This book offers the evidence-based insights into the ethical considerations surrounding disruptive technologies. In the rapidly evolving landscape of technology, where breakthroughs in artificial intelligence, big data, the Internet of Things, and bioinformatics have revolutionized our world, a critical need arises to reassess our ethical frameworks. This need has given birth to the thriving field of technology ethics, or tech ethics, which has grown exponentially in recent years. Once a niche area of research, it now encompasses a multitude of technology experts dedicated to understanding the societal impact of these advancements and striving for the development of more ethically grounded technology. At the forefront of this movement stands the International Conference on Disruptive Technologies, Tech Ethics, and Artificial Intelligence (DITTET 2023). Serving as a paramount platform for scholars, professionals, and experts, this conference presents anunparalleled opportunity to explore the latest scientific and technical progress and its profound ethical implications. DITTET facilitates the exchange of cutting-edge research on disruptive technologies, fostering knowledge transfer and collaboration among interdisciplinary fields. DITTET 2023 aspires to bring together a diverse range of industry leaders, humanists, and academics, providing a comprehensive overview of the scientific advancements and applications of artificial intelligence while examining their ethical dimensions in areas such as climate change, politics, economy, and security. By delving into these crucial topics, the conference aims to unravel the intricate relationship between technology and ethics, paving the way for responsible and conscientious innovation in today's world.

Offers evidence-based insights into ethical considerations surrounding disruptive technologies Provides practical frameworks for addressing ethical challenges posed by emerging technologies Uncovers the social impact of disruptive technologies, shedding light on crucial ethical issues

Inhalt
Application of search algorithm in research of sEMG in swallowing disorders.- Predictive Maintenance of Mechanical systems using Data Analytics.- Development of web application firewall based on artificial intelligence.- Age Analysis with Convolutional Neural Networks.- Comparing Supervised and Unsupervised Machine Learning Techniques to Decision Support Systems in Healthcare.- Machine Learning for Automatic Weather Stations: A Case Study.- LIPTracker - People detection system based on their devices.- Smart electronic Nose: an empirical evaluation of new multi-channel gas sensors for smell classification.- Scalable and Energy-Efficient Deep Learning for Distributed AIoT Applications Using Modular Cognitive IoT Hardware.- An IoT-Based Framework for Monitoring Photovoltaic Batteries.- Spearmint: A Decentralized Solution for Recording Evidence of Cyberbullying.- Synonym-substitution algorithms for enrich the Agrovoc vocabulary.- Exploring OpenStack for Scalable and Cost-Effective Virtualization in Education.- Analysis of surface electromyography devices applied to swallowing disorders. A Systematic Review.- An IoT-enabled Framework for Efficient Water Management in Agriculture.- Integrating Weather and Orography Information in Trip Planning Systems for Heavy Goods Vehicles.- Is blockchain a disruptive innovation? A systematic literature review.- Exploring the Potential of Mixed Reality as a Support Tool for Industrial Training and Production Processes: A Case Study Utilizing Microsoft HoloLens.- Platform for tele-rehabilitation of balance disorder and motork skills.- A Framework to Optimize Waste Containers Collection Enabled by an ARIMA Model and IoT Data.