Symposium Series

Institute of Sensors, Signals and Systems, Heriot-Watt University, UK

Symposium Chair: Dr. Cheng Wang, Assistant Professor in Heriot-Watt University

Autonomous vehicles (AVs) must operate safely in the real world without endangering passengers or others on the road. However, challenges arise from external factors like adverse weather conditions and internal issues such as sensor failures, making their reliable deployment difficult. The problem is further exacerbated by the introduction of AI to AVs, wherein uncertainty and opacity characteristics are brought. Despite these additional risks that AI will bring, its superior performance compared to traditional modular pipelines (perception-planning-control) is appealing. Therefore, how to fully leverage the potential of AI while assuring its safety and trustworthiness is a question faced by researchers. Since safety standards such as ISO 26262 and ISO 21448 do not take AI into account, new safety assurance paradigms are critical to mitigate the risks posed by AI. The symposium aims to bring researchers together to discuss novel solutions to address this challenge and identify future research questions, with the ultimate goal of bridging the gap between the utility and safety of AI-driven AVs.

University of East London (UEL), UK

Symposium Chair: Dr. Hisham AbouGrad, Senior Lecturer in University of East London

The AI and IoT for Next-Generation Smart Robotic Systems Innovations, Challenges, and Opportunities – AISRS 2025 Symposium took place on Monday, 9th December 2024, at the University of East London (UEL). As the organiser, I was pleased to contribute to the event by submitting two papers and co-authoring another two, resulting in four research papers accepted for publication in the conference proceedings. The symposium featured the following presentations:

1. Efficient Blind Equalizer Schemes Using Variable Tap-length Algorithm - Presented by Salem Alsaid and myself, this paper explores advanced equalization techniques to enhance communication systems.
2. Neural Networks Stock Market Price Forecasting Model - Co-authored with Lakshmi Sankuru and Abdul Qadoos, this study integrates economic indicators and technical analysis for improved financial forecasting; this has been presented by Lakshmi Sankuru.
3. AI-GeoInfo Crop Recommendation Framework - Developed with Manasa Yegamati, this framework employs decision tree classifiers and GeoAPI to optimize agricultural recommendations; this has been presented by Manasa Yegamati.
4. AI Investment Advisory - In collaboration with Abdul Qadoos, Julie Wall, and MhD Saeed Sharif, this research examines the adoption of robo-advisors based on financial literacy and investment experience. This is presented by Abdul Qadoos.

Symposium participants engaged in dynamic discussions, sharing experiences and outcomes through networking and social media platforms like LinkedIn. The event successfully fostered collaboration and innovation in smart robotic systems.

UCSI University, Malaysia

Symposium Chair: Dr. Mian Umer Shafiq, Assistant Professor in UCSI University

The symposium titled "Automation and Smart Technologies in Petroleum Engineering" was successfully held at UCSI University. The presentation explores the fundamentals of Artificial Intelligence (AI) and Machine Learning (ML), their evolution, and their applications in the oil and gas industry. AI is introduced as a technology that improves efficiency by automating routine, repetitive, and time-consuming tasks. ML, a subset of AI, enables computers to learn patterns from data and make predictions without explicit programming. A visual representation highlights the hierarchical relationship between AI and ML.

The historical development of AI is outlined, showcasing key milestones such as early rule-based systems, expert systems, and the emergence of deep learning. This evolution has led to widespread AI adoption across industries, including healthcare, finance, and energy. The presentation further discusses the role of ML in the oil and gas sector, emphasizing its application in predictive maintenance, reservoir management, and operational optimization. The ML workflow is described, including data collection, preprocessing, model training, validation, and deployment. AI-driven solutions enhance decision-making, automate workflows, and reduce costs while improving efficiency.

As AI and ML continue to advance, their impact on industries is expected to grow, driving innovation and transforming business operations. Their integration into oil and gas companies highlights the potential for smarter, data-driven solutions in energy management.

ITM Department, Illinois Institute of Technology, USA

Symposium Chair: Dr. Marwan Omar, Associate Professor in Illinois Institute of Technology

The Machine Vision System symposium will provide participants with a comprehensive introduction to the principles, technologies, and applications of machine vision. The session will begin by outlining the fundamental components of a machine vision system, including cameras, sensors, lighting, image processing software, and algorithms. Attendees will gain insights into how these elements integrate to enable machines to "see" and interpret visual data for automated decision-making.

Throughout the symposium, real-world applications will be explored, such as defect detection in manufacturing, barcode and QR code reading in logistics, and quality assurance in food production. Hands-on demonstrations will allow participants to experience configuring vision systems, calibrating cameras, setting up proper lighting, and developing simple image analysis workflows. Special attention will be given to preprocessing techniques and training machine learning models for complex inspection tasks.

Key challenges such as dealing with variable lighting conditions, motion blur, and processing high volumes of visual data will be discussed, along with best practices to overcome them. The symposium will conclude with a review of emerging trends in the field, including AI-powered vision systems, edge computing, and the integration of 3D vision technologies.

Highlights