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For the Inventor, By the Inventor

Fort Lauderdale, FL, United States of America

Strong Force Tp Portfolio 2022, LLC


USPTO Granted Patents = 52


Forward Citations = 29

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4 inventors (with patents filed for the assignee):

goldMedal Charles Howard Cella (52 out of 396 patents)

silverMedal Andrew Cardno (1 out of 85 patents)

bronzeMedal Jenna Lynn Parenti (1 out of 8 patents)

4.  Taylor D Charon (1 out of 1 patent)


Core Competencies:
Neural Network
Vehicle Optimization
Rider Satisfaction
Robotic Process Automation
Emotional State
Digital Twin
Augmented Reality
Physiological Data
User Experience
Transportation Systems
Cognitive System
Recommendation System

52 patents:

1. 12694427 - Hybrid neural network for determining at least one parameter of a charging plan for a vehicle (2026-07-28),
2. 12380746 - Digital twin systems and methods for transportation systems (2025-08-05),
3. 12361324 - Inducing variation in user experience parameters based on sensed rider physiological data in intelligent transportation systems (2025-07-15),
4. 12353206 - Vehicle rider satisfaction promoting systems based on adjusting operating parameters of the vehicle (2025-07-08),
5. 12321170 - Robotic process automation for achieving an optimized margin of vehicle operational safety (2025-06-03),
6. 12321169 - Optimizing a vehicle operating parameter based in part on a sensed emotional state of a rider (2025-06-03),
7. 12321168 - Transportation system to optimize an operating parameter of a vehicle based on an emotional state of an occupant of the vehicle determined from a sensor to detect a physiological condition of the occupant (2025-06-03),
8. 12298760 - Neural net optimization of continuously variable powertrain (2025-05-13),
9. 12298759 - Using social media data of a vehicle occupant to alter a route plan of the vehicle (2025-05-13),
10. 12283140 - Vehicle dynamics control using deep learning to update an operational parameter of a vehicle drive train (2025-04-21),
11. 12253851 - Cognitive system reward management (2025-03-18),
12. 12248317 - Neural net-based use of perceptrons to mimic human senses associated with a vehicle occupant (2025-03-11),
13. 12248316 - Expert system for vehicle configuration recommendations of vehicle or user experience parameters (2025-03-11),
14. 12242264 - Using neural network to optimize operational parameter of vehicle while achieving favorable emotional state of rider (2025-03-04),
15. 12242262 - Intelligent transportation systems (2025-03-04),
Company Overview
Strong Force Tp Portfolio 2022, LLC, based in Fort Lauderdale, FL, specializes in the development of advanced Intelligent Transportation Systems. The company focuses on leveraging cutting-edge technologies such as neural networks and robotic process automation to enhance vehicle optimization and rider satisfaction. Their innovative approach incorporates emotional state analysis, digital twin technology, and augmented reality, alongside the integration of physiological data, to create a more efficient and user-centric transportation experience.
Profile summary synthesized from public USPTO records and patent filings.

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USPTO Data Jan 1 1976 - Oct 20 2026

52 Patents

#9 in Fort Lauderdale, FL

#159 in Florida

#6,769 in US

#13,571 in the World

Fort Lauderdale, FL (US)
Fort Lauderdale, FL, United States of America

Strong Force Tp Portfolio 2022, LLC

Forward Citations = 29

4 inventors:

goldMedal Charles Howard Cella (52 out of 396 patents)

silverMedal Andrew Cardno (1 out of 85 patents)

bronzeMedal Jenna Lynn Parenti (1 out of 8 patents)

4.  Taylor D Charon (1 out of 1 patent)

IDiyas Innovation Intelligence. (2026). Company Patent Portfolio: Strong Force Tp Portfolio 2022, LLC. Retrieved from https://idiyas.com/company/strong-force-tp-portfolio-2022

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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