AI AND IOT-BASED INTELLIGENT SUPPLY CHAIN MONITORING AND OPTIMIZATION
DOI:
https://doi.org/10.67851/ijcmth.vol.1.issue.2.028Keywords:
Artificial Intelligence, Internet of Things, Supply Chain Management, Machine Learning, Predictive Analytics, Inventory Optimization, Logistics, Real-Time Monitoring.Abstract
Supply Chain Management (SCM) involves the coordination of suppliers, manufacturers, warehouses, transportation systems, and customers. Traditional supply chain systems often face challenges such as inaccurate demand forecasting, inventory imbalance, transportation delays, equipment failures, and limited real-time visibility. The integration of Artificial Intelligence (AI) and Internet of Things (IoT) provides an intelligent approach to overcome these challenges. IoT devices and sensors continuously collect real-time information related to inventory, location, temperature, vehicle movement, and equipment status. AI and Machine Learning (ML) techniques analyze this data to identify patterns, predict potential problems, and support automated decision-making.
This paper proposes an AI and IoT-based intelligent supply chain monitoring and optimization framework. The proposed framework consists of IoT data acquisition, cloud/edge data processing, AI-based analytics, prediction, optimization, and decision-support modules. The system can be applied to demand forecasting, inventory management, route optimization, warehouse monitoring, and supply chain risk prediction. The proposed approach can improve supply chain visibility, reduce operational costs, minimize delays, and support efficient resource utilization.
