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Real-Time Asset Tracking and Management: A Novel Framework Using IoT, RFID, and AI

Authors:

Pankaj Dattatraya Baviskar¹ Rohan Lahuraj Salunkhe¹

¹Trinity Academy of Engineering, Pune, India pankajbaviskar2410@gmail.com, rohansalunkhe2002@gmail.com Contact: +91-8208248990 (Pankaj), +91-8856885237 (Rohan)

June 2025

Abstract: Effective asset tracking and management are critical for organizations to optimize resource utilization, re- duce operational costs, and enhance decision-making. Traditional asset management methods, reliant on manual processes or barcode systems, often suffer from inefficiencies, errors, and lack of real-time visibility. This paper proposes an innovative framework integrating Internet of Things (IoT), Radio Frequency Identification (RFID), and Artificial Intelligence (AI) to enable real-time asset tracking, predictive maintenance, and data-driven opti- mization. Through a mixed-methods approach, including a systematic literature review, stakeholder interviews, and simulation-based analysis, the study addresses challenges such as asset misplacement, underutilization, and data silos. The proposed system leverages IoT sensors, RFID tags, and AI algorithms to achieve 98% tracking accuracy, 25% improved asset utilization, and 30% reduced maintenance downtime. Case studies across man- ufacturing, healthcare, and logistics demonstrate the framework’s versatility. This research offers a scalable, secure, and technology-driven solution for modern asset management, contributing to operational excellence and sustainability.

Keywords: Asset Tracking, Asset Management, Internet of Things, RFID, Artificial Intelligence, Real-Time Monitoring, Predictive Maintenance

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