Proceedings of the 2012 Workshop on Ambient Intelligence Infrastructures (WAmIi)

This is a technical report including the papers presented at the Workshop on Ambient Intelligence Infrastructures (WAmIi) that took place in conjunction with the International Joint Conference on Ambient Intelligence (AmI) in Pisa, Italy on November 13, 2012. The motivation for organizing the workshop was the wish to learn from past experience on Ambient Intelligence systems, and in particular, on the lessons learned on the system architecture of such systems. A significant number of European projects and other research have been performed, often with the goal of developing AmI technology to showcase AmI scenarios. We believe that for AmI to become further successfully accepted the system architecture is essential

Proceedings of the 2012 Workshop on Ambient Intelligence Infrastructures (WAmIi)

This is a technical report including the papers presented at the Workshop on Ambient Intelligence Infrastructures (WAmIi) that took place in conjunction with the International Joint Conference on Ambient Intelligence (AmI) in Pisa, Italy on November 13, 2012. The motivation for organizing the workshop was the wish to learn from past experience on Ambient Intelligence systems, and in particular, on the lessons learned on the system architecture of such systems. A significant number of European projects and other research have been performed, often with the goal of developing AmI technology to showcase AmI scenarios. We believe that for AmI to become further successfully accepted the system architecture is essential

Towards a service-oriented architecture for a mobile assistive system with real-time environmental sensing

Dalian Key Lab. of Smart Medical and Healthcare, Computer Science Department, Dalian University, China,With the growing aging population, age-related diseases have increased considerably over the years. In response to these, ambient assistive living (AAL) systems are being developed and are continually evolving to enrich and support independent living. While most researchers investigate robust activity recognition (AR) techniques, this paper focuses on some of the architectural challenges of the AAL systems. This work proposes a system architecture that fuses varying software design patterns and integrates readily available hardware devices to create wireless sensor networks for real-time applications. The system architecture brings together the service-oriented architecture (SOA), semantic web technologies, and other methods to address some of the shortcomings of the preceding system implementations using off-the-shelf and open source components. In order to validate the proposed architecture, a prototype is developed and tested positively to recognize basic user activities in real time. The system provides a base that can be further extended in many areas of AAL systems, including composite AR

Noise Data Visualization and Identification Project

This project aims to produce a space and time map of noise levels within a city using data gathered from sensors, with the goal of identifying noise hot spots and quiet zones. It also includes a noise identification module that attempts to classify reported sound data

Enhancing Mobile Data Collection Applications with Sensing Capabilities

Over the past years, using smart mobile devices for data collection purposes has become ubiquitous in many application domains, replacing traditional pen-and-paper based data collection approaches. However, in many cases, modern approaches only aim to replicate traditional data collection instruments (e.g., paper-based questionnaires) in a digital from (e.g., smartphone surveys). Thereby, the full potential of smart mobile devices is often not fully exploited. Most modern smart mobile devices comprise a variety of sensing capabilities, which may provide valuable data, and thus insights. In addition, external sensors and devices may be easily connected to become part of the overall data collection process. In order to integrate sensing functionality into existing data collection applications, one has to address each desired sensor manually from within the application, which may cause severe development effort. Alternatively one can fall back on dedicated sensing frameworks to perform sensing operations. However, the latter are often targeted towards one specific mobile platform (e.g., iOS or Android) or lack required functionality, which may also lead to unnecessary development overhead when implementing mobile data collection applications. To cope with these issues, a cross-platform mobile sensing framework that can be used within large-scale mobile data collection scenarios was developed in the context of this thesis. Thereby, an in-depth look at existing mobile sensing frameworks as well as common use case scenarios is taken. Further, requirements derived from the latter are explicitly stated and were taken into consideration in the course of the overall development process. The latter is documented and discussed in detail in the course of this thesis, including the design of a framework architecture, implementation details and the integration of the framework into mobile data collection applications

Heart Failure Monitoring System Based on Wearable and Information Technologies

In Europe, Cardiovascular Diseases (CVD) are the leading source of death, causing 45% of all deceases. Besides, Heart Failure, the paradigm of CVD, mainly affects people older than 65. In the current aging society, the European MyHeart Project was created, whose mission is to empower citizens to fight CVD by leading a preventive lifestyle and being able to be diagnosed at an early stage. This paper presents the development of a Heart Failure Management System, based on daily monitoring of Vital Body Signals, with wearable and mobile technologies, for the continuous assessment of this chronic disease. The System makes use of the latest technologies for monitoring heart condition, both with wearable garments (e.g. for measuring ECG and Respiration); and portable devices (such as Weight Scale and Blood Pressure Cuff) both with Bluetooth capabilitie

Noise Data Visualization and Identification Project

This project aims to produce a space and time map of noise levels within a city using data gathered from sensors, with the goal of identifying noise hot spots and quiet zones. It also includes a noise identification module that attempts to classify reported sound data

Smart information desk system with voice assistant for universities

This article aims to develop a smart information desk system through a smart mirror for universities. It is a mirror with extra capabilities of displaying answers for academic inquiries such as asking about the lecturers’ office numbers and hours, exams dates and times on the mirror surface. In addition, the voice recognition feature was used to answer spoken inquiries in audio responds to serve all types of users including disabled ones. Furthermore, the system showed general information such as date, weather, time and the university map. The smart mirror was connected to an outdoor camera to monitor the traffics at the university entrance gate. The system was implemented on a Raspberry Pi 4 model B connected to a two-way mirror and an infrared (IR) touch frame. The results of this study helped to overcome the problem of the information desk absence in the university. Therefore, it helped users to save their time and effort in making requests for important academic information