Smart Technologies Academic Press
Advancing global innovation through rigorous peer-reviewed research in computer science, sustainable technologies, and applied biomedical informatics.
Smart Technologies Academic Press
Is an academic platform dedicated to promoting and disseminating innovative research in the realm of sustainable technologies. Our mission is to empower researchers, academics, and industry professionals to exchange knowledge and contribute to advancing sustainable solutions for global challenges. By fostering a collaborative environment, STAP serves as a bridge connecting technology and sustainability. Our journal publications encompass a wide array of topics, including renewable energy, sustainable design, green innovations, and the intersection of technology with environmental responsibility. STAP is committed to rigorous peer-reviewed research and strives to uphold academic excellence. We aim to amplify impactful ideas and research contributions that align with the global vision of sustainable development, making it accessible to a diverse audience of readers and practitioners.
Indexed & Abstracted In








Featured Journals
Discover our tier-1 open access publications.

Journal of Cyber Security and Risk Auditing

Jordanian Journal of Informatics and Computing
Editors-in-Chief


STAP Journal of Security Risk Management
Editors-in-Chief


STAP International Journal of Accounting and Business Intelligence
Editors-in-Chief

Latest Publications
Recently accepted and published open-access articles.
Robust Image Steganography against Differential Attacks Using GA-Optimized LSB Embedding
Dena Abu Laila, Ziad E. Dawahdeh, Amer Alqutaesh, Ghada Alradwan
A Framework for Transparent and Secure Digital Trading Using Decentralized Applications
Alwi M Bamhdi
A Systematic Literature Review of Blockchain-Enabled Zero Trust Architectures for Secure Non-Terrestrial Networks in 6G Cloud–Edge Environments
Abdullah Albuali , Huda Aldawghan, Ashwag Alotaibi
A Smart Dashboard Framework for Urban Tourism Risk Analysis Using Deep Learning and Machine Learning
Adona Kulathinal Josephi, Mahmud Maqsood


