Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data

Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.

HMD - Praxis der Wirtschaftsinformatik - Smart City

Der Begriff Smart City oder Ubiquitous City bezeichnet die Nutzung von Informations- und Kommunikationstechnologien in Städten und Agglomerationen, um den sozialen und ökologischen Lebensraum nachhaltig zu entwickeln. Dazu zählen z.B. Projekte zur Verbesserung der Mobilität, Nutzung intelligenter Systeme für Wasser- und Energieversorgung, Förderung sozialer Netzwerke, Erweiterung politischer Partizipation, Ausbau von Entrepreneurship, Schutz der Umwelt sowie Erhöhung von Sicherheit und Lebensqualität. Das Themenheft widmet sich der Vielfalt dieser webbasierten Entwicklungen und berichtet über erste Erfahrungen von Pionierprojekten aus den folgenden Anwendungsfeldern: Smart Mobility, Smart Energy, Smart Economy, Smart Environment, Smart Governance, Smart Participation und Smart Living. Das Heft soll dazu dienen, den State of the Art der intelligenten Nutzung von Webtechnologien für den urbanen Raum aufzuzeigen, um damit Chancen und Risiken aufzudecken.

Associations of self-compassion and global self-esteem with positive and negative affect and stress reactivity in daily life: Findings from a smart phone study

The present study examined trait self-compassion and trait self-esteem in relation to positive (PA) and negative affect (NA), as well as their associations with stress reactivity in daily life. One hundred and one subjects completed questionnaires on perceived stress and affect twice a day for 14 consecutive days on smart phones. Results indicated that self-compassion and global self-esteem were positively related to PA and negatively to NA. After controlling for self-esteem, self-compassion remained significantly associated with PA and NA, whereas self-esteem was no longer associated with PA and NA after controlling for self-compassion. Furthermore, results indicated that self-compassion buffered the effect of stress on NA, whereas this was not the case for global self-esteem. Neither self-compassion nor self-esteem moderated the relation of stress on PA in separate models. The results of the present study add to the growing literature regarding beneficial relations of self-compassion and psychological well-being and further emphasize the distinction of self-compassion and global self-esteem.

Smart Hybrid Polymers for Advanced Damascene Electroplating: Combination of Superfill and Leveling Properties

A successful bottom-up fill of single Damascene test features is achieved by using a two-component additive package consisting of bis-(sodium-sulfopropyl)-disulfide (SPS) and Imep polymers (polymerizates of imidazole and epichlorohydrin). In addition, a remarkable leveling effect is observed. Clearly, the Imep additive combines bottom-up fill capabilities with leveling characteristics in one single polymer component. These unique hybrid properties of the Imep are rationalized on the basis of an extended N-NDR (N-shaped negative differential resistance) being present in the linear-sweep voltammogram of the SPS/Imep additive system during Cu electrodeposition.

George Thomas Smart, Brustbild

Signatur des Originals: S 36/G02260

Evaluation of therapist and client language in Motivational Interviewing (MI) sessions: A secondary analysis of data from the Southern Methodist Alcohol Research Trial (SMART) study

In the United States, “binge” drinking among college students is an emerging public health concern due to the significant physical and psychological effects on young adults. The focus is on identifying interventions that can help decrease high-risk drinking behavior among this group of drinkers. One such intervention is Motivational interviewing (MI), a client-centered therapy that aims at resolving client ambivalence by developing discrepancy and engaging the client in change talk. Of late, there is a growing interest in determining the active ingredients that influence the alliance between the therapist and the client. This study is a secondary analysis of the data obtained from the Southern Methodist Alcohol Research Trial (SMART) project, a dismantling trial of MI and feedback among heavy drinking college students. The present project examines the relationship between therapist and client language in MI sessions on a sample of “binge” drinking college students. Of the 126 SMART tapes, 30 tapes (‘MI with feedback’ group = 15, ‘MI only’ group = 15) were randomly selected for this study. MISC 2.1, a mutually exclusive and exhaustive coding system, was used to code the audio/videotaped MI sessions. Therapist and client language were analyzed for communication characteristics. Overall, therapists adopted a MI consistent style and clients were found to engage in change talk. Counselor acceptance, empathy, spirit, and complex reflections were all significantly related to client change talk (p-values ranged from 0.001 to 0.047). Additionally, therapist ‘advice without permission’ and MI Inconsistent therapist behaviors were strongly correlated with client sustain talk (p-values ranged from 0.006 to 0.048). Simple linear regression models showed a significant correlation between MI consistent (MICO) therapist language (independent variable) and change talk (dependent variable) and MI inconsistent (MIIN) therapist language (independent variable) and sustain talk (dependent variable). The study has several limitations such as small sample size, self-selection bias, poor inter-rater reliability for the global scales and the lack of a temporal measure of therapist and client language. Future studies might consider a larger sample size to obtain more statistical power. In addition the correlation between therapist language, client language and drinking outcome needs to be explored.^

Expanding cities and expanding waistlines: Urban sprawl and its impact on obesity, how the adoption of smart growth statutes can build healthier and more active communities

For decades, American towns and cities have expanded from their established cores into the surrounding rural areas. U.S. population has grown but the land that we use has grown at an even faster pace, and our country has now become a largely suburban nation. Americans moved and continue to move out to the suburbs in search of better lives – for clean and healthy living, for larger homes, and for better resources. In many ways and for many Americans, the suburban lifestyle has been a great success. However, there are some unintended public health consequences of urban sprawl that must be recognized. As most Americans no longer walk or bicycle, increasingly sedentary lifestyles now contribute to greater levels of obesity, diabetes and other associated chronic diseases. This thesis reviewed the impacts of urban sprawl on the public's health specifically, as sprawl relates to decreased physical activity rates and increased obesity rates. The health effects and their connection with sprawl were identified, and available evidence was reviewed. Finally, this thesis described legal and policy solutions for addressing the health effect through improving the design of our built environment and by recommending that governments adopt and implement Smart Growth statutes that incorporate a public health component and require public health involvement. ^

Enhancing Interaction With Smart Objects Throught Mobile Devices

Interaction with smart objects can be accomplished with different technologies, such as tangible interfaces or touch computing, among others. Some of them require the object to be especially designed to be 'smart', and some other are limited in the variety and complexity of the possible actions. This paper describes a user-smart object interaction model and prototype based on the well known event-condition-action (ECA) reasoning, which can work, to a degree, independently of the intelligence embedded into the smart object. It has been designed for mobile devices to act as mediators between users and smart objects and provides an intuitive means for personalization of object's behavior. When the user is close to an object, this one publishes its 'event & action' capabilities to the user's device. The user may accept the object's module offering, which will enable him to configure and control that object, but also its actions with respect to other elements of the environment or the virtual world. The modular ECA interaction model facilitates the integration of different types of objects in a smart space, giving the user full control of their capabilities and facilitating creative mash-uping to build customized functionalities that combine physical and virtual actions

Moving Object Detection for Real-Time High-Quality Lightweight Applications on Smart Cameras

Here, a novel and efficient strategy for moving object detection by non-parametric modeling on smart cameras is presented. Whereas the background is modeled using only color information, the foreground model combines color and spatial information. The application of a particle filter allows the update of the spatial information and provides a priori information about the areas to analyze in the following images, enabling an important reduction in the computational requirements and improving the segmentation results

Biomechanics of smart wings in a bat robot: morphing wings using SMA actuators

This paper presents the design of a bat-like micro aerial vehicle with actuated morphing wings. NiTi shape memory alloys (SMAs) acting as artificial biceps and triceps muscles are used for mimicking the morphing wing mechanism of the bat flight apparatus. Our objective is twofold. Firstly, we have implemented a control architecture that allows an accurate and fast SMA actuation. This control makes use of the electrical resistance measurements of SMAs to adjust morphing wing motions. Secondly, the feasibility of using SMA actuation technology is evaluated for the application at hand. To this purpose, experiments are conducted to analyze the control performance in terms of nominal and overloaded operation modes of the SMAs. This analysis includes: (i) inertial forces regarding the stretchable wing membrane and aerodynamic loads, and (ii) uncertainties due to impact of airflow conditions over the resistance–motion relationship of SMAs. With the proposed control, morphing actuation speed can be increased up to 2.5 Hz, being sufficient to generate lift forces at a cruising speed of 5ms−1.

Model-Driven Methodology for Rapid Deployment of Smart Spaces based on Resource-Oriented Architectures

Advances in electronics nowadays facilitate the design of smart spaces based on physical mash-ups of sensor and actuator devices. At the same time, software paradigms such as Internet of Things (IoT) and Web of Things (WoT) are motivating the creation of technology to support the development and deployment of web-enabled embedded sensor and actuator devices with two major objectives: (i) to integrate sensing and actuating functionalities into everyday objects, and (ii) to easily allow a diversity of devices to plug into the Internet. Currently, developers who are applying this Internet-oriented approach need to have solid understanding about specific platforms and web technologies. In order to alleviate this development process, this research proposes a Resource-Oriented and Ontology-Driven Development (ROOD) methodology based on the Model Driven Architecture (MDA). This methodology aims at enabling the development of smart spaces through a set of modeling tools and semantic technologies that support the definition of the smart space and the automatic generation of code at hardware level. ROOD feasibility is demonstrated by building an adaptive health monitoring service for a Smart Gym.

Design and modeling of the multi-agent robotic system: SMART

This article presents the design, kinematic model and communication architecture for the multi-agent robotic system called SMART. The philosophy behind this kind of system requires the communication architecture to contemplate the concurrence of the whole system. The proposed architecture combines different communication technologies (TCP/IP and Bluetooth) under one protocol designed for the cooperation among agents and other elements of the system such as IP-Cameras, image processing library, path planner, user Interface, control block and data block. The high level control is modeled by Work-Flow Petri nets and implemented in C++ and C♯♯. Experimental results show the performance of the designed architecture.

Ubiquitous green computing techniques for high demand applications in smart environments

Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these applications imply the usage of data centers. Research has paid much attention to the energy consumption of the sensor nodes in WSNs infrastructures. However, supercomputing facilities are the ones presenting a higher economic and environmental impact due to their very high power consumption. The latter problem, however, has been disregarded in the field of smart environment services. This paper proposes an energy-minimization workload assignment technique, based on heterogeneity and application-awareness, that redistributes low-demand computational tasks from high-performance facilities to idle nodes with low and medium resources in the WSN infrastructure. These non-optimal allocation policies reduce the energy consumed by the whole infrastructure and the total execution time.