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Welcome to the PLUSE

Introduction

The PLUSE (Predictive Uptime & Lifecycle Sentry Engine) Platform is a mission-critical, AI-driven system designed to deliver proactive, transparent, and intelligent asset management. Utilizing a high-performance FastAPI backend, PLUSE integrates real-time condition monitoring with advanced machine learning models for fault detection and Remaining Useful Life (RUL) prediction. This platform uniquely incorporates Digital Twin concepts and Explainable AI (XAI) to provide clear, actionable insights for mission-critical predictive maintenance operations.

This wiki serves as the central documentation repository for all aspects of the PLUSE platform, covering architecture, development, deployment, and operational procedures.

Quick Navigation

Section	Description	Key Content
Overview and Vision	High-level project summary, core pillars, and technology stack.	Project Goals, Tech Stack, Core Pillars
Architecture and Design	Detailed breakdown of system components, service interaction, and the Digital Twin structure.	System Diagram, Microservices, Data Flow
Data & Signal Processing	Documentation of data sources, ingestion pipeline, feature extraction, and signal processing techniques.	Sensor Data, Feature Engineering, Pipelines
Models and Explainability	Specifications for the Fault Detection and RUL Prediction models, including the methodology for Explainable AI (XAI).	Model Specs, Training Data, XAI Strategy
Development & Deployment	Guidelines for local setup, API endpoint documentation, and deployment procedures (Docker/Kubernetes).	FastAPI Endpoints, Local Setup Guide, Deployment SOP
Contribution Guidelines	Standards for code submission, documentation, and version control.	Code Standards, Branching Strategy, Review Process