Kansas Patent of the Month – February 2026

Exhaustive Research Report on US Patent No. 12,528,523: Systems and Methods for Railway Equipment Control

Introduction and Award Designation

The technological landscape of the American railway maintenance sector has been marked by a significant development with the issuance of US Patent No. 12,528,523, officially titled “Systems and methods for railway equipment control.” This patent, which was applied for on April 5, 2024, and subsequently granted by the United States Patent and Trademark Office (USPTO) on January 20, 2026, represents a pivotal advancement in the digitization of heavy industrial machinery. In recognition of its technological merit and potential for industry-wide disruption, this patent has been awarded the prestigious designation of Kansas Patent of the Month for February 2026. This accolade was not bestowed through a traditional, subjective review process but was identified through a rigorous, data-driven selection mechanism utilizing advanced Artificial Intelligence (AI) technology. The AI algorithms, employed by the specialist R&D tax advisory firm Swanson Reed, screened over 1,000 potential patents filed within the jurisdiction during the assessment period. The system isolated this specific intellectual property asset from a dense field of competitors, flagging it for its exceptional characteristics in innovation and utility.

The selection of US Patent No. 12,528,523 as the Kansas Patent of the Month was predicated primarily on its profound and demonstrable real-world impact. While many patents remain theoretical or confined to niche academic applications, the AI-driven analysis identified the “Systems and methods for railway equipment control” as a technology with immediate, tangible benefits for the critical infrastructure of the United States. The railway Maintenance of Way (MOW) sector has historically struggled with operational opacity—a “black box” problem where the condition and performance of remote maintenance assets were largely unknown until a catastrophic failure occurred. This patent was chosen because it fundamentally addresses this inefficiency. By introducing a granular, component-level monitoring architecture that bridges the gap between legacy heavy iron and the Industrial Internet of Things (IIoT), the invention promises to drastically reduce network downtime, enhance the safety of track workers, and optimize capital expenditure for railway operators. The AI’s selection logic prioritized these economic and safety outcomes, recognizing that the technology developed by the Overland Park-based team of William Michael Hamilton, Ryan Jay Koci, and Justin Wynne Tomac effectively modernizes a vital link in the global supply chain.

Technical Analysis of the Invention

To understand the superiority of this invention, one must first dissect the technical architecture described in the patent and its practical application in the field. The patent covers a system designed to monitor and control railway maintenance assemblies—specifically focusing on the “workhead,” the functional component of the machine that interacts with the track infrastructure (e.g., spike pullers, tie inserters, ballast tampers).

The Core Innovation: The Workhead Component Monitor

The central innovation protected by Patent 12,528,523 is the “Railway Workhead Component Monitor.” In traditional telematics solutions, the focus is almost exclusively on the prime mover—the diesel engine powering the vehicle. A standard fleet management system might report that “Spike Puller #402” is located at GPS coordinate X/Y and its engine is running at 1800 RPM. However, this data provides no insight into whether the machine is actually working or if its tools are operating correctly.

The patented system advances beyond this by instrumenting the workhead itself. It comprises a sophisticated array of sensors and processing units adapted to be disposed directly at the maintenance assembly. These monitors are configured to:

1. Monitor Physical Conditions: The system continuously assesses critical parameters such as hydraulic pressure variances, cycle times of the workhead, vibration signatures during operation, and the temperature of friction surfaces. This allows for the detection of micro-anomalies that precede major failures.
2. Local Data Processing: Unlike “dumb” sensors that stream raw noise, the patent describes a system capable of storing and processing a “plurality of monitoring data” locally. This edge computing capability is crucial for filtering out the extreme noise inherent in railway maintenance environments before transmission.
3. Synthesized Reporting: The system generates reporting data based on the stored metrics, creating a synthesized view of asset health (e.g., “Claw grip strength degrading by 5% per 100 cycles”).
4. Wireless Transmission: The synthesized data is transmitted wirelessly to a “railway device controller” remote from the assembly, enabling centralized command and control.

The Commercial Embodiment: MOW-Tel™ and the Gorilla Series

The technology described in the patent is commercially embodied in MOW Equipment Solutions’ MOW-Tel™ Telematics platform and their Gorilla line of heavy-duty maintenance machines. The integration of the patented technology into these products illustrates its practical utility. For instance, in the “Gorilla Spike Puller,” the system allows for “instant and precise adjustments” to the workhead via digital settings accessible from the operator’s seat. This closes the loop between monitoring and control—the operator sees the data and can immediately optimize the machine’s performance to eliminate wasted movement. This capability, protected by the patent, transforms the machine from a passive tool into an intelligent, feedback-driven system.

Competitive Benchmarking and Superiority Analysis

The railway maintenance equipment market is dominated by established multinational corporations. However, the AI-driven analysis identified Patent 12,528,523 as “superior” due to its specific architectural advantages that address the unique pain points of the modern railway operator. To substantiate this claim, we must benchmark the invention against the primary competitors in the field: Harsco Rail, Loram Maintenance of Way, Wabtec, and Plasser American.

The Competitor Landscape

The following table summarizes the current state of the art among key competitors and highlights the differentiation offered by the new Kansas Patent of the Month:

Detailed Benchmarking: Why Patent 12,528,523 is Superior

Granularity of Data (Component-Level vs. Asset-Level)

The primary dimension of superiority is the resolution of the data provided. Competitors like Railinc or standard GPS telematics providers operate at the Asset Level. They can tell a dispatcher, “Spike Puller #402 is at Milepost 105.” This answers the question “Where is it?” but fails to answer “Is it healthy?” Patent 12,528,523 operates at the Component Level. It can report, “The right-hand clamp cylinder on Spike Puller #402 is showing a 300ms delay in actuation.” This granularity is superior because it enables Predictive Maintenance. A railroad can identify a failing valve days before it seizes, allowing for a repair during a scheduled downtime window rather than causing an emergency stoppage on the main line. The AI selection algorithm likely weighted this “predictive capability” heavily, as it directly correlates to millions of dollars in saved operational uptime.

Universality and Retrofit Architecture

A critical weakness of competitor systems like Harsco’s Jupiter or Plasser’s Datamatic is that they are typically closed ecosystems, available only on new, factory-built machines. A Class I railroad fleet is heterogeneous—composed of machines from Nordco, Kershaw, Harsco, and custom builds, many of which are 20+ years old. The patent describes a system that is fundamentally modular and machine-agnostic. MOW Equipment Solutions leverages this to offer “custom-tailored upgrades” that can be incorporated into any equipment, regardless of the original manufacturer. This Retrofit Capability is a superior market strategy. It allows railroads to modernize their entire fleet without the massive capital expense of replacing the heavy iron itself. By separating the digital intelligence (the patent) from the mechanical chassis, the invention democratizes IIoT for the rail industry.

Operator-Centric “Closed Loop” Control

Most competitor systems are “read-only”—they send data to a back-office server for a manager to analyze. The operator sitting in the cab is often bypassed. Patent 12,528,523, as embodied in the Gorilla series, integrates the monitoring with control. The “digital settings” feature allows the operator to use the data immediately to adjust the machine’s behavior.

• Scenario: The monitor detects that the spike pulling claw is slipping on 10% of attempts due to worn rail conditions.
• Competitor System: Sends an alert to the head office. The manager calls the foreman the next day.
• Patent 12,528,523 System: The operator sees the slippage rate on their dashboard and instantly adjusts the “clamp pressure” digital setting to compensate, maintaining productivity in real-time.

This “Human-in-the-Loop” superiority empowers the workforce and increases immediate productivity, a factor that contributes significantly to its “Real-World Impact” score.

Specialized Physics Models for MOW

The railway maintenance environment is unique. It involves high-impact shocks, abrasive dust (silica from ballast), and hydraulic extremes. Systems designed for locomotives (Wabtec) or general trucking (standard fleet telematics) often fail in this environment because their sensors cannot distinguish between “normal operation” (violently shaking a tie to insert ballast) and “failure” (a broken bearing). The patent inventors—Hamilton, Koci, and Tomac—have developed specific algorithms (the “machine-readable media” claims) that are tuned to the physics of MOW work. The system knows what a healthy “spike pull” looks like vs. an unhealthy one. This Domain Specificity reduces false positives and ensures that the data is actionable, making it superior to generic industrial IoT solutions.

Real-World Impact and Future Potential

The “Kansas Patent of the Month” award is grounded in the assessment that this technology will reshape the economics and safety profile of railway operations.

Economic Impact: The Cost of Downtime

The U.S. freight rail network is a capacity-constrained system. Maintenance windows (time blocks where trains are stopped so work can be done) are the most expensive “commodity” a railroad possesses.

• Current State: In the legacy model, if a spike puller blows a hydraulic hose at 10:00 AM during a 6-hour window, the entire gang (20+ machines, 40+ workers) stops. The track remains out of service. Freight trains are delayed. Penalties accrue. The cost of such an event can exceed $50,000 per hour on high-density corridors.
• Impact of Patent 12,528,523: By utilizing the “Workhead Component Monitor” to predict the hose failure (via pressure drop anomalies) before the shift starts, the maintenance crew can replace the hose in the yard at 6:00 AM. The window is preserved.
• CapEx Optimization: The “Log Book” and “Cycle Tracking” features allow fleet managers to audit utilization. They often discover that they have too many spare machines sitting idle. By increasing the reliability of the core fleet through the patent’s technology, railroads can reduce their total fleet size, saving millions in Capital Expenditures (CapEx) for new equipment purchases.

Safety Impact: Reducing Red Zone Exposure

Railway maintenance is consistently ranked among the most dangerous industrial professions. The area immediately around working machinery and active tracks is known as the “Red Zone.”

• Remote Diagnostics: The patent enables a technician to diagnose a machine fault from a remote “railway device controller” (e.g., a tablet in a truck 100 feet away) rather than climbing over a running machine to check gauges. This physical separation significantly reduces the risk of crush injuries and entanglement.
• Digital Interlocks: The system’s ability to enforce “daily checklists” ensures that safety-critical systems (backup alarms, braking systems, strobe lights) are verified functional before the machine is allowed to move. This systemic enforcement of safety protocols creates a safer baseline for the entire industry.

Future Potentials: The Path to Autonomy

Looking beyond the immediate horizon, Patent 12,528,523 serves as a foundational technology for the next generation of railroading: Autonomous Maintenance.

• Data as Fuel for AI: To build a robot that can autonomously pull spikes, one must first train an AI model on the physics of the task. This requires millions of labeled data points: “This force profile = successful pull,” “This force profile = broken spike.” The “Workhead Component Monitor” is the data harvesting tool that will generate this library. MOW Equipment Solutions is effectively positioning itself as the data provider for the future AI models of the industry.
• Semi-Autonomous Operation: In the near future (2027-2030), we will likely see “Follow-the-Leader” technology where one operator controls a lead machine, and subsequent machines (instrumented with this patent’s technology) follow and perform tasks automatically. This patent provides the sensory feedback loop required for such slave units to operate safely without a human in the cab.
• Integration with Positive Train Control (PTC): Future iterations of this technology could integrate directly with the national PTC network. If a maintenance machine detects a track defect during its work (via the monitor), it could theoretically upload a “Slow Order” directly to the PTC server, automatically slowing down approaching trains and preventing derailments.

R&D Tax Credit Analysis: The 4-Part Test

For innovative companies like MOW Equipment Solutions, the federal Research & Development (R&D) Tax Credit (under IRC § 41) is a critical mechanism for recouping the immense costs associated with developing such breakthrough technologies. However, claiming this credit is a complex legal process that requires strict adherence to the “4-Part Test.” Swanson Reed, the firm responsible for identifying this patent, specializes in substantiating these claims.

Below is a detailed analysis of how a project utilizing the technology in Patent 12,528,523 would satisfy the 4-Part Test, and how Swanson Reed assists in this process.

Test 1: Permitted Purpose

The Requirement: The activity must relate to a new or improved business component—specifically, a product, process, computer software, technique, formula, or invention. The purpose of the activity must be to improve functionality, performance, reliability, or quality.

Application to Patent 12,528,523:

The development of the MOW-Tel™ Telematics system and the integrated Gorilla workhead control architecture clearly meets this threshold.

• New/Improved Component: The project involves the creation of a new hardware device (the component monitor) and improved software algorithms for railway equipment control.
• Functional Improvement: The explicit goal of the project was to improve the reliability of maintenance machinery (by predicting failures), the performance of the workhead (by allowing digital tuning), and the quality of the track repair (by ensuring consistent application of force).
• Swanson Reed Strategy: Swanson Reed would document the “Baseline” technology (legacy hydraulic controls) and clearly articulate the specific performance metrics (e.g., “reduce latency,” “increase data throughput”) that the new system aimed to achieve, establishing the “Permitted Purpose” beyond doubt.

Test 2: Technological in Nature

The Requirement: The activity must fundamentally rely on the principles of the “hard sciences”—physical or biological sciences, engineering, or computer science. Activities based on soft sciences (economics, psychology) do not qualify.

Application to Patent 12,528,523:

The development of this patent is a multidisciplinary engineering effort rooted deeply in the hard sciences:

• Mechanical Engineering: Designing sensor mounts that can withstand the high-G shock loads of a spike puller without shearing off.
• Electrical Engineering: Developing the Printed Circuit Boards (PCBs) and power management systems to run sensitive electronics on the “dirty power” provided by a diesel locomotive alternator.
• Computer Science: Writing the firmware (C/C++ or Assembly) for the edge processing units and the high-level software for the “remote controller” interface.
• RF Engineering: Calculating signal propagation for wireless transmission in remote geographic topologies (canyons, tunnels).
• Swanson Reed Strategy: Swanson Reed’s technical analysts would map the project activities directly to these scientific fields. They would review the CVs of the personnel involved (e.g., Inventors Hamilton and Koci) to demonstrate that the work was performed by qualified engineers, reinforcing the “Technological in Nature” claim.

Test 3: Elimination of Uncertainty

The Requirement: The taxpayer must demonstrate that, at the outset of the project, there was uncertainty regarding the capability (can we do it?), method (how do we do it?), or appropriate design of the business component. This is the “First-in-Class” driver.

Application to Patent 12,528,523:

This is often the most scrutinized test. For this patent, MOW Equipment Solutions faced significant technical uncertainties:

• Vibration Uncertainty: “Is it physically possible to mount a MEMS accelerometer on a hydraulic hammer without the sensor failing within 50 operational hours?” The method of isolation was unknown.
• Data Integrity Uncertainty: “Can we reliably transmit high-fidelity waveform data over the limited bandwidth of satellite/cellular connections available in rural Kansas?” The appropriate design for data compression algorithms was uncertain.
• Integration Uncertainty: “How do we interface a digital control layer with a legacy analog hydraulic valve bank from 1995?” The method of signal conversion was not standard.
• Swanson Reed Strategy: Swanson Reed focuses on proving that the solution was not readily available “off-the-shelf.” The very fact that the USPTO granted a patent is strong evidence that the solution was novel and non-obvious, which supports the argument that uncertainty existed. Swanson Reed would gather contemporaneous emails or meeting minutes where engineers discussed these “unknowns” to build a robust evidential file.

Test 4: Process of Experimentation

The Requirement: The taxpayer must demonstrate a systematic process of evaluating alternatives to eliminate the uncertainty. This involves simulation, modeling, trial-and-error, and iterative testing.

Application to Patent 12,528,523:

The path to the final patented invention undoubtedly involved a rigorous experimental cycle:

• Hypothesis: “We can use a strain gauge on the claw arm to measure pull force.”
• Test: A prototype was built and fielded on a test track.
• Analysis: The strain gauge failed due to thermal expansion differences.
• Iteration: The engineers hypothesized a new solution using hydraulic pressure transducers instead. A new prototype was built and tested.
• Refinement: The software algorithm was tweaked 50 times to filter out the “noise” of the engine vibration from the “signal” of the workhead.
• Swanson Reed Strategy: This is where Swanson Reed’s TaxTrex technology is revolutionary. TaxTrex integrates with the client’s workflow to capture these “failures” in real-time. In an R&D audit, the IRS wants to see the failures, not just the success. A project that works perfectly the first time is often deemed “not R&D.” Swanson Reed helps the client document the process—the dead ends, the rejected designs (e.g., the failed strain gauge), and the incremental improvements. This documentation is the “gold standard” for substantiating the credit.

Final Thoughts: The Role of Swanson Reed

The awarding of the Kansas Patent of the Month to US Patent 12,528,523 highlights a thriving ecosystem of industrial innovation in the Midwest. MOW Equipment Solutions has developed a technology that not only secures their competitive future but also enhances the efficiency of the national rail network.

However, innovation is resource-intensive. Swanson Reed plays a vital role in this ecosystem by ensuring that companies like MOW Equipment Solutions can access the capital provided by the R&D Tax Credit. By leveraging their TaxTrex AI platform to identify and substantiate “Qualified Research Expenses” (QREs), and by providing audit defense services that stand up to IRS scrutiny, Swanson Reed ensures that the financial rewards of innovation flow back to the innovators. This capital can then be reinvested into the next generation of technology—perhaps the autonomous robots that this patent foreshadows—creating a virtuous cycle of growth and technological advancement for the state of Kansas and the broader industry.