Welcome to

International Conference on Aerospace Engineering and Blockchain Systems
(ICAEBS-2026)

A global academic platform for research, innovation, and collaboration

Organized by

International Academic Research Forum (IARF)

 
Conference Date
10th - 11th August 2026
 
Conference Location
Sao Tome , Sao Tome and Principe
 
Mode of Conference
Hybrid

Conference Session Tracks

Focused research themes driving global academic dialogue and innovation

SDG Wheel

Aligned with

UN Sustainable Development Goals

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.

Goals We Support

SDG 3 SDG 3 — Good Health and Well-being
SDG 9 SDG 9 — Industry, Innovation and Infrastructure
SDG 11 SDG 11 — Sustainable Cities and Communities
SDG 12 SDG 12 — Responsible Consumption and Production
Session Tracks
Track 01
Innovations in Aerospace Engineering

This track focuses on the latest advancements in aerospace engineering, emphasizing the integration of blockchain technologies. Participants will explore how these innovations can enhance safety, efficiency, and performance in aviation systems.

Track 02
Blockchain Applications in Predictive Maintenance

This session will delve into the role of blockchain in predictive maintenance strategies for aerospace systems. Discussions will center on how blockchain can improve data integrity and facilitate real-time monitoring of aircraft components.

Track 03
Data Analytics in Aerospace Systems

This track will examine the application of data analytics techniques, including supervised and unsupervised learning, in aerospace engineering. Attendees will learn how these methodologies can optimize system performance and enhance decision-making processes.

Track 04
Anomaly Detection in Aviation Systems

Focusing on anomaly detection techniques, this session will discuss their critical role in ensuring safety and reliability in aviation systems. Participants will explore various algorithms and their applications in identifying potential failures.

Track 05
Feature Extraction from Sensor Data

This track will cover advanced methods for feature extraction from sensor data in aerospace applications. The emphasis will be on enhancing model performance and improving predictive capabilities through effective data representation.

Track 06
IoT Integration in Aerospace Engineering

This session will explore the integration of Internet of Things (IoT) technologies within aerospace systems. Discussions will highlight how IoT can facilitate real-time data collection and enhance operational efficiency.

Track 07
Digital Twin Technologies in Aviation

This track will focus on the development and application of digital twin technologies in the aerospace sector. Participants will discuss how digital twins can be utilized for system monitoring and optimization.

Track 08
Control System Optimization using Blockchain

This session will investigate the potential of blockchain technology in optimizing control systems within aerospace engineering. Emphasis will be placed on enhancing security and reliability of control processes.

Track 09
Risk Assessment in Aerospace Engineering

This track will address methodologies for risk assessment in aerospace engineering, particularly in the context of blockchain systems. Participants will explore frameworks for evaluating risks associated with data security and operational integrity.

Track 10
Model Evaluation Techniques in Aerospace Applications

This session will focus on the evaluation of predictive models used in aerospace engineering. Attendees will discuss best practices for model validation and performance assessment.

Track 11
Asset Tracking and Management in Aviation

This track will explore innovative approaches to asset tracking and management in the aerospace industry using blockchain technology. Discussions will include the implications for operational efficiency and data transparency.