Anand Kumar VedanthamSoftware Architect | Cloud, AI & Enterprise Systems

Patents & Innovation

This portfolio highlights registered intellectual property, design filings, and patent applications across connected vehicles, V2X communication, edge intelligence, camera-based sensing, cloud-enhanced predictive safety systems, acoustic diagnostics, software-defined automotive systems, and AI-augmented enterprise platform governance. The filings include functional system-level innovations and protected industrial design elements that support real-world deployment of intelligent connected systems.

Registered Patents, Design Filings, and Patent Applications

Registered2026German Utility Model

Integrated V2X-Based Cloud-Enhanced Predictive Risk Mitigation System for Heavy Commercial Vehicles

Predictive Risk Mitigation System for Heavy Commercial Vehicles

Number: 20 2026 100 129

Jurisdiction: Germany

Registered: 2026-03-04

IPC: G08G 1/16

An integrated predictive risk mitigation system for heavy commercial vehicles that combines onboard sensing, edge intelligence, V2X communication, and cloud-based predictive analytics to proactively identify and mitigate safety and operational risks.

Problem Addressed

Existing heavy commercial vehicle safety systems are often reactive, fragmented, and limited to vehicle-local sensing. They do not sufficiently combine cooperative V2X intelligence, cloud analytics, and real-time mitigation for traffic, weather, driver, and infrastructure-related risks.

Innovation Highlights

  • Onboard vehicle unit with sensor fusion and edge intelligence
  • V2X communication with V2V, V2I, V2N, and V2P support
  • Cloud predictive analytics using real-time and historical fleet data
  • Forecasting of collision risk, rollover probability, braking anomalies, driver fatigue, and infrastructure hazards
  • Mitigation actions including driver alerts, fleet notifications, route/speed recommendations, and cooperative safety messages
  • Support for fleet safety policies, compliance rules, and reporting
V2XConnected VehiclesPredictive AnalyticsFleet SafetyITSEdge AICloud AnalyticsHeavy Commercial VehiclesTransportation Safety
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Registered2026UK Registered Design

Integrated Camera–V2X Sensor Fusion Enclosure for Commercial Vehicles

UK Registered Design for Commercial Vehicle Camera and V2X Sensor Fusion Enclosure

Design Number: 6502315

Jurisdiction: United Kingdom

Grant Date: 12 February 2026

Registration Date: 28 January 2026

Classification: Class 16 / Subclass 01

Design Classification Detail: Photographic, Cinematographic and Optical Apparatus; Photographic and Cinematographic Cameras

A registered UK design covering the external enclosure and industrial design of an integrated camera and V2X sensor fusion device for commercial vehicles. The enclosure is designed to support vehicle-mounted sensing, camera integration, sensor fusion hardware, and rugged deployment scenarios for connected and predictive safety systems.

Problem Addressed

Commercial vehicle safety and connected mobility systems require rugged, purpose-built device enclosures that can support camera modules, sensor interfaces, edge electronics, vehicle mounting, and operational durability. Generic housings often do not adequately reflect the physical, integration, and deployment needs of V2X-enabled predictive safety devices.

Innovation Highlights

  • Vehicle-mountable enclosure for camera and V2X sensor fusion use cases
  • Designed for commercial vehicle safety and connected mobility applications
  • Supports integration of camera modules, sensing electronics, and edge intelligence hardware
  • Ruggedized industrial form factor suitable for vehicle deployment
  • Aligns with predictive risk mitigation, fleet safety, and intelligent transportation systems
  • Complements the German utility model by protecting the physical device enclosure design
UK Registered DesignDesign PatentCamera EnclosureV2XSensor FusionCommercial VehiclesEdge AIFleet SafetyConnected MobilityIndustrial Design
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Registered2026German Patent Application

System for Real-Time Acoustic Health Monitoring in Software-Defined Automotive Systems

AI-Enabled Acoustic Diagnostics for Software-Defined Vehicles

Jurisdiction: Germany

Status: Patent granted / registered

Filing Year: 2026

Technology Area: Software-Defined Vehicles, Automotive Diagnostics, Acoustic AI, Edge Intelligence

Inventor / Applicant: Anand Kumar Vedantham, Kirankumar Sunakara, NanaRam Parza

A granted patent directed to a real-time acoustic health monitoring system for software-defined automotive systems. The system is designed to capture in-vehicle acoustic signals, perform audio preprocessing and feature extraction, apply edge AI inference configured to detect abnormal subsystem signatures, correlate acoustic findings with vehicle telemetry and software-state metadata, and support health, safety, maintenance, and diagnostic evidence outputs.

Problem Addressed

Software-defined vehicles introduce increasing complexity through centralized compute platforms, zonal controllers, software updates, calibration changes, sensors, actuators, and connected vehicle functions. Traditional diagnostics often rely on diagnostic trouble codes, vibration sensors, temperature sensors, current sensing, and manual inspection. However, many early-stage mechanical, electrical, and subsystem degradation issues first appear as subtle acoustic signatures before clear fault codes are generated.

Innovation Highlights

  • Acoustic sensor layer using one or more microphones or microphone arrays positioned across vehicle zones
  • Audio preprocessing and feature extraction using noise filtering and compact acoustic embeddings
  • Edge AI inference for anomaly detection, subsystem classification, health scoring, and severity grading
  • Telemetry correlation with speed, acceleration, RPM, torque, braking, thermal, and electrical context
  • Software-state correlation using OTA build identifiers, calibration versions, drive modes, and feature flags
  • Alerting and evidence management with acoustic snippets, telemetry context, and recommended service actions
  • Optional backend integration for fleet analytics, governed model updates, and predictive maintenance workflows
Granted PatentGerman PatentSoftware-Defined VehiclesAutomotive DiagnosticsAcoustic AIEdge AIPredictive MaintenanceVehicle TelemetryFleet AnalyticsConnected Vehicles
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Filed2025U.S. Utility Patent Application

CONNECT Framework for AI-Augmented Enterprise Alignment and Platform Governance

AI-Augmented Enterprise Governance and Digital Transformation Framework

Application Number: 19/333,899

Jurisdiction: United States

Application Type: Utility – Nonprovisional Application under 35 USC 111(a)

Filing Date: 09/19/2025

Receipt Date: 11/24/2025

Confirmation Number: 8340

First Named Inventor: Anand Kumar Vedantham

Status: Patent application filed / pending

A U.S. utility nonprovisional patent application directed to the CONNECT Framework, a modular AI-augmented system for enterprise digital transformation and platform governance. The framework integrates collaboration, governance automation, tool registry management, standardization, AI-driven consolidation recommendations, workforce training, and continuous monitoring into a closed-loop enterprise governance architecture.

Problem Addressed

Large enterprises often struggle with tool sprawl, redundant platforms, siloed teams, inconsistent standards, fragmented governance, manual compliance reviews, and escalating technology costs. Traditional governance models are often reactive and static, making it difficult to align enterprise platforms, delivery standards, workforce capabilities, and transformation goals at scale.

Innovation Highlights

  • Collaboration hub for centralized solution discovery and governance interaction
  • Governance engine for policy enforcement, compliance validation, and approval workflows
  • Knowledge-graph-based tool registry linking tools, owners, business domains, compliance attributes, and usage metadata
  • Standardization engine for templates, naming conventions, reference architectures, and reusable patterns
  • AI analysis layer for redundancy detection, anomaly detection, clustering, and consolidation recommendations
  • Decision-support interface with explainable, role-specific recommendations for executives, developers, and risk officers
  • Training and onboarding subsystem that maps governance deviations to targeted learning paths
  • Continuous monitoring and CMDB integration to maintain a digital twin of enterprise tooling
  • Feedback loop that continuously improves governance, standardization, and platform optimization
U.S. Patent ApplicationCONNECT FrameworkEnterprise GovernanceAI GovernanceDigital TransformationPlatform GovernanceTool RegistryKnowledge GraphStandardizationCloud GovernanceDevSecOpsEnterprise Architecture
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