End-User Attitudes towards Location-Based Services and Future Mobile Wireless Devices: The Students' Perspective

Nowadays, location-enabled mobile phones are becoming more and more widespread. Various players in the mobile business forecast that, in the future, a significant part of total wireless revenue will come from Location-Based Services (LBS). An LBS system extracts information about the user’s geographical location and provides services based on the positioning information. A successful LBS service should create value for the end-user, by satisfying some of the users’ needs or wants, and at the same time preserving the key factors of the mobile wireless device, such as low costs, low battery consumption, and small size. From many users’ perspectives, location services and mobile location capabilities are still rather poorly known and poorly understood. The aim of this research is to investigate users’ views on the LBS, their requirements in terms of mobile device characteristics, their concerns in terms of privacy and usability, and their opinion on LBS applications that might increase the social wellbeing in the future wireless world. Our research is based on two surveys performed among 105 students (average student age: 24 years) from two European technical universities. The survey questions were intended to solicit the youngsters’ views on present and future technological trends and on their perceived needs and wishes regarding Location-Based Services, with the aim of obtaining a better understanding of designer constraints when building a location receiver and generating new ideas related to potential future killer LBS applications.Peer reviewe

ODIN112–AI-Assisted Emergency Services in Romania

The evolution of Natural Language Processing technologies transformed them into viable choices for various accessibility features and for facilitating interactions between humans and computers. A subset of them consists of speech processing systems, such as Automatic Speech Recognition, which became more accurate and more popular as a result. In this article, we introduce an architecture built around various speech processing systems to enhance Romanian emergency services. Our system is designed to help the operator evaluate various situations with the end goal of reducing the response times of emergency services. We also release the largest high-quality speech dataset of more than 150 h for Romanian. Our architecture includes an Automatic Speech Recognition model to transcribe calls automatically and augment the operator’s notes, as well as a Speech Recognition model to classify the caller’s emotions. We achieve state-of-the-art results on both tasks, while our demonstrator is designed to be integrated with the Romanian emergency system