The reflective mobile agent paradigm implemented in a smart office environment

Ubiquitous systems will integrate computers invisibly and unobtrusively in everyday objects. Data will be catched from single or multi-sensor devices and will be used for context extraction. New location-based services will be adapted to user preferences. For this the ubiquitous system needs to know user profiles, likings, and habits. As the user moves, these information must be made available at the new location of the user. Either the user carries the data on wearable or portable computers or the smart environment takes responsibility for transporting them. The amount of new devices and services makes an efficient use by centralized systems very difficult. The idea presented in this paper is that a virtual reflection of the user represented by a mobile agent accompanying in the smart environment. Mobile agents offer a possibility to encapsulate information of a person and the person’s preferences and perform location-based services of the ubiquitous system in the name of the user. Security and privacy are major concerns of such an agent system. This paper describes a ubiquitous mobile agent system named UbiMAS which has security extensions to provide high protection of agents and significant personal data. UbiMAS is applied in the smart doorplate project as part of a smart office environment.     

A smart surface inspection system using faster R-CNN in cloud-edge computing environment

Automated surface inspection has become a hot topic with the rapid development of machine vision technologies. Traditional machine vision methods need experts to carefully craft image features for defect detection. This limits their applications to wider areas. The emerging convolutional neural networks (CNN) can automatically extract features and yield good results in many cases. However, the CNN-based image classification methods are more suitable for flat surface texture inspection. It is difficult to accurately locate small defects in geometrically complex products. Furthermore, the computational power required in CNN algorithms is usually high and it is not efficient to be implemented on embedded hardware. To solve these problems, a smart surface inspection system is proposed using faster R-CNN algorithm in the cloud-edge computing environment. The faster R-CNN as a CNN-based object detection method can efficiently identify defects in complex product images and the cloud-edge computing framework can provide fast computation speed and evolving algorithm models. A real industrial case study is presented to illustrate the effectiveness of the proposed method. The results show that the proposed method can provide high detection accuracy within a short time.     

Flexible and robust multimodal interfaces for universal access

Multimodal interfaces are inherently flexible, which is a key feature that makes them suitable for both universal access and next-generation mobile computing. Recent studies also have demonstrated that multimodal architectures can improve the performance stability and overall robustness of the recognition-based component technologies they incorporate (e.g., speech, vision, pen input). This paper reviews data from two recent studies in which a multimodal architecture suppressed errors and stabilized system performance for accented speakers and during mobile use. It concludes with a discussion of key issues in the design of future multimodal interfaces for diverse user groups.     

Design of a user-support system for vision information using a smart phone

In this paper, we design a user-support system for vision information using smart phones. When the user takes a picture of a target using the smart phone camera, our system can recognize the image of the target and recommend a suitable service to the user. The system executes simple image analysis and determines a suitable service for the target image. The simple image analysis can extract 13 parameters (e.g., color information (RGB), number of intersections, depth of intersection, line width, and line depth). We use machine learning to classify the parameters into each service. In our research, we use a Support Vector Machine as a learning machine tool. Our system design provides user support for several services such as translation, barcode readers, and diagnosis of skin images and demonstrates the effectiveness of our research.     

Finding misplaced items using a mobile robot in a smart home environment

Frontiers of Information Technology & Electronic Engineering - Smart homes can provide complementary information to assist home service robots. We present a robotic misplaced item finding (MIF)...     

基于Microduino的智能家居环境监测系统设计

在智能家居中,环境监测与数据采集是使家居实现智能的关键步骤。本文设计的监测系统使用近年来新出现的Microduino系列套件制作,具有体积小、操作方便、功耗低、可随意移动的特点。利用价格便宜、市面上常见的温湿度传感器,结合Microduino套件中的模块,组合成采集节点与汇聚节点,并充分发挥Microduino的优势,使其不同于其他芯片所搭建的数据传输系统。     

Design and implementation of a user-support system for scheduling using a smart phone

In recent years, the ability to manage schedules using a mobile device equipped with a touch panel has increased. However, when one wishes to add a new event to the schedule book while taking into account the transit time for an existing event, it is necessary to switch to another application or website. In this study, we design a system that determines automatically whether the new event can be added. If it is impossible to add the event, the system proposes a time range in which events can be added.     

Effective quality factors of multimodal interaction in simple and complex tasks of using a smart television

Influencing quality factors, related to the user and system, need to be considered when building a well-designed multimodal interaction system. User groups, access to input modes and tasks were defined as the user and system factors to examine effective factors of multimodal interaction with a smart TV, and its input modes consisted of voice, arrow key, and motion-based pointer modes and their combinations. User group 1 had experience of multimodal interaction with another device, while user group 2 had only experience of unimodal interaction. In addition, the sequential/simultaneous input modes and simple/complex tasks were considered as the system factors. Depending on the task complexity, two experiments were conducted. Nine input modes (three unimodes and six multimodes), sequentially and simultaneously given to both user groups, were investigated for the simple task of menu traversal and the complex task of manipulating broadcasting content, menu traversal, and web content navigation. A subjective rating of the level of preference was recorded in the sequential input mode using a modified Likert-type rating scale, while each participant’s preferred mode was observed in the simultaneous scenario. Additionally, the completion time and error rate were measured in both experiments. When performing the simple task, user group 1 used multimodes more so than group 2. However, in the complex task, both user groups preferred multimodes when modes were simultaneously presented. Considering effective quality factors, input modes of a smart TV should be simultaneously provided with a voice and motion-based pointer multimode.     

Building a smart lecture-recording system using MK-CPN network for heterogeneous data sources

Neural Computing and Applications - Nowadays, lecture-recording systems play a vital role in collecting spoken discourse for e-learning. However, in view of the growing development of e-learning,...     

A system for efficient motor learning using multimodal augmented feedback

Numerous studies have established that using various forms of augmented feedback improves human motor learning. In this paper, we present a system that enables real-time analysis of motion patterns and provides users with objective information on their performance of an executed set of motions. This information can be used to identify individual segments of improper motion early in the learning process, thus preventing improperly learned motion patterns that can be difficult to correct once fully learned. The primary purpose of the proposed system is to serve as a general tool in the research on impact of different feedback modalities on the process of motor learning, for example, in sports or rehabilitation. The key advantages of the system are high-speed and high-accuracy tracking, as well as its flexibility, as it supports various types of feedback (auditory and visual, concurrent or terminal). The practical application of the proposed system is demonstrated through the example of learning a golf swing.     

Vehicle navigation in GPS denied environment for smart cities using vision sensors

The transformation of the existing urban environment in digital smart cities has become a reality, which aimed to transform daily life activities into automated processes for the ease in human efforts and reduction in effort time. Vision based sensors are commonly used for monitoring cities, which acquire a huge amount of diverse data and store them for further computer vision processing. In this article, we aim to explore whether and how to navigate a vehicle using cost effective means (vision based sensors) in smart cities without using the calibrated sensors and Global Positioning System (GPS). Vehicle localization and navigation require on-board calibrated sensors and reliable GPS link. In an urban environment, these sensors fail to perform well in: indoor environment (tunnels), crowded and congested areas, and severe weather conditions. The most effective technique used for vision based navigation depends on image registration. The challenges of a successful and effective registration are: sufficient illumination in the environment, dominance of static scene over moving objects, high textured ratio to allow apparent motion and necessary scene overlap between consecutive frames. We proposed a novel approach for vehicle navigation based on vision sensors using modified normalized phase correlation. In the proposed approach, the distinction between textured and texture less surface is based on the identification of corresponding features. In this regard, the Gram polynomial basis function is used to remove the Gibbs error problem generated due to peak in the registration process. Similarly, entropy based tensor approximation is used to remove outliers for robust image registration. Experiments performed in real time during test drives show excellent results with respect to estimated position accuracy in comparison with GPS calculated data.     

Robust one-time password authentication scheme using smart card for home network environment

Due to the exponential growth of the Internet users and wireless devices, interests on home networks have been enormously increased in recent days. In digital home networks, home services including remote access and control to home appliances as well as services offered by service providers are alluring. However, the remote control services cause digital home networks to have various security threats. Hence, for digital home networks, robust security services, especially remote user authentication, should be considered. This paper presents a robust and efficient authentication scheme based on strong-password approach to provide secure remote access in digital home network environments. The proposed scheme uses lightweight computation modules including hashed one-time password and hash-chaining technique along with low-cost smart card technology. It aims to satisfy several security requirements including stolen smart card attack and forward secrecy with lost smart card as well as functional requirements including no verification table and no time synchronization. Comparing with the existing representative schemes, it can be validated that the proposed scheme is more robust authentication mechanism having better security properties. We have conducted formal verification of the proposed scheme.     

Interactive job sequencing system for small make-to-order manufacturers under smart manufacturing environment

Peer-to-Peer Networking and Applications - Production scheduling is an important research topic widely studied during past few decades. However, many manufacturers still fail to successfully deploy...     

Case-based context ontology construction using fuzzy set theory for personalized service in a smart home environment

To provide context-based personalized services utilizing smart appliances in a smart home environment, we propose a framework for PersonAlized Service disCovery Using FuZZY-based CBR and Context Ontology (PASCUZZY). Basically, the PASCUZZY framework is implemented on case-based context ontology. To generate and manage the case instances on the case-based context ontology, we adopt the fuzzy set theory to transpose numerical-type context data sensed from the surrounding environment. The context is transposed to linguistic-type context instances on the context ontology. In addition, to formalize and manage the context and services as multi-attributed data, the context ontology was developed reflecting the structure of cases borrowed from case-based reasoning. Furthermore, we propose adaptation methods to adjust the generic fuzzy membership functions depending on the inhabitants’ context. It is performed by modifying the values of the membership number and/or modifying the numbers of the linguistic terms that are based on the inhabitants’ context to affect the membership numbers. The adapted membership functions return the personalized degree of memberships depending on the specialized context of a specific fuzzy variable. Inevitably, the number of cases on the case-based context ontology will be increased from time to time. We apply Ward’s method not only to reduce the search effort via a hierarchical clustering on the case-based context ontology but also to find the most similar service as a solution to the new context. To verify the superiority of the PASCUZZY framework, we perform two kinds of evaluations. First, we evaluate the effectiveness of the adaptation of the fuzzy membership functions. Second, we verify the effectiveness of the application of a clustering method to the case instances of the case-based context ontology to identify the most similar service. Results of the experiment verified the effectiveness and superiority of the PASCUZZY framework.     

Labscape: a smart environment for the cell biology laboratory

Labscape is a smart environment that we designed to improve the experience of people who work in a cell biology laboratory. Our goal in creating it was to simplify, laboratory work by making information available where it is needed and by collecting and organizing data where and when it is created into a formal representation that others can understand and process. By helping biologists produce a more complete record of their work with less effort, Labscape is designed to foster improved collaboration in conjunction with increased individual efficiency and satisfaction. A user-driven system, although technologically conservative, embraces a central goal of ubiquitous computing: to enhance the ability to perform domain tasks through fluid interaction with computational resources. Smart environments could soon replace the pen and paper commonly used in the laboratory setting.     

Ant-based service selection framework for a smart home monitoring environment

Selecting ambient media services in a smart home monitoring environment is challenging. Services in such an environment should be ubiquitous, adaptive, and robust with respect to access and delivery. Many different techniques exist for selecting services in smart environments, for example, dynamic programming, genetic algorithms, and fuzzy logic. However, existing approaches to service selection fail to address the dynamic nature of the services and the requirement of considering the user context and user satisfaction. We address this issue by proposing an ant-inspired service selection framework based on dynamic user preferences and satisfaction. This ant-inspired approach is robust to failures and adaptive to dynamic context. The proposed framework enables different categories of residents (e.g., elderly people, fathers with children, mothers, and so on) to access various media services in such a way that their experiences are optimized with regard to their surrounding environment. Experimental results demonstrate the viability of the proposed framework.     

Infrequent pattern mining in smart healthcare environment using data summarization

A summarization technique creates a concise version of large amount of data (big data!) which reduces the computational cost of analysis and decision-making. There are interesting data patterns, such as rare anomalies, which are more infrequent in nature than other data instances. For example, in smart healthcare environment, the proportion of infrequent patterns is very low in the underlying cyber physical system (CPS). Existing summarization techniques overlook the issue of representing such interesting infrequent patterns in a summary. In this paper, a novel clustering-based technique is proposed which uses an information theoretic measure to identify the infrequent frequent patterns for inclusion in a summary. The experiments conducted on seven benchmark CPS datasets show substantially good results in terms of including the infrequent patterns in summaries than existing techniques.     

Navigational tools for desktop virtual environment interfaces

Desktop systems typically rely on a two-dimensional (2D) software interface and general purpose hardware (mouse, keyboard) for interaction with a three-dimensional (3D) virtual environment. These interfaces must provide all the functionality required to navigate through and interact with the virtual environment, yet research into the usability aspects of the tools presented on these software interfaces indicates that the majority of users experience some degree of frustration when using them to perform even relatively simple tasks. This paper begins with a study of usability issues for interfaces to virtual environments on desktop systems, and details a series of experiments performed to evaluate the usability of a number of navigational tools. Participants were tested on the time taken to complete a number of navigational tasks with a series of interfaces presenting different navigational tools. The tools presented were a speed control function, a you-are-here (YAH) map, a function enabling the user to mark and teleport to any location within the presented environment, and an undo function. Results indicate that the visual presentation of navigational aids improves navigation performance, in terms of the time taken to complete tasks, and also improves user satisfaction with the desktop system.     

Human gait assessment using a 3D marker-less multimodal motion capture system

Multimedia Tools and Applications - Gait analysis is the measurement, processing and systematic interpretation of biomechanical parameters that characterize human locomotion. It supports the...