machine learning - mcp.claims

machine learning

Case Study: Model Context Protocol (MCP) ML Ops – Protocol-Managed Model Retraining with PyTorch & Feature Store

Project Overview The Model Context Protocol (MCP) ML Ops project was designed to automate and optimize machine learning model retraining workflows using PyTorch-based tool nodes and feature store resource servers. The goal was to create a scalable, protocol-managed system that ensures models remain up-to-date with minimal manual intervention while maintaining

maritime safety

Enhancing Maritime Safety with Model Context Protocol (MCP): AIS/Radar Data Fusion for Collision Avoidance

Project Overview The Model Context Protocol (MCP) Maritime Safety project aimed to improve collision avoidance in maritime navigation by fusing Automatic Identification System (AIS) and radar data using edge computing resource nodes. Traditional maritime safety systems often rely on standalone AIS or radar data, leading to gaps in situational awareness.

predictive maintenance

Case Study: MCP Factory 4.0 – Predictive Equipment Failure Using TensorFlow and OPC-UA

Project Overview The Model Context Protocol (MCP) Factory 4.0 project was designed to revolutionize predictive maintenance in industrial automation by leveraging machine learning (ML) and real-time PLC (Programmable Logic Controller) data. The goal was to develop a scalable system that could predict equipment failures before they occurred, minimizing downtime