Sustainability Data Management Platform for Industry

Abstract

Rapid industrialization has intensified environmental degradation, making systematic monitoring of ecological indicators indispensable for regulatory compliance and sustainable development. This paper presents the Sustainability Data Management Platform (SDMP), a web-based system designed to monitor and manage environmental sustainability data in industrial settings. The platform tracks critical parameters including the Air Quality Index (AQI) based on Central Pollution Control Board (CPCB) standards, carbon dioxide emissions derived from established emission factor formulas, energy consumption, and fuel usage. Built on a three-tier architecture employing React on the frontend, Python Django with Django REST Framework on the backend, and PostgreSQL as the persistent data store, the system incorporates a hybrid intelligent approach that combines rule-based threshold detection with pattern-based recommendation logic. An alert classification mechanism categorizes operational states as Safe, Warning, or Critical, while a structured recommendation engine generates actionable insights in the form of Problem–Action–Impact triplets. A role-based workflow spanning Data Entry Operator, Analyst, Manager, Supervisor, and Administrator roles ensures data integrity and governance. Evaluation on a simulated industrial dataset demonstrates that the platform reliably detects threshold violations, produces contextually relevant recommendations, and presents environmental trends through interactive dashboards. The SDMP offers a pragmatic and scalable foundation for industrial sustainability management, without reliance on computationally intensive machine learning models.