Smart IoT and AI for Sustainable Safety Management: Enhancing Efficiency in Industrial and Urban Environments
Year: 2024
Type: article
Abstract: The convergence of Smart Internet of Things (IoT) and Artificial Intelligence (AI) has revolutionized safety management in both industrial and urban settings. As environments become increasingly complex, traditional safety systems struggle to meet demands for real-time monitoring, adaptive response, and sustainability. Smart IoT systems enable continuous data collection through interconnected sensors and devices, while AI technologies process this data to detect anomalies, predict hazards, and automate responses. This integration fosters proactive safety mechanisms that enhance operational efficiency and reduce human error. This paper proposes a comprehensive framework that utilizes AI-IoT synergy to support sustainable safety management. The framework emphasizes predictive maintenance, autonomous decision-making, and secure data exchange, thereby reducing environmental impact and resource wastage. Through case studies in manufacturing plants and smart urban infrastructure, the study demonstrates how intelligent safety systems can reduce response time, improve situational awareness, and support long-term sustainability goals. The research concludes that AI and IoT integration offer a transformative path for designing responsive, scalable, and eco-conscious safety solutions suited to evolving industrial and urban landscapes.
Authors: Md Ferdous Ahmed, Md Rakibul Islam, Md Rifat Al Amin Khan, Md Nazmul Islam
Institutions: Wilkes University, University of Dhaka, Lamar University
Language: English
Topic: Internet of Things and AI
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4410075118