North Dakota Patent of the Month – January 2026

Subject: Comparative Analysis, Market Impact, and Fiscal Incentivization of U.S. Patent No. 12,523,643

Assignee: SafetySpect Inc.

Date: February 13, 2026

Overview of Innovation

In the contemporary landscape of biomedical engineering and industrial safety, the convergence of optical physics and artificial intelligence represents a frontier of immense economic and social value. This report provides an exhaustive analysis of U.S. Patent No. 12,523,643, titled “System and method for assessing biological tissue,” granted on January 13, 2026. Assigned to SafetySpect Inc., a Grand Forks-based innovator, this patent has been distinguished as the North Dakota Patent of the Month by Swanson Reed, selected from a field of over 1,000 candidates through a rigorous AI-driven evaluation process.

The invention addresses a critical gap in biological safety monitoring: the inability of traditional methods to detect microscopic contamination and tissue anomalies in real-time over large surface areas. By integrating multi-modal fluorescence imaging with deep learning algorithms (specifically YOLO and VGG architectures), the system offers a superior alternative to the industry-standard ATP bioluminescence swabbing and visual inspection.

This report benchmarks the technology against legacy competitors, revealing a paradigm shift from reactive, point-based sampling to proactive, area-wide imaging. It details the technology’s profound real-world impact across food safety, healthcare infection control, military readiness, and extraterrestrial agriculture (NASA). Furthermore, the report serves as a strategic guide for leveraging the Research & Development (R&D) Tax Credit (IRC Section 41). It deconstructs the development of Patent 12,523,643 through the lens of the IRS “Four-Part Test,” demonstrating how Swanson Reed’s methodology ensures compliant substantiation of such high-value innovation.

The Genesis of Innovation: U.S. Patent 12,523,643

Patent Pedigree and Specifications

The intellectual property rights secured by SafetySpect Inc. represent a significant milestone in the field of biophotonics. The details of the patent are as follows:

• Patent Number: 12,523,643
• Title: System and method for assessing biological tissue
• Application Date: October 16, 2022
• Grant Date: January 13, 2026
• Assignee: SafetySpect Inc. (Grand Forks, North Dakota)
• Inventors: Fartash Vasefi, Kenneth Edward Barton, Nicholas Bennett MacKinnon, Abdolrahim Zandi, and Kouhyar Tavakolian

The patent covers a system designed to assess biological tissue and surface contamination through a sophisticated arrangement of illumination hardware and processing logic. It is not merely a camera but a multispectral analytical device capable of distinguishing between biological contaminants (e.g., saliva, respiratory droplets, bacterial biofilms) and the background substrate. The formal granting of this patent in early 2026 marks the culmination of years of intensive research and development, solidifying SafetySpect’s proprietary position in the market for advanced optical sensing.

The Core Technology: Multimodal Imaging & AI Fusion

The innovation described in Patent 12,523,643 forms the backbone of SafetySpect’s CSI (Contamination Sanitization Inspection) and CSI-D+ technology platforms. The system operates on the principle of fluorescence excitation. Unlike standard photography which relies on reflected visible light, this system illuminates surfaces with specific wavelengths to induce fluorescence in organic molecules.

Optical Physics Mechanism

The system employs a dual-excitation approach:

1. UVC Excitation (275 nm): Ultraviolet-C light is highly effective at exciting amino acids and proteins found in biological residues.
2. Violet Excitation (405 nm): This wavelength targets porphyrins and other metabolic byproducts of bacteria.

When these wavelengths hit biological contaminants, the contaminants re-emit light at longer wavelengths (fluorescence). The system captures this emission using high-sensitivity sensors. However, raw fluorescence images are often noisy, plagued by “sensor artifacts, tissue autofluorescence, and uneven illumination”. This is where the patent’s integration of artificial intelligence becomes transformative.

The AI Engine: Deep Learning Integration

The patent creates a bridge between raw optical data and actionable intelligence. SafetySpect utilizes advanced neural networks, including VGG19 and YOLO11 (You Only Look Once) architectures, to process the spectral data.

• Noise Reduction: The AI filters out structured noise that simple background subtraction cannot handle.
• Classification: It classifies residues based on texture features (such as Local Binary Patterns) rather than just intensity, allowing it to differentiate between a dangerous bacterial biofilm and a harmless water stain or dust.
• Real-Time Edge Computing: The processing occurs on the device (edge computing), eliminating the latency of cloud uploads. This allows a user to scan a room and see contamination “heat maps” instantly.

The Distinction: North Dakota Patent of the Month

The Award and Criteria

In January 2026, Swanson Reed recognized Patent 12,523,643 as the North Dakota Patent of the Month. This accolade is not merely a participation trophy; it is a signal of elite technical achievement and commercial viability. The selection methodology underscores the rarity of this achievement.

The selection process involves an AI-powered algorithm that screens the entire corpus of newly granted patents—in this case, a pool of over 1,000 candidates. The AI evaluates patents based on a weighted matrix of indicators:

1. Novelty: Does the invention represent a new branch of technology or an incremental step?
2. Technical Complexity: Does the solution solve a difficult engineering problem?
3. Breadth of Claims: How wide is the competitive moat created by the patent?
4. Real-World Impact: Does the technology have immediate application in critical sectors like healthcare or food security?

Why SafetySpect Won

SafetySpect’s selection over 999 other candidates highlights its disruptive potential. While many patents cover abstract software concepts or minor mechanical adjustments, Patent 12,523,643 secures a platform technology with hardware and software components that address a global crisis: contamination control.

The “bar is set extraordinarily high,” with competition from advancements in biotechnology and clean energy. SafetySpect’s win validates its R&D efforts, signaling to investors and the market that this is a verified, high-value asset. The technology is not theoretical; it is already being piloted in biomedical engineering labs at the University of North Dakota (UND) and has drawn interest from the U.S. Air Force and global food services.

Comparative Analysis: Benchmarking the Technology

To understand the superiority of Patent 12,523,643, one must contrast it with the incumbent technologies: ATP Bioluminescence Swabbing and Visual Inspection.

The Incumbents

Visual Inspection

• Method: A human looks at a surface to see if it is clean.
• Limitation: It is subjective and fundamentally flawed. Dangerous bacteria and viral particles are microscopic and invisible to the naked eye. Reliance on visual inspection is a primary cause of outbreaks.

ATP Bioluminescence Swabbing

• Method: A swab is rubbed on a small surface area, then reacted with an enzyme (luciferase) to produce light if Adenosine Triphosphate (ATP) is present.
• Limitation 1: Sampling Error. A swab covers only a 4 x 4 inch area. In a large hospital room or food processing plant, swabbing effectively amounts to “spot checking,” leaving 99% of the surface untested.
• Limitation 2: Cost. Each test requires a consumable swab, costing money per test. High costs discourage frequent testing ($50/month for hardware + consumables).
• Limitation 3: Reliability. ATP testing is prone to false positives (detecting food residue as bacteria) and false negatives (missing the contaminated spot). Studies show ATP sensitivity varies wildly between 20% and 78%.

The SafetySpect Advantage (CSI-D+)

The technology in Patent 12,523,643 (implemented as CSI-D+) radically outperforms these legacy methods across all key metrics.

Superiority in Detection

• Sensitivity & Specificity: In benchmark studies, the CSI-D+ system achieved a sensitivity of 86.9% and specificity of 90.5%, far surpassing the inconsistent performance of ATP swabs.
• Differentiation: The AI can distinguish between different types of residues (e.g., respiratory droplets vs. chemical stains) using texture analysis (Local Binary Patterns), which ATP cannot do.

Operational Efficiency

• Speed: The system provides results in seconds via real-time video overlay, whereas ATP requires physical swabbing and incubation time.
• Coverage: It scans entire tables, beds, or equipment surfaces instantly. It replaces “random sampling” with “comprehensive imaging”.
• Cost: It requires no consumables. Once purchased, the device can scan thousands of times without incremental cost, making it scalable for high-frequency testing.

Real-World Impact and Market Applications

The award of “Patent of the Month” was heavily influenced by the “Real-World Impact” criteria. Patent 12,523,643 is not a niche laboratory tool; it is a platform technology with diverse applications in critical sectors.

Healthcare: The War on HAIs

Hospital-Acquired Infections (HAIs) cost the U.S. healthcare system approximately $10 billion annually.

• Impact: The SafetySpect CSI-D+ system allows environmental services staff to verify cleaning efficacy in real-time. By identifying biological residues on “high-touch” surfaces (bed rails, door handles) that visual inspection misses, hospitals can break the chain of infection.
• Senior Care: In senior living facilities, where residents are vulnerable, the technology is used to audit cleanliness and integrate with Sanitation Standard Operating Procedures (SSOPs), reducing the risk of outbreaks.

Food Safety: Farm to Fork Traceability

The food industry faces a $2.2 billion annual burden from contamination-related recalls.

• Processing: The patent enables the QAT (Quality, Adulteration, Traceability) technology. It can detect adulterants in food products and assess the quality of meat (e.g., pork loin evaluation) without destroying the sample.
• Efficiency: Unlike chemical tests that destroy the sample or take days for culture results, SafetySpect’s imaging is non-invasive and immediate. This allows for 100% inspection of products rather than random batch testing.

Military: Force Protection

SafetySpect has established a Cooperative Research and Development Agreement (CRADA) with the U.S. Army.

• Application: The technology is deployed to keep troops safe from biological threats in field environments. The ruggedized, handheld nature of the device makes it suitable for austere environments where traditional lab equipment cannot function.

Future Potential: NASA and Extraterrestrial Agriculture

Perhaps the most futuristic application of Patent 12,523,643 is its adaptation for space exploration.

• Project MoonLight: SafetySpect is proposing to integrate its multimodal imaging with environmental sensors to monitor plant health in extraterrestrial environments (ISS, Lunar Gateway, Mars habitats).
• Mechanism: The system uses Hyperspectral Reflectance Imaging (HRI) to detect plant stress, nutrient deficiencies, and diseases autonomously. This is critical for long-duration missions where food self-sufficiency is a matter of survival.

Strategic Financials: The R&D Tax Credit (IRC Section 41)

The development of Patent 12,523,643 was not merely an act of scientific curiosity; it was a substantial financial investment. Under Internal Revenue Code (IRC) Section 41, the expenses incurred during this development are eligible for the federal Research and Experimentation (R&D) Tax Credit.

For a project to qualify, it must pass the IRS Four-Part Test. Below is a detailed analysis of how the development of SafetySpect’s technology meets these rigorous statutory requirements.

The Four-Part Test Applied

Part 1: Permitted Purpose

• Requirement: The activity must relate to a new or improved business component (product, process, software, or technique) with the goal of improving performance, reliability, or quality.
• Application to Patent 12,523,643: SafetySpect aimed to create a new product (the handheld CSI device) and improved software algorithms (the AI detection engine). The specific goal was to improve the reliability of contamination detection (overcoming the false negatives of ATP) and the quality of surface hygiene assessment.
• Conclusion: Pass.

Part 2: Technological in Nature

• Requirement: The research must fundamentally rely on principles of the physical or biological sciences, engineering, or computer science.
• Application to Patent 12,523,643: The development relied heavily on optics/photonics (determining optimal excitation wavelengths at 275nm and 405nm), biological sciences (understanding fluorescence of bacterial porphyrins), and computer science (training VGG19 and YOLO11 neural networks). It was not based on soft sciences like economics or psychology.
• Conclusion: Pass.

Part 3: Elimination of Uncertainty

• Requirement: At the outset, the company must have faced uncertainty regarding the capability to develop the product, the method of development, or the appropriate design.
• Application to Patent 12,523,643:
  • Capability Uncertainty: Could a handheld device generate sufficient UV power to excite fluorescence in ambient light?
  • Design Uncertainty: How to integrate multiple sensors (RGB + UV) into a portable form factor without overheating?
  • Methodology Uncertainty: Which neural network architecture (VGG vs. YOLO) would provide the best balance of speed and accuracy on an edge device?
• Conclusion: Pass.

Part 4: Process of Experimentation

• Requirement: Substantially all activities must constitute a process of experimentation, involving the simulation, modeling, and systematic trial and error of alternatives to eliminate the uncertainty.
• Application to Patent 12,523,643: The patent development involved:
  • Hypothesis: That 275nm excitation would reveal residues invisible to 405nm alone.
  • Testing: Creating prototypes and scanning inoculated surfaces (e.g., E. coli on rubber slides).
  • Analysis: Comparing AI model performance (YOLO11n-cls vs YOLO11s-cls) and refining the training datasets.
  • Refinement: Adjusting exposure settings and gain to handle signal noise.
• Conclusion: Pass.

Claiming the Credit: The Swanson Reed Methodology

Swanson Reed, the firm responsible for the “Patent of the Month” award, specializes in substantiating these claims. Their approach ensures that innovative companies like SafetySpect can monetize their IP development without fear of audit disallowance.

The “Six-Eye Review” Process

Swanson Reed employs a rigorous quality assurance protocol to validate every R&D claim.

1. Eye Pair 1: Qualified Engineer/Scientist. They review the technical narrative of Patent 12,523,643. They verify that the “process of experimentation” (e.g., the optical wavelength testing) is scientifically valid and distinct from routine engineering.
2. Eye Pair 2: Tax Attorney. They review legal eligibility, ensuring the claim aligns with current case law (e.g., Sudderth, Union Carbide). They check for exclusions, such as “funded research” (e.g., ensuring the CRADA with the Army didn’t disqualify the expenses).
3. Eye Pair 3: CPA/Financial Expert. They calculate the Qualified Research Expenses (QREs)—wages of the inventors (Vasefi, Barton, et al.), cost of prototypes, and cloud computing costs for AI training.

AI-Driven Substantiation (TaxTrex)

Just as SafetySpect uses AI for bacteria detection, Swanson Reed uses AI for tax compliance. Their proprietary platform, TaxTrex, integrates with a company’s project management systems to tag QREs in real-time. This creates a “robust audit trail” that links specific dollars spent to specific technical uncertainties resolved in the patent.

Realizing the Value

For a high-tech startup like SafetySpect, the R&D credit is not just a deduction; it is a lifeline.

• Payroll Tax Offset: As a qualified small business, they can likely use the credit to offset the employer portion of Social Security taxes (up to $250,000/year, and potentially more under recent legislation), preserving cash flow for further innovation.
• State Credits: The activity in North Dakota likely qualifies for state-level R&D incentives, which Swanson Reed also manages.

Final Thoughts

U.S. Patent 12,523,643 is a testament to the power of interdisciplinary innovation. By merging the physics of light with the intelligence of neural networks, SafetySpect Inc. has created a tool that makes the invisible visible, enhancing safety in hospitals, food plants, and potentially on the surface of Mars.

The selection of this patent as the North Dakota Patent of the Month by Swanson Reed highlights not only its technical brilliance but its commercial and social necessity. As demonstrated, the development of this technology is a textbook case for the R&D Tax Credit, meeting every facet of the IRS Four-Part Test. For stakeholders, investors, and policymakers, this patent represents exactly the type of high-impact technology that the U.S. patent system and tax code were designed to foster.