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Скачать или смотреть 🚇 MetroDocs AI: Smart Document Intelligence Platform for Kochi Metro - SIH25080- Innovative Squad

  • Ariyan
  • 2025-09-25
  • 79
🚇 MetroDocs AI: Smart Document Intelligence Platform for Kochi Metro - SIH25080- Innovative Squad
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Описание к видео 🚇 MetroDocs AI: Smart Document Intelligence Platform for Kochi Metro - SIH25080- Innovative Squad

Background & Problem :
Since its first commercial run in 2017, Kochi Metro Rail Limited (KMRL) has grown into a multidisciplinary organization that goes far beyond running trains. Every single day, the system generates and receives a massive volume of documents: engineering blueprints, safety circulars, HR policies, vendor invoices, regulatory notices, incident reports, and many more. These arrive in different formats—emails, SharePoint repositories, scanned hard copies, WhatsApp PDFs, and bilingual documents in English and Malayalam.

This has created multiple pain points for KMRL:

Information delays: Employees waste hours searching through long documents to find small but critical details.

Siloed awareness: Different departments often remain unaware of important updates from others.

Compliance risk: Regulatory deadlines from safety authorities are buried in documents, creating the risk of non-compliance.

Knowledge attrition: Institutional memory gets lost when senior staff retire or transfer.

Duplication of effort: Teams independently prepare summaries or slide decks from the same documents.

If this continues, the burden will only grow as KMRL expands corridors, adds depots, and integrates modern technologies. A solution is needed to bring speed, accuracy, and clarity into document management.

Proposed Solution – MetroDocs AI
We propose MetroDocs AI, an AI-powered smart document management and intelligence platform tailored for KMRL. It will:

Smart Document Ingestion Hub

Collects documents from all sources (emails, scans, WhatsApp PDFs, SharePoint, hard-copy uploads).

Supports bilingual files (English + Malayalam).

AI/NLP Processing Layer

Uses Optical Character Recognition (OCR) to extract text from scanned images.

Natural Language Processing (NLP) models summarize key insights, deadlines, figures, and safety instructions.

Categorizes documents into Safety, HR, Engineering, Finance, and Compliance.

Role-Based Dashboards

Safety Team: Keeps up with the latest safety updates, compliance notifications, and incident summaries.

HR: Monitors changes in policies, training needs, and staff announcements.

Engineering: Reviews design modification notices and technical documentation.

Finance: Oversees invoices, vendor compliance, and important deadlines.

Compliance & Traceability

Automated notifications for deadlines and regulatory obligations.

Blockchain-based audit trail to maintain data integrity.

Smart Access Features

Voice-activated and chatbot-assisted document search.

Offline capabilities for accessing crucial files in areas with low connectivity.

Technology Stack

Frontend: React.js (responsive, contemporary UI)

Backend: Python (Flask/FastAPI APIs) + Node.js for scalability

AI/NLP: HuggingFace Transformers, SpaCy, Tesseract OCR

Database: MongoDB (unstructured) + PostgreSQL (structured)

Cloud Hosting: AWS / MeghRaj (Government Cloud)

Blockchain: Hyperledger Fabric for secure logging

Visualization: Grafana / PowerBI for dashboards

Impact & Benefits

Social: Multilingual capabilities and voice features empower employees at all levels.

Economic: Saves up to 40% of staff time in document management, minimizes compliance penalties, and reduces operational expenses.

Environmental: Encourages a paperless work environment and cuts down on unnecessary printing.

Feasibility & Strategy

Cost-effective: Utilizes open-source AI tools and government-backed cloud infrastructure.

Scalable: Can be implemented in other metro systems across India.

Adoption Plan: Gradual rollout beginning with Safety & HR, followed by Finance and Engineering.

Sustainability: Built as a SaaS platform to extend to other public transport systems and smart city initiatives.

Future Scope

Broaden the solution to additional metros such as Delhi, Mumbai, and Chennai.

Incorporate predictive AI models to identify potentially problematic documents before issues arise.

Merge IoT sensor data with document information for comprehensive Metro Operations oversight.

Investigate collaborations with Smart City projects for broader implementation.

Conclusion
MetroDocs AI will transform the way KMRL handles its daily flood of documents. Instead of wasting time searching, duplicating, or risking compliance failures, staff at every level will have access to quick, reliable insights. The result will be faster decision-making, stronger regulatory compliance, reduced costs, and better service reliability for passengers.

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