US 9235259

A concise summary of US Patent 9,235,259 is as follows:

Title: Method for detecting audio ticks in a noisy environment

Assignee: The current assignee of record is K Mizra LLC. The original assignee was Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek TNO.

Inventors: Mark van Staalduinen, Victor Bastiaan Klos, and Peter Jan Otto Doets.

Filing Date: November 26, 2010.

Issue Date: January 12, 2016.

Abstract: The patent describes a method for detecting short "tick" sounds in a noisy audio environment. The process involves a two-step approach. First, a "coarse" detection processor analyzes the audio signal to identify potential ticks. If a likely tick is found, a "fine" detection processor is enabled to perform a more thorough analysis to confirm the tick. The coarse step involves buffering audio samples, determining their local range, and comparing changes in this range to a threshold. The fine step involves more computationally intensive processing, such as a Fast Fourier Transform, to compare the audio signal's characteristics with a pre-trained "fingerprint" of a tick. This two-stage method aims to be efficient in terms of processing power and battery use, making it suitable for mobile devices.

Plain-Language Overview of Independent Claims:

Independent Claim 1: This claim outlines a method for detecting a "tick" sound on a specific device. The method first uses a computationally simple "coarse" processor to listen for any sound that might be a tick. Only when this coarse processor identifies a potential tick does it activate a more sophisticated "fine" processor. This fine processor then compares the sound to a pre-recorded set of sound properties that are unique to that specific device to confirm if it was a genuine tick.

Independent Claim 9: This claim describes a system, rather than a method, for detecting ticks. The system includes both a coarse tick detector and a fine tick detector. Similar to the method in claim 1, the coarse detector first identifies a likely tick. Only then does it enable the fine detector to perform a more detailed analysis by comparing the sound against a set of properties characteristic of the device to confirm the tick.

Independent Claim 20: This claim details another method for detecting ticks that also uses a two-step (coarse then fine) process. A key aspect of this claim is how the fine detection process suppresses background noise. It does this by taking Fourier transforms of the audio in different time windows (buffers), calculating the differences in energy between frequency components of these successive windows, and then comparing these differences to a pre-trained reference set.

Independent Claim 22: This claim describes a system that implements the method outlined in claim 20. The system has a coarse processor to first flag a potential tick and a fine processor that is then enabled. This fine processor is configured to reduce the influence of background noise by computing Fourier transforms of the audio, determining the energy differences in various frequencies between consecutive time segments, and comparing these differences to a stored reference set to confirm the tick.

It should be noted that K.Mizra LLC is a patent licensing company and has been involved in patent litigation. Recent reports from April 2026 indicate that prior art has been identified against U.S. Patent 9,235,259. I do not have access to CAFC dockets to confirm any ongoing legal proceedings.

Litigation History of US Patent 9,235,259

As of May 10, 2026, research indicates at least one litigation case involving US Patent 9,235,259. The patent is currently assigned to K. Mizra LLC, a patent licensing company that has been involved in numerous patent assertion campaigns against various technology companies.

A case was filed by a previous assignee, DataServe Technologies LLC, which was subsequently assigned to K. Mizra LLC.

Case Details:

• Plaintiff: DataServe Technologies LLC (initial), K.Mizra LLC (current)
• Defendant: General Motors LLC
• Jurisdiction: U.S. District Court for the Western District of Texas
• Case Number: 1:21-cv-00316
• Filing Date: April 5, 2021
• Status: The case appears to be ongoing. A motion by General Motors to transfer the venue to the Eastern District of Michigan was denied in November 2022, and the case was proceeding to discovery. I do not have access to PACER or other federal court dockets to confirm the most current status of this specific case.

It is worth noting that General Motors has been a frequent target of patent infringement lawsuits from various entities concerning technologies used in its vehicles, including its OnStar and Super Cruise systems. Additionally, K. Mizra LLC has asserted other patents from its portfolio against a wide range of defendants, including major telecommunications and technology companies.

Proceedings overview

As of May 29, 2026, there are no AIA trial proceedings on file for US Patent 9,235,259. This means the patent has not been subjected to Inter Partes Review (IPR), Post-Grant Review (PGR), or Covered Business Method (CBM) proceedings at the USPTO's Patent Trial and Appeal Board (PTAB). This lack of PTAB activity suggests that all claims of the patent remain untested and are currently presumed valid. For a defendant, this means there are no prior PTAB decisions to leverage for invalidity arguments, and any defensive posture would need to initiate a new PTAB challenge or rely on district court litigation.

Strategic summary

Currently, all claims of US 9,235,259 are untested by PTAB proceedings. No claims have been canceled or sustained through an AIA trial. Consequently, there is no estoppel landscape established under § 315(e)(2), meaning a potential petitioner would not be barred from raising any prior-art grounds that they raised or reasonably could have raised in a prior IPR. There are no pattern signals of multiple IPR filings by the same petitioner or aggressive PTAB appeals by the patent owner, nor is a defensive aggregator involved in any PTAB proceedings for this patent.

Recommended next steps

Since no PTAB activity exists for US Patent 9,235,259, a defendant facing assertion of this patent should consider initiating an AIA trial proceeding (e.g., IPR) if viable prior art can be identified. The absence of prior PTAB challenges might indicate that potential petitioners have not yet found sufficiently strong prior art to warrant a challenge, or it could simply mean the patent has not been asserted widely enough to attract such challenges.

Inventors

• Mark van Staalduinen: Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek TNO
• Victor Bastiaan Klos: Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek TNO
• Peter Jan Otto Doets: Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek TNO

No unusual patterns were observed regarding inventors departing the original assignee within 12 months of filing.

Original assignee

The original assignee was Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek TNO (TNO). TNO is a Dutch independent research organization that connects people and knowledge to create innovations. Based on publicly available information, TNO's primary line of business is contract research and development across various sectors, not the direct shipment of consumer products embodying the claims. TNO is currently an operating entity.

Assignment timeline

The USPTO Assignment Center (https://assignmentcenter.uspto.gov/) was searched for patent number 9235259. The following assignment records were found:

• 2012-06-14 to 2012-06-22 (executed) / recorded 2012-07-03 — Reel 028482/0713

  • Conveyance: ASSIGNMENT OF ASSIGNORS INTEREST
  • Assignor: VAN STAALDUINEN, MARK; KLOS, VICTOR BASTIAAN; DOETS, PETER JAN OTTO
  • Assignee: NEDERLANDSE ORGANISATIE VOOR TOEGEPAST-NATUURWETENSCHAPPELIJK ONDERZOEK TNO
  • Correspondent: MCDONNELL BOEHNEN HULBERT & BERGHOFF LLP, ATTN: PATENT DOCKET, 300 SOUTH WACKER DRIVE SUITE 3200, CHICAGO, IL 60606.
  • Context: Internal transfer of inventor rights to the original assignee.

• 2020-02-25 (executed) / recorded 2020-03-05 — Reel 052113/0431

  • Conveyance: ASSIGNMENT OF ASSIGNORS INTEREST
  • Assignor: NEDERLANDSE ORGANISATIE VOOR TOEGEPAST-NATUURWETENSCHAPPELIJK ONDERZOEK (TNO)
  • Assignee: DATASERVE TECHNOLOGIES LLC
  • Correspondent: WOLF, GREENFIELD & SACKS, P.C., 600 ATLANTIC AVENUE, BOSTON, MA 02210.
  • Context: Fire-sale from original research organization to an assertion entity.

• 2020-07-22 (executed) / recorded 2020-08-21 — Reel 053579/0590

  • Conveyance: ASSIGNMENT OF ASSIGNORS INTEREST
  • Assignor: DATASERVE TECHNOLOGIES LLC
  • Assignee: K.MIZRA LLC
  • Correspondent: WOLF, GREENFIELD & SACKS, P.C., 600 ATLANTIC AVENUE, BOSTON, MA 02210. This correspondent recurs in this chain.
  • Context: Transfer-to-asserter between two licensing entities.

Timeline diagram

timeline
    title Ownership of US 9235259
    2010 : Filed by TNO
    2012 : Inventors assign to TNO
    2016 : Patent issued
    2020 : Assigned to DataServe Tech LLC
         : Assigned to K.Mizra LLC
    2021 : First infringement suit filed

NPE / troll-pattern signals

1. Shell-entity transfer — present

   • 2020-02-25 (executed) / recorded 2020-03-05 (Reel 052113/0431): Transfer from Nederlandse Organisatie voor Toegepast-Natuurwetenschappelijk Onderzoek (TNO) to DATASERVE TECHNOLOGIES LLC. TNO is a research organization, not a product manufacturer. DataServe Technologies LLC is recognized as a patent assertion entity, having no known products.
   • 2020-07-22 (executed) / recorded 2020-08-21 (Reel 053579/0590): Transfer from DATASERVE TECHNOLOGIES LLC to K.MIZRA LLC. K.MIZRA LLC is a known patent licensing company (NPE) and does not manufacture products.

2. Known asserter in the chain — present

   • 2020-02-25 (executed) / recorded 2020-03-05 (Reel 052113/0431): DATASERVE TECHNOLOGIES LLC is an assignee.
   • 2020-07-22 (executed) / recorded 2020-08-21 (Reel 053579/0590): K.MIZRA LLC is the current assignee and is identified as a patent licensing company.

3. Repeat correspondent across the chain — present

   • WOLF, GREENFIELD & SACKS, P.C. appears as the correspondent for both the 2020-03-05 recording (Reel 052113/0431) and the 2020-08-21 recording (Reel 053579/0590). This indicates continuity in legal representation across transfers between assertion entities.

4. Cascading transfers — present

   • The assignments from TNO to DATASERVE TECHNOLOGIES LLC (recorded 2020-03-05) and then from DATASERVE TECHNOLOGIES LLC to K.MIZRA LLC (recorded 2020-08-21) occurred within a span of less than six months. Both transfers involve shell entities.

5. Pre-litigation transfer — present

   • The patent was assigned to K.MIZRA LLC on 2020-07-22 (executed) / recorded 2020-08-21 (Reel 053579/0590). The first infringement suit, DataServe Technologies LLC v. General Motors LLC, case number 1:21-cv-00316, was filed on April 5, 2021, which is within 8 months of the final transfer to K.Mizra LLC. This suggests the chain was arranged to enable assertion.

6. Bankruptcy fire-sale — not present

   • No evidence suggests TNO filed for bankruptcy. The transfer appears to be a direct sale of the patent.

7. Privateering — unclear

   • There is no readily available public information (e.g., SEC filings or specific reporting from RPX/EFF) to confirm if TNO transferred the patent to DataServe Technologies LLC or K.Mizra LLC with the intent for them to assert on TNO's behalf against competitors.

8. Defensive aggregator (anti-NPE) — not present

   • The current assignee, K.MIZRA LLC, is a known patent asserter, not a defensive aggregator.

Verdict

NPE — high confidence

The assignment chain for US Patent 9,235,259 exhibits multiple strong signals indicative of patent assertion by a Non-Practicing Entity. Specifically, the patent moved from a research organization (TNO) to two successive shell entities (DataServe Technologies LLC and K.Mizra LLC) within a short period in 2020 (Reel 052113/0431 and Reel 053579/0590). K.Mizra LLC is a known asserter, and the transfers occurred shortly before litigation commenced, with the same correspondent firm handling multiple transfers.

USPTO Assignment Center Search for US9235259

Prior Art Analysis for US Patent 9,235,259

This analysis examines the prior art cited during the prosecution of US Patent 9,235,259. The following references were considered by the USPTO examiner and are listed in the patent's file wrapper. Each entry details the reference, its relevance, and a preliminary analysis of which claims it might anticipate.

The primary innovation claimed in US 9,235,259 is the two-step, coarse-to-fine method for detecting a specific audio "tick." This method conserves computational resources by only engaging the more intensive "fine" processing after a "coarse" analysis flags a potential event. The fine detection is further distinguished by its use of a device-specific, pre-trained set of reference properties or "fingerprint" to confirm the tick.

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Cited Prior Art References

Based on the patent's "Citations" list, the following prior art was considered.

1. US20030132950A1 - Detecting, classifying, and interpreting input events based on stimuli in multiple sensory domains

• Publication Date: July 17, 2003
• Filing Date: November 27, 2001
• Assignee: Fahri Surucu
• Description: This application describes a system for interpreting user input events on a device by using multiple sensors, such as acoustic and motion sensors. It discloses detecting a "tap" on a device's housing and using the acoustic signature of that tap as an input command. The system can learn and recognize different types of taps based on their acoustic characteristics.
• Potential Anticipation: This reference appears relevant to the general concept of using an acoustic signature from a tap as an input. It discloses detecting a tap and analyzing its acoustic properties. It could potentially anticipate the broader concepts within Claim 1 and Claim 9, which cover detecting a tick on a device and using its characteristics for identification. However, '259 distinguishes itself with its specific two-step "coarse-to-fine" processing architecture designed to save power, which is not explicitly detailed in this reference.

2. EP1978508A1 - Beat extraction device and beat extraction method

• Publication Date: October 8, 2008
• Filing Date: January 25, 2006
• Assignee: Sony Corporation
• Description: This document, which is also discussed in the background section of the '259 patent itself, discloses a method for detecting musical beats in an audio file. It proposes detecting initial "beat positions from large instantaneous peaks in the time-series waveform" (a coarse-like step) and then performing a more detailed analysis on a spectrogram using an FFT to refine the beat timing.
• Potential Anticipation: This reference is highly relevant. The patentee of '259 acknowledges this reference in the specification, attempting to distinguish it by arguing that it applies to musical rhythms and not singular, aperiodic "ticks" for device pairing. However, the described method of a coarse peak detection followed by a more detailed FFT-based analysis of the spectrogram bears a strong resemblance to the process in Claim 1, 5, 9, 20, and 22. The core method of a two-stage analysis is present. An argument for anticipation could be made that applying this known audio analysis technique to a "tick" instead of a "beat" would have been obvious to a person skilled in the art.

3. US20090153342A1 - Interacting with devices based on physical device-to-device contact

• Publication Date: June 18, 2009
• Filing Date: December 12, 2007
• Assignee: Sony Ericsson Mobile Communications AB
• Description: This application discloses a method where physical contact or a "tap" between two devices initiates an action or communication. The system detects the tap using sensors, which can include a microphone to detect the sound of the contact. The characteristics of the tap (e.g., sound, vibration) can be analyzed to trigger a specific function.
• Potential Anticipation: This reference establishes the context of "tap-to-pair" or "tap-to-interact." It discloses detecting a tap sound and using it to trigger an event, which is foundational to the use case described in the '259 patent. It could be seen as anticipating the general framework of Claim 2 and Claim 14, which describe using the detected tick for pairing mobile devices. The novelty of '259 rests on how the tick is detected (the coarse-to-fine method), not the act of using a tick for pairing itself.

4. EP2018032A1 - Identification of proximate mobile devices

• Publication Date: January 21, 2009
• Filing Date: July 20, 2007
• Assignee: Nederlandse Organisatie voor Toegepast-Natuurwetenschappelijk Onderzoek TNO (the original assignee of '259)
• Description: This application, from the same original assignee, describes a method for identifying proximate devices by having them both detect a common, externally generated audio event (like a hand clap or a tap). The devices then compare characteristics of the detected sound to confirm they heard the same event, thereby establishing their proximity and enabling pairing. This is the core concept behind the application mentioned in the '259 patent's background section (WO 2009/014438).
• Potential Anticipation: This reference solidifies the problem the '259 patent aims to solve. It describes the overall system of using a common audio event for pairing but does not specify the power-saving, two-step coarse-to-fine detection method. Therefore, it provides context but is unlikely to anticipate the specific method claims (e.g., Claims 1, 4, 5, 20) which detail the two-processor architecture and signal processing steps.

5. WO2006094739A1 - Communication terminal with a tap sound detecting circuit

• Publication Date: September 14, 2006
• Filing Date: March 7, 2005
• Assignee: Sony Ericsson Mobile Communications AB
• Description: This application describes a mobile device equipped with a circuit specifically for detecting tap sounds on its casing. It discusses using a microphone to capture the sound and a processing unit to distinguish tap sounds from other ambient noises.
• Potential Anticipation: This reference further supports the general idea of detecting a tap on a device using a microphone and processing the signal. It speaks to the general concept of Claim 1 and Claim 9. However, like other references, its strength lies in establishing the concept of tap detection rather than disclosing the specific two-stage, computationally efficient method claimed in '259. The novelty of '259 is in the implementation details designed for low-power operation on mobile devices.

Obviousness Analysis of US Patent 9,235,259 under 35 U.S.C. § 103

This analysis evaluates whether the claims of US Patent 9,235,259 would have been obvious to a Person Having Ordinary Skill in the Art (PHOSITA) at the time of the invention. Under 35 U.S.C. § 103, an invention is unpatentable if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains.

A PHOSITA in this context would be an engineer or computer scientist with experience in digital signal processing for embedded or mobile systems, particularly with knowledge of audio processing techniques and power management for resource-constrained devices.

The central claims of US 9,235,259 revolve around a two-step "coarse-to-fine" method for detecting an audio "tick." A computationally inexpensive coarse processor identifies a potential tick, which then triggers a more resource-intensive fine processor to confirm the event, often by comparing it to a pre-trained, device-specific acoustic fingerprint. This approach is explicitly designed to conserve processing power and battery life on mobile devices.

Based on the provided prior art, a strong case for obviousness can be constructed by combining several references.

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Primary Combination of References

A compelling argument for obviousness arises from the combination of EP1978508A1 (Sony) and US20090153342A1 (Sony Ericsson).

• EP1978508A1 (Sony) teaches the core signal processing method claimed in '259. The Sony reference discloses a two-stage method for detecting musical beats:

  1. A coarse step that detects "large instantaneous peaks in the time-series waveform."
  2. A fine step that performs a more detailed analysis on a spectrogram using an FFT (Fast Fourier Transform) to accurately determine the beat position.

  This is, in essence, the "coarse-to-fine" processing architecture claimed in '259. The patentee's attempt to distinguish this by limiting its application to "musical rhythm" is a weak argument. A "tick" from a device tap is simply a singular, aperiodic impulsive sound event, functionally equivalent to a single "beat" from a drum hit described in the Sony reference. A PHOSITA would readily recognize that the same signal processing technique used to identify a beat could be applied to identify a tick.

• US20090153342A1 (Sony Ericsson) provides the clear motivation for this application. It describes the problem domain and context: using a physical "tap" between devices to initiate communication or pairing ("tap-to-pair"). This reference establishes the goal of reliably detecting a tap sound on a mobile device for a specific function.

Motivation to Combine:

A PHOSITA tasked with implementing the "tap-to-pair" functionality described in Sony Ericsson ('342) on a battery-powered mobile device would immediately confront the dual challenges of detection accuracy and power consumption, the very problems the '259 patent claims to solve. When seeking an efficient method for detecting a short, impulsive audio event (the tap), the PHOSITA would look to known signal processing techniques. The coarse-to-fine method disclosed in Sony ('508) presents a direct and known solution for efficiently processing such audio events.

The motivation to combine these references is therefore strong and direct: to apply a known, computationally efficient audio event detection method (from Sony '508) to solve the specific problem of tap detection for device interaction (from Sony Ericsson '342). This combination would have rendered the core method of Claims 1, 5, 20, and 22 obvious, as it would have been a straightforward application of a known technique in an analogous field with a predictable result.

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Secondary Combination and Device-Specific "Fingerprint"

An alternative argument can be made by combining US20030132950A1 (Surucu) with EP1978508A1 (Sony).

• US20030132950A1 (Surucu) teaches using the specific acoustic signature of a tap on a device's housing as a form of user input. Crucially, it discloses that the system can learn and recognize different types of taps based on their acoustic characteristics. This directly teaches the concept of training a system to recognize a specific acoustic event tied to the device itself.

• EP1978508A1 (Sony), as before, provides the efficient two-stage processing architecture.

Motivation to Combine:

A PHOSITA starting with the tap-input system from Surucu ('950) and seeking to improve its efficiency for a mobile device would be motivated to find a less computationally demanding processing method. The coarse-to-fine method from Sony ('508) provides an obvious path to achieving this efficiency.

Furthermore, this combination renders the "device-specific" and "previously trained" limitations of Claim 1 and others obvious. Surucu teaches training a system on the acoustic characteristics of a tap. A PHOSITA would understand that the acoustic response of a physical tap is inherently "characteristic for the device" due to the device's unique physical construction, materials, and microphone placement. Therefore, combining Surucu's concept of a trainable recognizer with Sony's efficient detection algorithm would lead directly to a system that uses a coarse-to-fine method to compare an incoming tap sound against a "previously trained set of reference properties that are characteristic for the device." There is no inventive step in recognizing that a learned tap signature on a device is, by its nature, specific to that device.

Conclusion

The independent claims of US Patent 9,235,259 appear to be obvious in light of the cited prior art. The core inventive concept—a two-stage, coarse-to-fine processing method to save power—is directly taught by EP1978508A1 for the analogous purpose of detecting audio impulses. The motivation to apply this known method to the problem of "tap-to-pair" is clearly provided by references like US20090153342A1. Finally, the concept of using a trained, device-specific acoustic signature is taught by US20030132950A1. A person having ordinary skill in the art would have been motivated to combine these teachings to arrive at the claimed invention with a reasonable expectation of success.

Analysis of Patent Term, Adjustments, and Family for US Patent 9,235,259

As of May 10, 2026, the following details pertain to the term and lineage of US Patent 9,235,259.

Patent Term and Expiration

• Filing Date: The application for this patent, US 13/512,139, was filed on November 26, 2010.
• Standard Term: Utility patents filed after June 8, 1995, have a standard term of 20 years from the earliest non-provisional filing date. For this patent, that date is November 26, 2010.
• Patent Term Adjustment (PTA): The United States Patent and Trademark Office (USPTO) grants Patent Term Adjustments to compensate for certain administrative delays during the patent prosecution process. For US 9,235,259, a total of 1,099 days of PTA was granted.
  • This adjustment was calculated based on USPTO processing delays, from which any applicant-induced delays were subtracted.
• Projected Expiration Date: The standard 20-year term from the filing date would end on November 26, 2030. Adding the 1,099 days of PTA results in a projected expiration date of November 30, 2032. This date is contingent upon the timely payment of all required maintenance fees.
• Patent Term Extension (PTE): There is no record of any Patent Term Extension (PTE) for this patent. PTE is typically granted for delays caused by regulatory review processes (e.g., by the FDA) and is not applicable in this case.

Continuity and Application History

• Continuation or Divisional Applications: There are no records indicating that US 9,235,259 is a continuation, divisional, or continuation-in-part of any prior US application. Likewise, no continuation or divisional applications have been filed claiming priority to this patent. It is a standalone utility patent.
• Priority Application: The US application (13/512,139) is the national stage entry of the international PCT application PCT/NL2010/050795, which was filed on November 26, 2010. This PCT application claims priority to an earlier European patent application, EP09177411, filed on November 27, 2009. This 2009 date is considered the priority date for the invention.

Patent Family Members

A patent family consists of a set of patent applications filed in various countries to protect a single invention. The family members for US 9,235,259 share the same priority application (EP09177411).

• International (WIPO): WO2011065828A1
• European Patent Office (EPO): EP2328142A1, EP2504834A1, EP2504834B1
• United States: US20120288103A1 (publication of the application), US9235259B2 (the granted patent)

This document serves as a defensive disclosure of derivative inventions and improvements related to the art described in US Patent 9,235,259. The purpose of this disclosure is to place these concepts into the public domain, thereby establishing them as prior art for any future patent applications. The disclosures herein are described in sufficient detail to enable a Person Having Ordinary Skill in the Art (PHOSITA) to practice the inventions.

Disclosure Set 1: Derivatives of Core Coarse-to-Fine Tick Detection (Claims 1 & 9)

This set of disclosures expands upon the fundamental method of using a low-power coarse processor to trigger a high-fidelity fine processor that compares an audio event to a device-specific, pre-trained fingerprint.

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1.1. Component Substitution: Haptic/Vibrational Tick Detection

• Enabling Description: This variation replaces the microphone with a non-acoustic sensor to detect the "tick" as a physical impulse. A piezoelectric transducer is laminated onto the device's chassis, or a multi-axis MEMS accelerometer is used. The coarse detection processor monitors the sensor output for a rapid, high-amplitude change in voltage (from the piezoelectric element) or G-force (from the accelerometer) that exceeds a baseline threshold. Upon this coarse trigger, a buffer of the high-resolution sensor data is passed to the fine detection processor. The fine processor calculates the Fast Fourier Transform (FFT) of the vibrational signal. The "fingerprint" is a pre-trained reference set of the device's characteristic structural resonant frequencies in response to a physical tap. The fine detection step involves correlating the frequency spectrum of the live impulse with this stored vibrational fingerprint.

• Mermaid Diagram:

  flowchart TD
      A[Physical Tap on Device] --> B{Piezoelectric Transducer / MEMS Accelerometer};
      B --> C[Coarse Processor: Monitor for Voltage/G-force Spike];
      C -->|Spike > Threshold| D[Trigger & Buffer High-Res Vibration Data];
      C -->|Spike <= Threshold| C;
      D --> E[Fine Processor: Perform FFT on Vibration Data];
      E --> F{Correlate FFT with Stored Vibrational Fingerprint};
      F -->|Correlation > T_p| G[Tick Confirmed];
      F -->|Correlation <= T_p| H[False Alarm];
  

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1.2. Operational Parameter Expansion: Ultrasonic Fracture Detection in Industrial Assets

• Enabling Description: This disclosure applies the method to the field of predictive maintenance and non-destructive testing. An ultrasonic transducer, sensitive in the 50 kHz to 5 MHz range, is acoustically coupled to a critical industrial component (e.g., a pressure vessel wall, a pipeline section, a rotating turbine blade). The coarse detection processor continuously monitors for wideband energy bursts characteristic of Acoustic Emission (AE) events, such as those produced by micro-fracture propagation in metals or composites. When such a burst is detected, the fine detection processor is enabled. It analyzes a high-resolution buffer of the ultrasonic waveform, comparing its spectral and temporal characteristics against a pre-trained library of AE "fingerprints" corresponding to known failure modes (e.g., crack growth, delamination, fiber breakage). The fine analysis uses a Short-Time Fourier Transform (STFT) to create a spectrogram, which is then compared to reference spectrograms using image correlation techniques.

• Mermaid Diagram:

  sequenceDiagram
      participant Asset as Industrial Asset (e.g., Pipeline)
      participant Sensor as Ultrasonic Transducer
      participant CoarseCPU as Coarse Processor
      participant FineCPU as Fine Processor
      participant Hub as Monitoring Hub
  
      Asset->>Sensor: Micro-fracture event generates ultrasonic 'tick'
      loop Continuous Monitoring
          Sensor->>CoarseCPU: Ultrasonic Waveform Data
          CoarseCPU->>CoarseCPU: Detect Energy Burst
      end
      CoarseCPU->>FineCPU: Enable! (Coarse Tick Detected at T_0)
      Sensor->>FineCPU: Buffer High-Resolution Waveform around T_0
      FineCPU->>FineCPU: Generate Spectrogram and Compare with Failure Fingerprints
      alt Correlation > Threshold
          FineCPU->>Hub: ALERT: Potential Fracture Detected (Type: Crack Growth)
      else Correlation <= Threshold
          FineCPU->>Hub: LOG: Non-critical Acoustic Event
      end
  

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1.3. Cross-Domain Application: Subterranean Pest Detection in Agriculture (AgTech)

• Enabling Description: This invention is adapted for precision agriculture to non-invasively detect and identify subterranean pests, such as root-boring insects. A geophone or soil-vibration sensor is buried in the root zone of crops. The coarse processor monitors for low-amplitude, intermittent vibrational transients against the background seismic noise. The fine processor is triggered when a transient is detected and uses a pre-trained library of vibrational "fingerprints." Each fingerprint corresponds to the unique substrate-borne vibrations produced by the movement, chewing, or stridulation of a specific target pest (e.g., the root weevil larva). The fine analysis employs the energy differencing technique from claim 20 but applies it to the low-frequency (10-800 Hz) spectrum of the geophone signal. Identification of a pest triggers a targeted micro-dosing of pesticide or biological agent at that specific location.

• Mermaid Diagram:

  stateDiagram-v2
      [*] --> Listening
      Listening --> CoarseTrigger : Vibration transient detected
      CoarseTrigger --> FineAnalysis : Enable fine processor
      FineAnalysis --> Listening : Correlation < Threshold (False Alarm)
      FineAnalysis --> PestIdentified : Correlation > Threshold for Pest 'X'
      PestIdentified --> Dosing : Trigger targeted micro-dosing
      Dosing --> Listening : Return to monitoring state
  

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1.4. Integration with Emerging Tech: AI-Adaptive Acoustic Fingerprinting

• Enabling Description: This disclosure enhances the tick detection system with an AI model that dynamically adapts the reference fingerprint to changing environmental conditions. The device is equipped with an array of IoT sensors (e.g., temperature, humidity, barometer, accelerometer for orientation). The coarse detection stage remains the same. When triggered, the fine processor receives the audio buffer and a feature vector of the current environmental state from the IoT sensors. Instead of a static fingerprint, it uses a lightweight generative neural network (e.g., a conditional variational autoencoder) that was trained on tick recordings under a wide range of conditions. The network takes the environmental feature vector as a condition and generates an expected fingerprint for the tick under the current conditions. This generated fingerprint is then used for the correlation, dramatically improving robustness to environmental changes and device aging.

• Mermaid Diagram:

  classDiagram
      class CoarseDetector {
          +listenForSpike()
      }
      class FineDetector {
          -correlationThreshold
          +confirmTick(audioBuffer, contextVector)
      }
      class AIGenerator {
          <<Model>>
          +generateFingerprint(contextVector)
      }
      class IoTSensorManager {
          +getCurrentContextVector()
      }
      CoarseDetector --> FineDetector : triggers
      FineDetector "1" -- "1" IoTSensorManager : gets
      FineDetector "1" -- "1" AIGenerator : uses
      IoTSensorManager ..> AIGenerator : provides context
  

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1.5. Inverse/Failure Mode: Failsafe Low-Power Tick Confirmation

• Enabling Description: This variant describes a "graceful degradation" mode for ultra-low-power scenarios, such as when a device's battery is critically low. Upon entering this state, the fine detection processor and its associated memory and clock domains are completely powered down. The system relies solely on the coarse detector. To reduce the high rate of false positives from the coarse detector alone, a secondary confirmation logic is implemented. When the coarse detector triggers, it does not wake the fine processor. Instead, it registers a "potential tick event" and opens a short time window (e.g., 500 ms). It then requires a second, distinct coarse tick event to occur within that window to validate the event as a "confirmed tick." This "double-tap" logic provides a rudimentary but extremely low-power method of confirmation, maintaining basic functionality while consuming minimal energy.

• Mermaid Diagram:

  stateDiagram-v2
      state "Low Power Mode" as LPM {
          [*] --> Idle
          Idle --> Tentative : Coarse tick detected
          Tentative --> Confirmed : Second coarse tick detected within 500ms
          Tentative --> Idle : Timeout (500ms)
          Confirmed --> Idle : Report tick and reset
      }
      state "Full Power Mode" as FPM {
          [*] --> Listening
          Listening --> Fine_Processing : Coarse tick detected
          Fine_Processing --> [*]
      }
  

Disclosure Set 2: Derivatives of Noise Suppression via FFT Energy Differencing (Claims 20 & 22)

This set expands on the specific fine-processing technique of using differences between FFTs of successive audio buffers to suppress noise and create a fingerprint.

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2.1. Signal Processing Substitution: Wavelet Packet Decomposition for Fingerprinting

• Enabling Description: This disclosure replaces the FFT-based fine processing with a Wavelet Packet Decomposition (WPD). WPD provides a richer time-frequency analysis than FFT, particularly for transient signals. Upon a coarse trigger, the buffered audio is decomposed using WPD to a specified level (e.g., level 4), creating a tree of wavelet coefficients. The energy of the coefficients in each terminal node (representing a specific frequency sub-band) is calculated for successive time buffers. The "fingerprint" is a reference vector (or matrix) of the expected inter-buffer energy differences across these specific wavelet sub-bands. This method is more robust to certain types of non-stationary noise, as the wavelet basis functions are better at compactly representing transient "tick" signals than sinusoidal FFT basis functions. A Morlet or Daubechies mother wavelet is selected for this purpose.

• Mermaid Diagram:

  flowchart TD
      subgraph Fine Processing v1 (Patent)
          A[Audio Buffer] --> B[Compute FFT];
          C[Previous Buffer] --> D[Compute FFT];
          B & D --> E{Compute Energy Difference in Frequency Bins};
      end
      subgraph Fine Processing v2 (Wavelet)
          F[Audio Buffer] --> G[Compute WPD];
          H[Previous Buffer] --> I[Compute WPD];
          G & I --> J{Compute Energy Difference in Wavelet Sub-bands};
      end
      E --> K[Correlate with FFT Fingerprint];
      J --> L[Correlate with Wavelet Fingerprint];
  

---

2.2. Cross-Domain Application: Smart Home Wake-Word Reverb Analysis

• Enabling Description: The method is applied to smart speakers to reject false wake-word activations from media playback (e.g., a TV). The standard low-power phonetic model serves as the "coarse detector." Upon a potential wake-word detection, the "fine processor" is enabled. It analyzes the audio signal containing the wake-word and the audio immediately following it. It computes FFTs for two overlapping buffers: one centered on the wake-word and one centered on the subsequent reverberant tail. By taking the difference of the energy spectra (F c (ω,m') = E c (ω,m') - E c (ω,m'-1)), the system isolates the spectral decay characteristics of the sound in the specific room. This acoustic signature is compared to a "fingerprint" of the room's reverberation profile learned during device setup. A wake-word originating from a TV will have the acoustic characteristics of the TV's speakers and the recording environment, which will not match the live room's fingerprint, causing the activation to be rejected.

• Mermaid Diagram:

  stateDiagram-v2
      [*] --> Listening
      Listening --> CoarseWakeWord : Phonetic match for "Hey Gizmo"
      CoarseWakeWord --> FineReverbAnalysis : Enable fine processor
      state FineReverbAnalysis {
          direction LR
          [*] --> CaptureAudio
          CaptureAudio --> ComputeFFTs : Buffer 1 (word), Buffer 2 (tail)
          ComputeFFTs --> ComputeEnergyDiff : Isolate room reverb signature
          ComputeEnergyDiff --> CorrelateWithRoomFingerprint
      }
      FineReverbAnalysis --> [*] : Correlation > Threshold (Wake-word Accepted)
      FineReverbAnalysis --> Listening : Correlation < Threshold (False Alarm, from TV)
  

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2.3. Integration with Blockchain: Immutable Physical Event Auditing

• Enabling Description: This disclosure creates a system for a high-security, auditable supply chain. An IoT device attached to a secure container uses the coarse-to-fine tick detection to identify impacts or unauthorized access attempts. Upon a confirmed "fine" detection, the system generates the fingerprint matrix (F c (ω,m)). This matrix, along with the GPS location, a high-precision timestamp, and the device ID, is serialized into a JSON object. The SHA-256 hash of this JSON object is computed. This hash is then submitted as a transaction to a permissioned blockchain (e.g., Hyperledger Fabric). Storing only the hash on-chain is efficient, while the full JSON payload is stored off-chain in a distributed file system like IPFS. This creates an immutable, tamper-evident, and verifiable record of a physical event occurring at a specific time and place.

• Mermaid Diagram:

  sequenceDiagram
      participant Container as Secure Container
      participant Sensor as IoT Device
      participant Blockchain as Private Blockchain
      participant OffChainDB as Distributed Storage (IPFS)
  
      activate Sensor
      Container->>Sensor: Physical Impact ('tick')
      Sensor->>Sensor: Coarse-to-Fine Detection
      Sensor->>Sensor: Generate Fingerprint Matrix Fc
      Sensor->>Sensor: Create JSON Payload (Timestamp, GPS, Fc)
      Sensor->>OffChainDB: Store JSON Payload, get Content ID (CID)
      Sensor->>Sensor: Compute Hash(CID + Metadata)
      Sensor->>Blockchain: Submit Transaction(Hash)
      deactivate Sensor
  

Combination Prior Art Disclosures

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3.1. Combination with WebRTC and WebAssembly (WASM)

• Enabling Description: A method for browser-based, peer-to-peer device pairing is disclosed. Two devices (e.g., laptops) navigate to a web application. The application uses the Web Audio API (getUserMedia) to access the microphone on each device. A Web Worker, running in a background thread, performs the computationally inexpensive "coarse tick detection" on the raw audio stream. When a potential tick is found, the relevant AudioBuffer is passed to the main JavaScript thread. The main thread invokes a pre-compiled WebAssembly (WASM) module that executes the high-performance "fine tick detection" algorithm, including the FFT energy differencing and correlation check against a fingerprint downloaded from the server. When both devices report a confirmed tick with a closely matching timestamp and fingerprint correlation, their identities are exchanged over an existing, unauthenticated WebRTC RTCDataChannel, thus establishing a secure, authenticated session. This method fully implements the patented invention within the open standards of the modern web platform.

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3.2. Combination with the Matter IoT Protocol

• Enabling Description: A "tap-to-commission" feature for Matter-compliant IoT devices is disclosed. A new, un-commissioned device (e.g., a smart bulb) listens for a specific tap sequence on its housing using the coarse-to-fine detection method. A commissioning device (e.g., a smartphone) is physically tapped against the bulb. Both devices detect the tick. The bulb, upon confirming the tick via its internal fine processor, broadcasts a special Matter-compliant BLE advertisement packet containing a hash of the tick's fingerprint. The smartphone, also having detected the tick, computes its own hash. It scans for the bulb's advertisement and, upon finding a packet with the matching hash, initiates the standard Matter commissioning flow over BLE. This uses the shared physical event, verified by the patented method, as a secure, out-of-band mechanism to bootstrap the standardized Matter onboarding process.

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3.3. Combination with Android Sensor Hardware Abstraction Layer (HAL)

• Enabling Description: A method for system-level integration of the tick detection algorithm into an Android-based mobile device is disclosed. The device manufacturer implements the coarse-to-fine tick detection logic within the device's Sensor HAL. A new, non-standard sensor type, SENSOR_TYPE_ACOUSTIC_TAP, is defined and registered with the SensorManager. The coarse detection algorithm is implemented to run continuously on a low-power Digital Signal Processor (DSP) that has access to the device's microphone data. Upon a coarse trigger, the DSP wakes the main Application Processor (AP) and passes it the relevant audio buffer. The AP executes the fine detection algorithm. If the tick is confirmed, the HAL driver populates a sensors_event_t structure and pushes it to the system's sensor event queue. Any user-space application with the appropriate permissions can then register a SensorEventListener for this sensor type, allowing them to receive tap events without requiring microphone access or implementing the detection logic themselves. This embeds the patented method as a native feature of the open-source mobile operating system.