then utilized to identify at least one event attribute corresponding to an event associated with the electronic input signal, and the identified event attribute is outputted.
  • a computer-implemented method for monitoring for a specified frequency band comprising: utilizing a micro-electromechanical (MEMS) based acquisition device to monitor an environment; receiving an environmental input signal at said MEMS based acquisition device; generating an input signal at said MEMS based acquisition device, said input signal comprising an electronic representation of said environmental input signal; and conditioning said input signal for at least one specific frequency band.
  • MEMS micro-electromechanical
  • An environmental monitor comprising: a micro-electromechanical (MEMS) based acquisition device that monitors an environment, receives at least one environmental input signal from within said environment, and generates an input signal comprising an electronic representation of said environmental input signal; and a signal conditioner coupled with said MEMS based acquisition device, said signal conditioner receiving said input signal from said MEMS based acquisition device and comparing said input signal against at least one specific frequency band.
  • MEMS micro-electromechanical
  • a computer-implemented method of event detection comprising: prequalifying a first input signal for a specific frequency band, said first input signal received from an environmental monitoring device; comparing said first input signal to a database of reference signals, each reference signal in said database having an associated event frequency range; conditioning said first input signal to generate a conditioned signal with a refined frequency spectrum when said comparing results in a match; and utilizing said conditioned signal to identify at least one event attribute corresponding to an event associated with said first input signal, and outputting said at least one event attribute.
  • An event detection system comprising: a prequalification device that prequalifies an input signal received from an environmental monitoring device for a specific frequency band; a processing unit coupled to said prequalification device, said processing unit comparing said input signal to a database of reference signals, each reference signal in said database having an associated event frequency range; a refined conditioning system coupled to said processing unit, said refined conditioning system conditioning said input signal to generate a conditioned signal with a refined frequency spectrum when said comparing results in a match; and a refined event determination system coupled to said refined conditioning system, said refined event determination system utilizing said conditioned signal to identify at least one event attribute corresponding to an event associated with said input signal.
  • Concept 32 The system of Concept 31 wherein said refined event determination system generates an output signal that identifies said at least one event attribute, and transmits said output signal to a receiver.
  • Concept 33 The system of Concept 31 wherein said input signal is associated with an input selected from a group of input signal receivers consisting of electronic, magnetic, electromagnetic audio, visual, olfactory, taste-sensory, temperature, pressure, and radioactive data receivers.
  • Concept 34 The system of Concept 31, further comprising: a storage unit that stores processed data such that said processed data may be subsequently retrieved and further processed.
  • Concept 40 The computer-usable medium of Concept 38, further comprising: initiating a second environmental monitoring device when said first input signal is prequalified; receiving a second input signal from said second environmental monitoring device, said first input signal and said second input signal being associated with different environmental data types; and prequalifying said second input signal along with said first input signal.
  • Concept 42 The computer-usable medium of Concept 38, wherein said at least one event attribute is selected from a group of event types consisting of a specific calibers of gunshots, types of firecrackers, cars backfiring, aerosol spray can discharges, pipeline leaks, spoken words, faces associated with specific people, images of guns, images of knives, unique vehicle license plates, or toxic chemicals.
  • event types consisting of a specific calibers of gunshots, types of firecrackers, cars backfiring, aerosol spray can discharges, pipeline leaks, spoken words, faces associated with specific people, images of guns, images of knives, unique vehicle license plates, or toxic chemicals.
  • a computer-implemented method of environmental monitoring and event detection comprising: utilizing a micro-electromechanical (MEMS) based acquisition device to monitor an environment; receiving an environmental input signal at said MEMS based acquisition device; generating an electronic input signal at said MEMS based acquisition device, said electronic input signal corresponding to said environmental input signal; prequalifying said electronic input signal for a specific frequency band; comparing said electronic input signal to a database of reference signals, each reference signal in said database having an associated event frequency range; conditioning said electronic input signal to generate a conditioned signal with a refined frequency spectrum when said comparing results in a match; and utilizing said conditioned signal to identify at least one event attribute corresponding to an event associated with said electronic input signal, and outputting said at least one event attribute.
  • MEMS micro-electromechanical
  • An environmental monitoring and event detection system comprising: a micro-electromechanical (MEMS) based acquisition device that monitors an environment, receives an environmental input signal and generates an electronic input signal corresponding to said environmental input signal; a prequalification device that prequalif ⁇ es an electronic input signal received from an MEMS based acquisition device for a specific frequency band; a processing unit coupled to said prequalification device, said processing unit comparing said electronic input signal to a database of reference signals, each reference signal in said database having an associated event frequency range; a refined conditioning system coupled to said processing unit, said refined conditioning system conditioning said electronic input signal to generate a conditioned signal with a refined frequency spectrum when said comparing results in a match; and a refined event determination system coupled to said refined conditioning system, said refined event determination system utilizing said
  • MEMS micro-electromechanical
  • Concept 54 The system of Concept 53, further comprising an alert triggering module that executes an end video operation when said at least one event attribute is identified, said end video operation causing said video feed to terminate.
  • Concept 55 The system of Concept 51, further comprising an alert triggering module that generates an output signal identifying said at least one event attribute, and transmits said output signal to a remote receiver.
  • Concept 56 The system of Concept 51 wherein said refined conditioning system further comprises a linear discriminate analysis module that digitally represents component parts of said conditioned signal.
  • Figure 1 is a block diagram of an exemplary system according to an embodiment of the present technology wherein an environment is monitored for an event.
  • Figure 2 is a block diagram of an exemplary system used in accordance with an embodiment of the present technology for acquiring and conditioning an input signal.
  • Figure 3 is a block diagram of an exemplary system used in accordance with an embodiment of the present technology for prequalifying an input signal for a predefined event.
  • Figure 4 is a block diagram of an exemplary system according to an embodiment of the present technology wherein a prequalified signal is determined to be a specific pre-defined event.
  • Figure 5 is a block diagram of an exemplary system according to an embodiment of the present technology wherein a first conditioning stage is combined with a second conditioning stage.
  • Figure 6 is a block diagram of an exemplary system according to an embodiment of the present technology that demonstrates possible system responses resulting from the event determination process.
  • Figure 7 is a flowchart of an exemplary method for monitoring for a specified frequency band in accordance with an embodiment of the present technology.
  • Figure 8 is a flowchart of an exemplary method of event detection in accordance with an embodiment of the present technology.
  • Figure 9 is a flowchart of an exemplary method of environmental monitoring and event detection in accordance with an embodiment of the present technology.
  • An embodiment of the present invention relates to a system for monitoring an environment for a specific frequency band.
  • the technology initially utilizes a micro- electromechanical system ("MEMS") based acquisition device to monitor an environment.
  • MEMS micro- electromechanical system
  • the MEMS device receives a signal from the environment, and generates an input signal comprising an electronic representation of the received environmental signal.
  • This input signal is then conditioned for at least one frequency band for which the system is configured to monitor.
  • the input signal is first sampled, such that a conditioning unit may perform a frequency check on a plurality of discrete samples associated with the input signal.
  • Another embodiment of the present technology relates to a prequalif ⁇ cation stage for prequalifying the conditioned signal for a specific frequency range.
  • the prequalif ⁇ cation stage determines whether the environmental input signal might be categorized as one or more predefined events for which the system is monitoring.
  • a prequalif ⁇ cation device implements a frequency check to determine whether the detected environmental signal oscillates within a specific, predefined frequency range that represents a characteristic frequency spectrum of a range of predefined events.
  • Yet another embodiment relates to a preliminary event processing system in which a detected environmental signal is identified to be the result of a single event among a group of predefined events.
  • the system implements a process of event determination by comparing the characteristic peaks and frequencies of a conditioned input signal to those of a number of similar signals from the signal database.
  • a event determination process yields an assessment of whether the detected environmental signal is similar enough to a predefined event from the signal database such that the signal may be classified as one of such predefined events. If such classification is warranted, then the event determination process identifies the specific event.
  • An alternative embodiment of the present technology implements a refined conditioning system where acquired data can be further conditioned so that specific attributes of a detected event can be identified.
  • a bandpass filter is utilized to further condition the data for a specific and more refined frequency spectrum.
  • a signal analysis converter then takes the conditioned data and converts it into a format that the system can efficiently and accurately analyze, and that can be easily viewed and mathematically represented for later analysis.
  • a linear discriminate analysis module next acquires a waveform of the formatted data and digitally represents each of its component parts.
  • a refined event detection process identifies one or more attributes associated with a detected event.
  • the proficiency of the refined event determination process of the refined conditioning system can be further increased by implementing a partial matrix that utilizes a set of trained data and calculates a specific degree of accuracy regarding identification by the system of an inputted signal as a specific event.
  • An event detection system may be further configured to execute a specific response once an event determination process has taken place.
  • This response may be predefined by a user, or otherwise determined on-the-fly such that the system decides the best method for responding to a detected event.
  • the environmental input signal is assigned an event ID for identification purposes.
  • An alert triggering module then executes one or more predefined response operations that have been assigned to the identified event.
  • the alert triggering module may be further configured to generate an output signal that communicates information relating to an identified event.
  • An environmental input signal 110 is produced by an event that occurs in the monitored environment.
  • This environmental input signal may be any type of signal that is capable of being detected.
  • the environmental input signal is a sound signal that resonates at a certain frequency.
  • This characteristic frequency may be sonic, ultrasonic, subsonic, etc.; indeed, the sound signal may be audible or non-audible.
  • the vibration of the environmental input signal need only be capable of being detected for the present embodiment to be practiced.
  • the environmental input signal may be a light signal or visual image.
  • a light signal itself has a characteristic frequency that is capable of being detected. For example, the frequency characteristics of a visible light signal are capable of being detected by the human eye, whereas the frequency of an ultraviolet (UV) light signal is capable of being detected by UV light detectors.
  • UV ultraviolet
  • a signal acquisition device 120 is used to monitor the environment for an event.
  • the signal acquisition device detects the characteristic frequency of the environmental input signal 110, and converts the detected signal into an electronic input signal 130 that may later be processed by an electronic event detection system.
  • This conversion process comprises the generation of an electronic input signal 130 that is an electronic representation of the frequency characteristics of the detected environmental input signal 110.
  • the signal acquisition device 120 monitors the environment for a broadband, multi-frequency signal that is non-discriminate in nature.
  • the signal acquisition device may be configured such that it selectively monitors an environment by being active for a certain period of time and then inactive for another period of time.
  • a system timing device such as a quartz, GPS or atomic clock.
  • the device may be cycled on and off depending on when a user wishes to monitor an environment.
  • a home security system implementing this embodiment of the invention could be configured to monitor for intruders only during the hours that the homeowner is generally away from home (e.g., during normal weekday work hours).
  • the security system could be programmed to begin monitoring the environment at 7:30 a.m., and then cease monitoring at 5:30 p.m.
  • the signal acquisition device 120 is a micro-electromechanical system ("MEMS") based acquisition device, as opposed to a traditional audio microphone or ultrasonic transducer.
  • MEMS micro-electromechanical system
  • a traditional microphone is capable of detecting acoustic frequencies between 0 and 10 kHz
  • modern MEMS devices are capable of detecting between 0 and 100 kHz, and beyond, and in many cases, can succeed in doing so without adding much distortion.
  • MEMS devices are even capable of operating in the gigahertz range.
  • MEMS devices are capable of acquiring ultrasonic sound, which is above the normal, audible sound range.
  • MEMS devices may be configured to acquire non-audio data, such as visual imaging signals.
  • the acquisition of such visual imaging signals is combined with specific machine vision algorithms. For example, an image could be received by the MEMS device, and a first algorithm could be implemented to "clean-up" the image such that a foreground object can be better differentiated from the image's background. Then, a second algorithm could be implemented to analyze various features of a specific foreground object and compare them to attributes associated with an array of known objects in an object database. In this manner, a person skilled in the art could utilize this embodiment of the present technology for image recognition applications.
  • the aforementioned example could be utilized by security personnel at an airport to monitor a specific terminal for certain high-profile individuals who might constitute a security threat.
  • a security system that is configured to monitor for and recognize a characteristic shape of a specific weapon (such as a handgun).
  • any noise that the signal acquired during the transmission process will be amplified as well.
  • amplifiers are plagued by a non-linear amplification characteristic that not only amplifies any noise that was acquired during the transmission, but which also injects an additional degree of distortion into the amplified signal.
  • modern amplifiers play an important role in "boosting" the strength of a received signal, they are mired by undesirable attributes with regard to signal processing applications.
  • modern MEMS technology permits a signal to be acquired without injecting a significant degree of gain. This translates into less noise overall, and less chance of inaccuracy regarding the original signal acquisition and subsequent event determination.
  • An environmental input signal 110 is produced by an event that occurs in an external environment.
  • a MEMS based acquisition device 220 monitors the external environment for such an event.
  • the MEMS based acquisition device 220 operates in the 0 to 100 kHz frequency spectrum, but this range may be controlled and changed depending on the needs and the objectives of the user. For instance, a user may configure the MEMS based acquisition device so as to concentrate on a specific frequency range (such as may be used for gunshot detection, graffiti detection, or machine vision applications).
  • the MEMS based acquisition device 220 of Figure 2 Upon detecting the environmental input signal 110, the MEMS based acquisition device 220 of Figure 2 translates the detected signal 110 into an electronic input signal 230 that can then be conditioned for a specific frequency.
  • the electronic input signal 230 is an electronic representation of the environmental input signal 110. That is, the electronic input signal 230 represents, in an electronic form, the frequency characteristics of the environmental input signal 110, such that these frequency characteristics may be analyzed and processed by the system 200.
  • the environmental input signal 110 is a sound signal comprising mechanical vibrations that are detected by the MEMS based acquisition device 220, these mechanical vibrations will be translated into an electronic format that can then be processed by the system 200.
  • the system 200 utilizes a predefined process of regular sampling 240 to acquire discrete samples 250 of the electronic input signal 230 at various points of the signal's 230 oscillation pattern.
  • a first conditioning stage 260 is then implemented to condition the environmental input signal 110 for a specific frequency.
  • the discrete samples 250 are transmitted to a conditioning device 261 that implements a predefined frequency check 262.
  • the frequency check 262 is used to determine whether the detected environmental signal oscillates within a specific, predefined frequency range.
  • an output signal 270 is generated that can later be processed by the system 200.
  • a system 300 for prequalifying an input signal for a pre-defined event is shown.
  • the system 300 implements a prequalification stage 310 for determining whether the environmental input signal might be categorized as one or more predefined events for which the system 300 is monitoring.
  • a prequalification device 311 implements a frequency check 312 to determine whether the detected environmental signal 110 oscillates within a specific, predefined frequency range that represents a characteristic frequency spectrum of a range of predefined events.
  • the engine of a truck such as a tractor trailer used for transporting and/or distributing goods, may break down while the vehicle is in transit due to a faulty ball bearing, and while the ball bearing is relatively inexpensive, the damaged engine (as well as other damages resulting to the remainder of the vehicle, the driver and passengers, and the vehicle's cargo) may prove to be quite costly.
  • an embodiment of the present technology could be configured such that the prequalification device 311 implements a frequency check 312 that focuses on the frequency characteristics associated with the acoustic sounds resulting from a faulty ball bearing.
  • the system 300 could detect the presence of an error associated with such a ball bearing before damage is caused to the truck and engine, and this information could then be communicated to the driver. The driver could then immediately stop the vehicle and seek repairs.
  • prequalification is not limited to a frequency check.
  • an image check could also be implemented wherein various machine vision techniques and algorithms are implemented so as to check for a specific predefined image.
  • sound may be inputted into the prequalification device 311 and additionally qualified with other sources of data or data types (e.g., temperature, humidity, light/darkness, motion and/or imaging, etc.).
  • an embodiment of the present technology could be implemented wherein an acoustic frequency check for a faulty ball bearing is initiated only when a vehicle is in motion. This would seem to make sense as far as system functionality is concerned, because a faulty ball bearing will generally only create a noise when the vehicle is moving as opposed to when the vehicle is parked.
  • the system 300 may be configured so as to add as much additional information and data as is desired for the user's objectives.
  • the prequalification device 311 implements a frequency check 312 to determine whether the detected environmental signal 1 10 should be categorized as one or more predefined events for which the system 300 is monitoring. After the prequalification stage 310 has finished processing a signal, the system 300 generates a prequalified output signal 320 that may later be processed by the system 300 for purposes of refined event determination. Pursuant to one embodiment, if the prequalification device 311 does not successfully prequalify an event, the device 311 yields a system null which resets the prequalification system 300, and the MEMS based acquisition device 220 continues to monitor for an event.
  • a system 400 for processing a prequalif ⁇ ed signal for purposes of event determination is shown. After the input signal 130 has been conditioned and prequalii ⁇ ed for a specific frequency range, the system 400 determines 410 whether the environmental input signal 110 is the result of an acoustic event. The system 400 next implements a preliminary processing stage 420 for purposes of preliminary event determination.
  • the processing unit 421 in Figure 4 compares data to a known database 424 of similar signals, which correspond to predefined events.
  • the preliminary processing unit 421 then carries out a process of event determination 425 by comparing the characteristic peaks and frequencies of a conditioned signal to those of a number of similar signals from the signal database 424.
  • the event determination process 425 yields an assessment of whether the conditioned signal is similar enough to a predefined event from the signal database 424 such that the environmental input signal 110 may be classified as having resulted from one of such predefined events. If such a classification is warranted, then the event determination process 425 identifies the specific event that the input signal 110 has been identified as by the system 400.
  • the system 400 does not simply output a binary response (e.g., that a discharge from a spray canister was or was not identified). Rather, the system 400 discretely identifies specific attributes of the event that has been identified (e.g., that a detected spray canister is an aerosol spray can).
  • the system 400 Subsequent to processing 420, the system 400 generates an output signal 450 that comprises the results of the event determination process 425. Thus, the output signal communicates the specific event that has been identified, or that no event was determined to have transpired in the monitored environment if the system 400 determines that no such event has occurred. In one embodiment, if an event is not qualified, the system 400 continues to monitor the environment for a predetermined event (i.e., the entire process cycles back and begins again). [00109] Referring still to Figure 4, a prequalif ⁇ ed signal may be analyzed together with other input signals 440. These other input signals 440 need not be acquired by the same MEMS based acquisition device 220, as different inputs can have their own parallel channels in the system 400.
  • logic e.g. AND/NAND technology
  • prequalification technology may be used in combination with the prequalification technology such that multiple required events must be present in order for the process to continue.
  • qualification of one input is dependent upon the qualification of another input.
  • This latter application offers great utility regarding early event detection systems. For instance, if a specific sound is detected (e.g. aerosol spray can discharge), the system can then concentrate its efforts on monitoring for a specific image (e.g. a human form present in the area of interest). This provides an example of how one skilled in the art might implement the present technology to quickly identify and deter certain undesirable events (in this case, graffiti).
  • the present technology could be implemented as an event detection security system in which the qualification of one input is dependent upon the qualification of another input.
  • the system 400 could be configured such that selective monitoring occurs between dusk and dawn, and such that infrared motion as well as certain predefined sounds must be present in order for an event to be identified, and a particular task carried out.
  • the system 400 when the event determination process 425 identifies a particular predefined event (e.g., the possible presence of a burglar) for which the system 400 is configured to monitor, the system sounds an alarm to alert a user of the identification of the predefined event. For example, if the system 400 identifies what may be a burglar breaking into a dwelling, the system 400 then notifies a user, such as the owner or an inhabitant of the dwelling, by sounding an audible alarm configured to be heard by a human being. In an alternative embodiment, the system 400 is coupled to a communication network and configured to automatically notify the police when the presence of a potential burglar is detected.
  • a particular predefined event e.g., the possible presence of a burglar
  • the system 400 may be configured to carry out a different task once the event determination process 425 identifies a particular predefined event. For example, if the presence of a potential burglar is detected, the system 400 could be configured to turn on one or more lights, such a light located in the vicinity of any detected motion associated with the detected event. Thus, in the event that a burglar is detected near a dwelling, the system 400 could be configured to turn on a group of outside lights to scare the burglar off or notify others, such as occupants and neighbors of the dwelling, of the detected event. According to an alternative embodiment, the system 400 may be configured to automatically take an action to incapacitate an identified threat. For example, if the system 400 detects a person scaling an electric fence, the system 400 would automatically turn on or adjust the current being driven through the fence in order to temporarily incapacitate the person.
  • the system 400 is configured to automatically lock one or more entrances to a structure when the presence of a potential burglar is detected.
  • the system 400 could be implemented in an office building having doors and windows that may be electronically locked, and wherein the system 400 is configured to monitor for potential prowlers. If the system 400 identifies what may be a potential prowler, the system 400 automatically locks the building's doors and windows.
  • the system 400 may be further configured carry out other operations. For example, the system 400 could be configured to access a communication network and send a message to one or more security personnel that a potential prowler has been detected.
  • the sent message could include one or more attributes associated with the event, such as the location of the building, where precisely the event was detected, contact information for certain persons of interest (e.g., the owner or lessee of the building), or directions for the recipient of the message. For instance, upon detecting the presence of a potential prowler, the system 400 could send an electronic message that directs a security guard to immediately contact the police, relay the message to the police, and then proceed, with caution to the specific location where the event was detected.
  • attributes associated with the event such as the location of the building, where precisely the event was detected, contact information for certain persons of interest (e.g., the owner or lessee of the building), or directions for the recipient of the message.
  • the system 400 upon detecting the presence of a potential prowler, the system 400 could send an electronic message that directs a security guard to immediately contact the police, relay the message to the police, and then proceed, with caution to the specific location where the event was detected.
  • the system 400 may be further configured to implement video triggered 422 and still image triggered 423 events for processing data associated with detected images and motion.
  • the processing unit could be configured to execute a begin video operation in response to a received input signal, wherein the begin video operation cause a video clip to be captured 400 by the system. Then, the video triggered event 422 would analyze movement of a foreground object present in the captured video clip.
  • the still image triggered event 423 could be configured to analyze physical attributes associated with a foreground image located in a captured still image.
  • the system 400 is configured to detect the presence of a potential threat in an area of interest and automatically respond to the potential threat.
  • the system 400 could be configured to monitor for certain images and motion in an area that surrounds a military installation. If the system 400 identifies a gunshot coming from a specific direction, the system 400 analyzes the output of the video triggered 422 and still image triggered 423 events in order to determine the direction from which the shot was fired.
  • the system 400 is coupled to a firearm that may be electronically triggered, and the system 400 is further configured to automatically return fire when the direction of a detected gunshot has been identified.
  • results of the video triggered 422 and still image triggered 423 events are saved into storage 430 so that they may be subsequently retrieved by the system 400.
  • the results of these events 422, 423 are first stored in a temporary storage unit 431, and next transmitted to a permanent storage unit 432 for long term storage applications.
  • the system storage 430 serves a dual purpose: First, it allows the system 400 to later retrieve these results in order to conduct further processing and/or conditioning of an acquired signal. Second, it allows for the option of providing further training to the system 400 (i.e., an active learning process may be implemented, which in the long run, can increase overall system efficiency and performance). This can allow the system 400, in the future, to quickly identify events that are similar to the specific predefined events that the system 400 was originally configured to identify.
  • the system 400 could be configured to monitor for gunshot sounds, and upon hearing a firecracker, the system would initiate the conditioning and prequalification stages 260, 310. Although unlikely, if the sound of the firecracker resonates at a frequency that is similar to a gunshot for which the system is monitoring, then the input signal 110 will satisfy the prequalification stage 310. Once the firecracker is determined to be an acoustic event 410, the system 400 initiates the preliminary processing stage 420, wherein the event determination process 425 determines that the acquired environmental input signal 110 (i.e., the sound of the firecracker) does not share the same exact frequency characteristics of any event in the signal database 424.
  • the event determination process 425 determines that the acquired environmental input signal 110 (i.e., the sound of the firecracker) does not share the same exact frequency characteristics of any event in the signal database 424.
  • the system 400 can next classify the environmental input signal 110 as an event of interest for future analysis, and then store the attributes of the environmental input signal 110 into the system storage 430. In this manner, the system 400 will be able to compare subsequently acquired signals to the saved attributes of the environmental input signal 110 in order to increase the efficiency of the event determination process 425.
  • Such heuristic methods of implementation would provide a long term benefit to the system 400, because there would be a greater probability of less false positives.
  • the system 400 would be able to quickly identify a newly acquired signal as being a product of the event of interest and not among any predefined events from the signal database 424.
  • Embodiments of the present invention can also be configured to store in memory a specific amount of inputted data (e.g., 20 seconds, 30 seconds, etc.) depending on how much data needs to be captured for adequate event analysis, and depending on when the data needs to be captured.
  • a specific amount of inputted data e.g., 20 seconds, 30 seconds, etc.
  • An embodiment of the present technology could be implemented for highway patrol purposes in which a speed detection system is equipped with two data acquisition devices.
  • a first data acquisition device could comprise radar device used to determine the velocity of a vehicle traveling at a certain point on a monitored highway.
  • the system 400 would be configured to trigger a MEMS based acquisition device 220 if the determined velocity exceeds a particular threshold (e.g., 75 miles per hour).
  • the MEMS based acquisition device 220 would then input visual data relating to the vehicle for the next twenty seconds, and the twenty seconds of data would be stored into memory 430 for later analysis.
  • the system 400 in this example could be further configured such that the video triggering 422 or still image triggering 423 processes automatically trigger the storing of the captured data. In this way, the captured video footage could be subsequently scrutinized in order to determine specific information about the speeding vehicle and its driver.
  • temporally expanded data capture and storage would also allow the system 400 to assess background changes such that the system 400 can more quickly and proficiently qualify an event.
  • the system could be configured to capture and store visual and audio data and simultaneously monitor for an acoustic event.
  • the system 400 could analyze 20 seconds of data captured previous or subsequent to the detected event such that there is a higher probability of capturing an image of the perpetrator's face for subsequent identification purposes.
  • the system 400 could analyze 20 seconds of data captured previous or subsequent to the detected event such that there is a higher probability of capturing data that may be utilized by the police to identify the person who fired the shot, such as a vehicle license plate, identifying features of a person of interest (e.g., the perpetrator or a witness), a name being shouted, etc.
  • the system 400 is configured to control an adjustable lighting system located in the vicinity of a monitored environment in order to adjust the quality and usefulness of captured data.
  • the system 400 detects an event, it adjusts the lighting in a monitored environment and captures subsequent visual data.
  • the system 400 can simultaneously obtain, record and analyze visual imaging data intended to obtain more information about an object of interest in the monitored environment (e.g., a perpetrator's facial features). If a different lighting setting is required in order to adjust the quality of the captured data, the system will adjust the lighting in the monitored environment accordingly. New visual data will then be captured and recorded into memory, and this new data will itself be analyzed. The system will continue to adjust the lighting and record new data until quality data has been obtained that may be adequately processed, or until the object of interest is no longer present in the monitored environment.
  • a refined conditioning system 500 for further conditioning an input signal is shown.
  • the acquired data is forwarded to the refined conditioning system 500 where the data is further conditioned such that a refined conditioning process 520 can identify one or more specific attributes associated with an identified event.
  • the bandpass filter 511 could be configured to further condition the signal such that the system 500 can more accurately identify the caliber of firearm that fired the round.
  • the preliminary event processing system 400 of Figure 4 may be coupled to the refined conditioning system 500 of Figure 5 so as to identify more specific information associated with an event.
  • the processing unit 421 forwards the acquired data to a first conditioning stage 510 where a bandpass filter 511 further conditions the data for a specific frequency spectrum.
  • the bandpass filter 511 isolates a specific portion of the inputted data that is of most interest to the system 500, which increases the efficiency of the processing time and the capacity of the system 500 to process subsequent events.
  • the bandpass filter 511 could be configured to isolate the frequencies of the signal that correspond to discharges associated with various handgun rounds (e.g., .38, .357, .40, .45, etc.).
  • the system 500 will then be able to process these isolated frequency characteristics in a more efficient manner, because it will not need to process data that is not of interest to the refined event determination process 520.
  • a signal analysis converter 512 takes the conditioned data and converts it into a format that the system 500 can efficiently and accurately analyze, and that can be easily viewed and mathematically represented for later analysis.
  • the signal analysis converter implements a Fourier transform algorithm such that the system 500 can analyze this data in a frequency domain. Such refined conditioning aids the system 500 to recognize certain patterns in the frequency characteristics of inputted data, which ultimately aids in the refined event determination process 520.
  • the signal analysis converter 512 implements a
  • the system 500 could be implemented to process visual data associated with a captured image of a person's face.
  • the Gabor wavelet transform would provide a means of achieving a more refined image analysis.
  • the implementation of a Gabor wavelet transform would provide the system 500 with a means of mathematically identifying unique instances of action occurring at specific frequencies among distinct points of an analyzed waveform. This is in contrast to many modern Fourier transform algorithms, which are oftentimes limited to simply identifying which frequencies are present in a waveform without a more refined analysis being instituted.
  • a linear discriminate analysis module 513 acquires a waveform of an inputted signal and digitally represents each of its component parts.
  • the linear discriminate analysis module further generates a histogram representation of the entire sequence of such component parts that may then be analyzed by a user.
  • the linear discriminate analysis module generates X number of samples, which can then be analyzed in N number of dimensions, thus creating an Nth-dimensional "trend line.”
  • subsequent samples are generated within a predefined number milliseconds or microseconds. The greater the number of samples and dimensions utilized in the analysis, the greater will be the degree of accuracy that the system 500 can realize in the pattern recognition process.
  • the linear discriminate analysis module 513 could be configured to generate a sample of a gunshot signal every 100 microseconds as opposed to every 10 milliseconds (thus increasing the number of samples by a factor of 100). As a result, the system will have more pertinent data at its disposal during the refined event determination process 520 because the system will have generated a greater number of samples.
  • the system 500 could be further configured to analyze the frequency characteristics both as a function of time and air pressure.
  • An increased number of processing dimensions would enable the system 500 to implement processing algorithms that are more complex, and would provide the refined event determination process 520 with a more comprehensive backdrop with which to conduct its analysis.
  • the event determination process would be able to take into account the effects of air pressure on the discharge of a firearm (for instance, an increased level of air pressure may prove to squelch the sound of a gunshot to a certain degree).
  • the linear discriminate analysis module 513 may be configured to take more or less samples of the waveform depending on the degree of accuracy and amount/speed of processing that a user desires. This provides for a greater degree of extensibility regarding implementation of the system 500 for processing different events under different conditions, in which varying processing speeds may be required.
  • the linear discriminate analysis module 513 obtains trained data 514 to confirm the occurrence of a specific event type.
  • the trained data 514 may be updated to include new information.
  • the system 500 could be configured to communicate with a remote database containing event information not found in the trained data 514. This new information would then be transferred, uploaded, downloaded or copied to the trained data 514 such that the information that is available to the linear discriminate analysis module 513 is updated.
  • the system 500 could be configured to periodically query a remote database to determine if new information is available, and to automatically download such new information to update the trained data 514. This would increase the efficiency with which the system 500 can identify attributes associated with identified events, since the trained data 514 would be comprised of a greater amount of information regarding possible event attributes.
  • the system 500 is configured to communicate with a remote database to determine if new information regarding the identified event is available.
  • the system 500 could be configured to couple to a communication network through which a server accesses one of a plurality of databases, and forwards new information regarding an event attribute to the system 500.
  • the system 500 could be further configured to automatically download new event information when a specific attribute cannot be identified, thus allowing the system 500 to heuristically update its breadth of knowledge regarding the number and type of possible event attributes.
  • the system 500 is configured to communicate with a second event processing system. For instance, if the system 500 is unable to identify a specific event attribute, the system 500 could be configured to automatically forward, through a transmission line or wireless data connection, the conditioned data to the second system, which may be located remotely. Upon receiving the forwarded data, the second system would then process the data and determine if a specific attribute can be identified. If such an attribute is identified, the second event processing system would forward its results to the refined conditioning system 500.
  • the efficiency and efficacy of various embodiments of the present technology may be increased by implementing various heuristic methods of data processing, or by utilizing a plurality of event processing systems or information databases in tandem.
  • the proficiency of the refined event determination process 520 of the refined conditioning system 500 of Figure 5 can be further increased by implementing a partial matrix 531, such as a Fischer partial matrix.
  • This partial matrix 531 utilizes a set of trained data 532 and calculates a specific degree of accuracy regarding identification by the system 500 of an inputted signal as a specific event. For example, once an event has been identified as a gunshot, the partial matrix 531 could be implemented to determine the highest probability that the gunshot was the result of a specific caliber firearm.
  • a user can specify a desired degree of accuracy (e.g., a specific number of standard deviations) that the system 500 must operate within.
  • a desired degree of accuracy e.g., a specific number of standard deviations
  • the system 500 could be configured such that it operates within three standard deviations, which yields a high degree of accuracy regarding the output of the refined event determination process 520, but which saves the system 500 from continued processing iterations that would degrade system performance.
  • a user could decide to settle for 98 % accuracy rather than 99 % accuracy in order to speed up the processing cycle.
  • the system 500 may be configured to operate with an even smaller degree of accuracy. For instance, less accuracy may be desired so as to avoid filtering out a possible event that might actually have occurred, but where the inputted signal was unintentionally distorted or degraded by bugs present in the actual implementation or configuration in the system 500. For instance, a manufacturing flaw in a transmission line that is used to send data between two points in the system 500 might cause the line to have a relatively high level of internal impedance, which could degrade an acquired signal. By operating with a smaller degree of accuracy, the degradation of the acquired signal will not cause the refined event determination process 520 to be fooled into thinking that the acquired signal is unrelated to a specific, predetermined event.
  • the system 500 might eliminate the possibility of a .40 caliber round as a possibility during the refined event determination process 520.
  • the system 500 could be configured to operate with a smaller degree of accuracy such that events relating to the discharge of both .40 and .45 caliber rounds are determined to be event possibilities.
  • the trained data 532 comprises an average of frequency characteristics of similar events that the partial matrix 531 takes into consideration.
  • a portion of the trained data 532 relating to gunshot events could comprise an average of twenty shots fired from each of a plurality of different model firearms, and where each of the fired rounds is of the same caliber, but is fired under different conditions (e.g., during a clear day versus in the middle of a rainstorm).
  • the partial matrix 531 would be able to consider how varying weather conditions affect the sound of a gunshot of a specific caliber round that is fired from a particular firearm of interest.
  • an integrated system 600 is configured to respond once the refined event determination process 520 has taken place.
  • the environmental input signal 110 is assigned an event ID 620 for identification purposes.
  • An alert triggering module 620 then executes one or more predefined response operations that have been assigned to the identified event. For instance, in the illustrated embodiment, the alert triggering module executes an end video operation 621 that causes a specific video feed to terminate; in this way, the system 600 can be configured to execute the end video operation 621 for purposes of implementing a selective monitoring process. In this way, video data is captured only during selected times according to a user's particular needs, and precious system storage 431, 432 is conserved.
  • the alert triggering module generates an output signal 622 that can subsequently be transmitted to a remote receiver.
  • the output signal 622 could be transmitted to either a local or remote alarm system that is used to alert others as to the occurrence of the detected event.
  • the output signal 622 may be transmitted by means of a number of output options. Such output options include, but are not limited to, RS232, RS485, USB, firewire, fiber optic, infrared, AM, FM, PCM, GPS, and similar communication technologies.
  • the system 600 may implement the output signal 622 to communicate such information. For instance, if the system has identified a gunshot as being a detected event, and if the refined event determination process 520 has identified the gunshot as being the result of a firearm firing a .40 caliber cartridge, the system will generate the output signal 622 communicating that a .40 caliber round has been discharged in the monitored environment.
  • the system 600 will simply identify the detected event (e.g., the output signal 622 will be used to communicate that a gunshot was detected, but that the system 600 was unable to identify the specific caliber of the round fired).
  • the output signal 622 communicates one or more possible attributes that might be associated with detected event. For instance, if a gunshot is detected, and if the refined conditioning system 500 is able to determine that either a .40 or .45 caliber round may have been fired, the output signal 622 can be configured to communicate both of these possible event attributes. In this manner, even if a specific attribute of the detected event cannot be identified, a user will still receive valuable information relating to a range of attribute possibilities.
  • the method 700 comprises utilizing a micro-electromechanical (MEMS) based acquisition device is to monitor an environment 710, and receiving a sound signal at the MEMS based acquisition device 720.
  • the method 700 further comprises generating an input signal at the MEMS based acquisition device 730, wherein the input signal comprises an electronic representation of the sound signal, and conditioning the input signal for at least one specific frequency band 740.
  • an input signal received at the MEMS based acquisition device is conditioned within at least one specific frequency band to provide a refined version of the input signal for future analysis.
  • the method of Figure 7 can be expanded so as to include other data acquisition and processing operations, depending on the needs and objectives of a user.
  • the MEMS based acquisition device is powered by means of an electrical power source.
  • This electrical power source may comprise an internal power source, such as a system battery, or an external power source, such as a transmission line that delivers alternating current and that may be accessed through an electrical wall socket.
  • an internal power source e.g., a system battery
  • the method of Figure 7 comprises providing power to the device only during specific periods of time such that the MEMS device is selectively powered up and selectively powered-down to extend the device's battery life.
  • the method of Figure 7 comprises selectively powering the MEMS based acquisition device such that the MEMS device selectively monitors an environment.
  • the method can be further expanded so as to include the step of utilizing the MEMS based acquisition device to monitor an environment for frequencies ranging from 0 kHz to 100 kHz. This would essentially fine tune and configure the MEMS device for broadband monitoring applications. In the case of firearm detection, this latter step could be further configured so as to select a range of frequencies that include gunshot sounds that resonate within at least one frequency band from within the frequencies ranging from 0 kHz to 100 kHz that are monitored by the MEMS based acquisition device.
  • the method of Figure 7 could be expanded so as to include the step of selecting a range of frequencies that includes spray can discharge sounds that resonate within at least one frequency band from within the frequencies ranging from O kHz to 100 kHz monitored by the MEMS based acquisition device.
  • the method of Figure 7 may be utilized for security applications configured to monitor for gunshot sounds and also detect graffiti.
  • the method of Figure 7 may be expanded so as to allow the MEMS based acquisition device to concentrate its efforts on more than one frequency spectrum.
  • the method 800 comprises prequalifying an input signal received from an environmental monitoring device for a specific frequency band 810.
  • the input signal is also compared to a database of reference signals each having an associated event frequency 820.
  • the method 800 further comprises conditioning the input signal to generate a conditioned signal with a refined frequency spectrum 830. For instance, in one embodiment, when comparing the input signal to a database of reference signals 820 results in a match between the input signal and a reference signal from the database, a conditioned signal with a refined frequency spectrum is generated in response to the match.
  • the method 800 comprises utilizing the conditioned signal to identify at least one event attribute corresponding to an event associated with the input signal 840.
  • a corresponding event attribute is selected from a group of event types consisting of a specific calibers of gunshots, types of firecrackers, cars backfiring, aerosol spray can discharges, pipeline leaks, spoken words, faces associated with specific people, images of guns, images of knives, unique vehicle license plates, or toxic chemicals.
  • the method 800 is configured to identify highly specific event information with respect to past event detection processes.
  • the method 800 further comprises outputting an identified event attribute. For instance, an output signal could be generated that identifies at least one event attribute corresponding to an event associated with an input signal, and this output signal could be transmitted to a receiver. The output signal could then be obtained from the receiver and analyzed in order to obtain information about an event associated with the input signal.
  • the method 800 may be expanded such that one or more specific types of input signals may be processed.
  • the method could include processing an input signal that is associated with an input selected from a group of possible input signal receivers consisting of electronic, magnetic, electromagnetic audio, visual, olfactory, taste-sensory, temperature, pressure, and radioactive data receivers.
  • the environmental monitoring device is utilized to detect a pungent odor in a monitored environment, and the input signal that is received from the environmental monitoring device comprises information corresponding to the detected olfactory data.
  • the method 800 of Figure 8 can be further expanded so as to include other data acquisition and processing operations, depending on the needs and objectives of a user.
  • the method 800 comprises initiating a second environmental monitoring device when the input signal is prequalified, and receiving a second input signal from the second environmental monitoring device.
  • the use of two or more environmental monitoring devices would increase the physical range within an environment in which data may be captured. Indeed, a first input signal and a second input signal may be associated with different environmental data types in order to further increase the scope of data capture and analysis so as to include a range of processed data types corresponding to a detected event.
  • prequalifying 810 the input signal comprises the implementation of a frequency check to determine whether the input signal oscillates within a specific frequency spectrum.
  • the method 800 comprises prequalifying one or more other inputs along with the input signal. Indeed, the prequalification of an input signal could be dependent on the successful prequalification of one or more other inputs in order to implement a multi-input prequalification analysis. Thus, it is understood that the prequalification stage 810 of the method 800 of event detection may be implemented in different ways to achieve different goals.
  • the method 800 may be further expanded such that acquired visual data is processed.
  • the method 800 comprises implementing a machine vision algorithm when the input signal is associated with visual data.
  • the machine vision algorithm could be configured to analyze an image feature associated with the visual data.
  • the method 800 comprises identifying an image feature based on visual traits exhibited by the feature.
  • a still image triggered event is implemented that processes data associated with acquired still images.
  • the still image triggered event could be utilized to analyze physical attributes associated with a foreground image located in a captured still image, or could even be used to enhance an attribute associated with an object in an image (e.g., sharpness, brightness, color contrast, size) such that the object in the image can be more easily analyzed.
  • the method comprises utilizing a video triggered event to process data associated with detected motion.
  • the video triggered event could be utilized to analyze movement of a foreground object present in a captured video clip relative to other foreground objects or a stationary background.
  • the video triggered event is used to identify characteristics of an object in a captured video clip so that the object can be identified.
  • the method 800 of event detection may be further expanded to include automatically executing a predefined action in response to an identified event. For instance, in one embodiment, if either the still image triggered or video triggered events succeed in identifying an object of interest in an acquired still image or captured video footage, the method 800 could comprise automatically notifying a predefined person of such identification. Implementation of this embodiment would be valuable for a variety of applications, such as homeland security. For example, the method 800 could be instituted at an airport wherein still image triggered and video triggered events are used to analyze facial features of persons present in a particular airport terminal. Upon identifying a person of interest, the method 800 would further comprise automatically notifying airport security, local police, and federal authorities of the presence of such an individual.
  • the method 800 of Figure 8 may also be expanded to include storing data for various purposes.
  • processed data is stored in a storage unit such that the processed data may be subsequently retrieved and further processed.
  • a hard disk drive HDD
  • HDD hard disk drive
  • HGA head gimbal assembly
  • the read/write head may then magnetically read the data from the magnetic storage medium such that the data may be later accessed and further processed at a subsequent point in time.
  • random access memory is used to electronically store the data by means of arrays of electronic capacitors that are configured to acquire an electronic charge, wherein the charging of the capacitor arrays corresponds to a digital representation of the acquired data.
  • RAM random access memory
  • the aforementioned examples are merely exemplary of different storage units that may be implemented pursuant to various embodiments of the present technology.
  • Other suitable storage units may also be utilized to store data such that it may be later accessed and processed.
  • a portable flash drive may be used to store data, and the flash drive could be physically transported from a first computing system to a second computing system, wherein both computing systems are capable of accessing data stored on the drive.
  • the method 800 could comprise automatically routing data to a specific storage unit having the capacity to store such data. For instance, in one embodiment, it is first decided that specific data should be stored in a storage unit. The method 800 of the present embodiment would further comprise analyzing the amount of data that needs to be stored, and checking the storage capacity of two or more storage units. Next, a specific storage unit having the requisite degree of storage capacity would be identified, and the data would be automatically routed to the unit, where it would be stored such that the data could be subsequently accessed and analyzed.
  • the method 800 comprises utilizing a set of trained data to confirm the occurrence of a specific event type.
  • the trained data may include a set of identifying factors related to a plurality of possible event attributes. This trained data could then be accessed such that the set of identifying factors could be analyzed such that a specific event attribute associated with an event of interest may be identified and further analyzed.
  • the utilization of a set of trained data could be used to obtain a greater amount of information regarding possible event attributes.
  • the method 800 further comprises implementation of an algorithm that arranges the trained data such that specific identifying factors and related information are arranged according to characteristic attributes associated with these factors.
  • a filtering algorithm is used to identify a range of identifying factors among the set of trained data, wherein the factors within the targeted range all share one or more characteristic attributes. In this way, the trained data may be filtered according to an attribute associated with an identified event, and the trained data may be utilized to obtain more information regarding a specific event attribute of interest.
  • the method 800 may further include an accuracy assessment regarding an identified attribute.
  • the method comprises calculating a specific degree of accuracy associated with the identification of a particular event attribute with respect to an input signal received from an environmental monitoring device.
  • the method 800 could comprise analyzing a group of identifying factors among a set of trained data, wherein the group of identifying factors relates to a plurality of possible event attributes, and deciding that a single event attribute cannot be identified with absolute certainty.
  • two or more event attributes that may possibly correspond to an event associated with a received input signal may be selected, and each of these selected attributes may be further analyzed and assigned a specific degree of accuracy regarding their possible associations with the input signal.
  • a characterization may be carried out by comparing and contrasting characteristic attributes associated with each possible event attribute and the received input signal, and utilizing the results of this analysis to generate and assign a statistical probability tag to each possible event attribute with respect to the input signal.
  • the method 900 comprises utilizing a micro-electromechanical (MEMS) based acquisition device to monitor an environment 910, receiving an environmental input signal at the MEMS based acquisition device 920, and generating an electronic input signal at the MEMS based acquisition device, wherein the electronic input signal corresponds to the environmental input signal 930.
  • MEMS micro-electromechanical
  • the method 900 includes sensing mechanical vibrations in an ambient environment and creates an electrical signal having characteristic electronic amplitudes and frequencies that mirror the mechanical amplitudes and frequencies of the sensed vibrations.
  • the method 900 of Figure 9 further comprises prequalifying the electronic input signal for a specific frequency band 940 and comparing the electronic input signal to a database of reference signals 950.
  • each reference signal in the database could have an associated event frequency range, and these event frequency ranges could be compared with an electronic frequency range of the prequalified electronic input signal in order to identify an event associated with the environmental input signal.
  • the reference signals in the database could even be filtered prior to being compared with the prequalified input signal in order to shorten the requisite duration of time required to adequately compare the electronic input signal to the database of reference signals 950. In this way, only a select group reference signals from the database would need to be individually compared to the electronic input signal, which would serve to increase the efficiency of the method 900.
  • the method 900 further comprises conditioning the electronic input signal to generate a conditioned signal with a refined frequency spectrum 960, and utilizing the conditioned signal to identify at least one event attribute corresponding to an event associated with the electronic input signal 970. For instance, when the comparison between the electronic input signal and the database of reference signals results in a match, a conditioned signal with an associated refined frequency spectrum could be generated, and this conditioned signal could be compared to a specific group of possible event attributes having characteristic frequencies within the refined frequency spectrum of the conditioned signal. Then, one or more event attributes are identified as being associated to the electronic input signal based on a correlation between their respective characteristic frequencies and a characteristic frequency of the input signal.
  • Another embodiment of the present invention includes communicating with a remote database comprising information associated with a plurality of event attributes, and obtaining new information associated with a specific event attribute. In this manner, locally accessible data may be periodically updated such that a more thorough analysis may be performed.
  • the method 900 also includes outputting one or more identified event attributes so that another entity may be informed of the specific event attributes that were identified during execution of the method 900.
  • an output signal could be generated, wherein the output signal identifies at least one event attribute that has been identified.
  • This output signal could then be transmitted to a remote receiver coupled to a remotely located communication system.
  • the communication system could then be utilized to communicate the contents of the output signal to one or more interested parties.
  • the method 900 comprises wirelessly transmitting the generated output signal to a remote receiver.
  • a remote receiver For instance, if an analog output signal is generated, the signal could be transmitted using AM or FM communication technologies in which the output signal is modulated with a carrier signal, and then electromagnetically communicated from a transmitter to a remote receiver. Once the modulated signal has been received, a predefined demodulation algorithm would be used to reconstruct the original output signal, and the contents of the output signal could then be remotely analyzed.
  • a remote transceiver is utilized to receive the modulated output signal from the transmitter, and the signal is then remotely routed to another receiver. This implementation allows for long range communication of the output signal over a relatively larger area.
  • the method 900 comprises implementing a pulse-code modulation (PCM) algorithm to create a digital representation of an analog output signal that identifies one or more event attributes associated with an electronic input signal.
  • the analog output signal is sampled at uniform intervals, and theses samples are then quantized according to a discrete set of integer values.
  • the quantized samples of the output signal are translated into a digital format that is communicated to a remote receiver, at which point a remotely located communication system coupled to the remote receiver can reconstruct the analog output signal and analyze its contents.
  • PCM pulse-code modulation
  • the aforementioned modulation algorithms are only examples of how to implement principles of the present technology pursuant to various specific embodiments. Indeed, a wide range of communication technologies may be utilized to transmit information pertaining to an identified event attribute.
  • the method 900 could further comprise wirelessly transmitting an output signal to a remote receiver by implementing a communication technology selected from a group of communication technologies consisting of AM, FM, PCM, GPS, RS232, RS485, USB, firewire, infrared and fiber optic communication technologies.
  • the present technology provides a system and method of advanced event detection that may be used to specifically identify a range of events occurring in a within a monitored environment.
  • the present technology provides a system and method for conditioning a signal received at a
  • MEMS based acquisition device implemented in various embodiments of the present invention to be configured to scan for a specific type of event selected from a wide range of events that are capable of being detected, and a disclosed event detection process could then be implemented to identify the detected event.
  • the present technology also provides a system and method for prequalifying a signal for a specific frequency range, as well as an advanced system and method of refined conditioning. Therefore, a person skilled in the art could implement a combination of embodiments in which a specific type of input is succinctly processed and analyzed in order to yield a more refined analysis with respect to past technologies.
  • a specific type of input is succinctly processed and analyzed in order to yield a more refined analysis with respect to past technologies.
  • a MEMS based acquisition device could be configured to monitor for a range of chemicals, and then generate an input signal that communicates specific attributes associated with a detected chemical.
  • the prequalification and refined conditioning processes could then be utilized to implement a refined analysis of these specific attributes in order to determine whether the detected chemical is toxic to humans.
  • one embodiment of the present technology could comprise a mobile gunshot detection unit that may be mounted in a police cruiser.
  • the law enforcement officer can check the mobile gunshot detection unit in order to make sure that the sound was in fact a gunshot, rather than a confusingly similar sound (e.g., a car backfiring).
  • a confusingly similar sound e.g., a car backfiring
  • the officer can contact the police dispatch unit and report the event.
  • application of the embodiment would translate into fewer false alarms, which has the practical application of preserving precious police department resources for genuine emergencies.
  • an embodiment of the present technology could be implemented so as to allow a soldier in a theater of war to not only be sure that a gunshot was fired, but to also pinpoint the precise caliber of the weapon that fired the round. This will enable the soldier to make a more informed decision regarding how to react to the gunshot (e.g., should he simply alert his squad, or should he radio in for an even greater degree of reinforcement).
  • an array of MEMS based acquisition devices are utilized in a pipeline leak detection system.
  • a MEMS device could be installed at various points along an intricate network of pipeline.
  • the MEMS devices could each be configured to monitor for a specific frequency spectrum, such as a frequency range associated with sounds resulting from pipeline leaks.
  • the pipeline leak detection system Upon detecting the sound of a leak in a pipeline, the pipeline leak detection system would communicate to a system user, such as by sending a wireless or hard line transmission, the location of the leak. In this way, engineers and technicians having the arduous task of finding leaks in a large pipeline network would be able to more quickly recognize a leak, pinpoint its location and remedy the problem.
  • the present technology is operational with numerous other general-purpose or special-purpose computing system environments or configurations.
  • Examples of well known computing systems, environments, and configurations that may be suitable for use with the present technology include, but are not limited to, personal computers, server computers, hand-held or laptop devices, multiprocessor systems, microprocessor- based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
  • the present technology may be described in the general context of computer- executable instructions, such as program modules, being executed by a computer.
  • program modules include routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types.
  • the present technology may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network.
  • program modules may be located in both local and remote computer-storage media including memory- storage devices.

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Abstract

L'invention concerne un système et un procédé pour surveiller une bande de fréquence spécifiée. La technologie utilise initialement un dispositif d'acquisition à base de système microélectromécanique (« MEMS ») pour surveiller un environnement. Le dispositif MEMS reçoit un signal de l'environnement, et génère un signal d'entrée incluant une représentation électronique du signal environnemental reçu. Ce signal d'entrée est ensuite conditionné pour au moins une bande de fréquence. Des modes de réalisation de l'invention permettent ensuite de comparer le signal conditionné à divers éléments prédéfinis afin de déterminer l'origine du signal.
PCT/US2009/030330 2008-01-11 2009-01-07 Système et procédé pour conditionner un signal reçu au niveau d'un dispositif d'acquisition à base de mems WO2009089281A1 (fr)

Applications Claiming Priority (6)

Application Number Priority Date Filing Date Title
US12/008,491 US20100283849A1 (en) 2008-01-11 2008-01-11 System and method of environmental monitoring and event detection
US12/008,551 US8050413B2 (en) 2008-01-11 2008-01-11 System and method for conditioning a signal received at a MEMS based acquisition device
US12/008,491 2008-01-11
US12/008,492 US20090182524A1 (en) 2008-01-11 2008-01-11 System and method of event detection
US12/008,551 2008-01-11
US12/008,492 2008-01-11

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