United States Patent and Trademark Office Publication
Title: System, Method, Apparatus, and Computer Program Product for Jurisdictionally Compliant Staffing Management Within Corrections Facilities
Publication No.: US-2026-0050847-A1
Publication Date: February 19, 2026
Application No.: 19/288,901
Applicant: William David Colón
Status: Published (Patent Pending)
Full Patent Link
This published patent application forms the technical foundation of the Constitutional Public Safety Staff Management System (CPSSMS).
Patent Technology Characterization
The CPSSMS is an Adaptive Self-Optimizing AI System that continuously learns from real-world operational data and dynamically adapts to changing correctional environments, including staffing levels, overtime patterns, population shifts, and regulatory requirements. The system self-optimizes through backpropagation neural networks, empirical machine learning, and multivariable optimization, governed by a central engine with mandatory Human-in-the-Loop (HITL) oversight.
CPSSMS iteratively refines staffing forecasts, schedule balancing, compliance monitoring, and resource allocation. It integrates 26 years of direct correctional leadership experience with advanced computational methodologies to deliver jurisdictionally and constitutionally compliant staffing solutions.
Core Components
- Human-In-The-Loop (HITL) Design: Ensures human review and alignment with operational context, staff safety, and constitutional standards.
- Universal Domain Bridge: Built on deep, practitioner-level mastery of labor agreements, union protocols, collective bargaining dynamics, and complex regulatory frameworks gained through NYCDOC operations — enabling seamless adaptation and compliance across federal, state, and local correctional jurisdictions nationwide.
- Performance Analysis Integration: Incorporates tools such as the Schedule Mapping Tool, Tour/Group/Squad Balance Calibration Tool, Overtime Tracking System, Enhanced Overtime Code Mapping Tool, Sequential Staff Sort System, and Governed System Compliance Engine.
- Scalable Architecture: Designed for deployment across varied jurisdictional correctional and public safety environments.
USPTO Classification and Technical Novelty
Classified under G06Q 10/06311 (Scheduling and task assignment) and G06Q 10/0633 (Workflow analysis and management), along with related subgroups covering skill-based matching and government/public services.
The CPSSMS employs an interdependent multivariable machine learning pipeline — incorporating RNN/LSTM forecasting, reinforcement learning, PCA clustering, and backpropagation — with SHAP (SHapley Additive exPlanations) for full transparency and bias mitigation.
Grounded in 26 years of proven NYCDOC operational results, including significant reductions in overtime and deployment gaps, the system delivers auditable, explainable outputs that support constitutional compliance, fiscal sustainability, and humane correctional operations.
The patented framework applies multivariable calculus as the foundational method to measure and resolve budgetary gaps between stated assumptions and actual costs for primary and ancillary tasks. It uses gradient rate analysis, time-series methods, prescriptive analytics, variance analysis, and constituent-element decomposition to achieve transparent differentiation of budgeted and non-budgeted positions.
This enables Total Resource Optimization and Workforce Excellence — the auditable endpoint of the CPSSMS — delivering a transparent, judicially defensible resource-allocation framework. The system maintains a predetermined calibrated staffing gap as a deliberate safeguard, ensuring risks remain within defined tolerances through preventive internal controls, sensitivity analysis, and continuous Human-In-The-Loop validation, all while upholding constitutional standards of care, custody, and control.
Implementation Note
All inquiries regarding licensing, implementation, or applicability should be directed to patent counsel.