Performance evaluation of ambient services by combining robotic frameworks and a smart environment platform

We know about word play, verbal jokes, and about humor that appears spontaneously in conversations. This humor is studied in computational linguistics, together with issues such as verbal incongruities, ambiguities, irony and sarcasm. These appearances of humor are also part of computational humor studies, where a broader view is taken, that is, a view that includes artificial intelligence, reasoning, common-sense and context representations, and machine learning. But there are other kinds of humor. We can laugh about events that appear in our physical world. We can play an active role in having these events happening. Obviously, they can be accompanied with verbal comments and interaction. Nowadays physical worlds are equipped with multimodal sensors and multimedia actuators. Environments do not only have human inhabitants, but also tangibles, wearables, social robots and 2D and 3D display possibilities that can help to create changes in the world that is perceived by its human inhabitants. The possibility of humor creation can be transferred from the purely linguistics worlds of text and verbal exchanges to virtual, mixed, augmented and physical reality intelligent environments equipped with sensors and actuators that can help to create and control humorous events. In this paper we introduce this research area and we survey what is available in humor research literature that may help to establish this research area. Applications of this research include avatar behavior in videogames, robot and product behavior in entertainment, social, and game environments, and in smart physical environments that allow for playful and humorous events.

One of the functionalities a service robot should have, to work in a smart environment, is object recognition and handling of objects. Many researchers have attempted to make service robots recognize objects in natural environments but no conventional vision systems can recognize target objects in complex scenes. We built a prototype smart environment in our research building at Korea Institute of Industrial Technology (KITECH) to demonstrate the feasibility that a service robot with few sensors can provide reliable services by interacting with an environment full of smart devices through wireless sensor network communications. In this paper, we address the issues of how to develop an object recognition system for our RoboMaidHome project. Our object recognition system can not only recognize objects with no need of a previous training stage but make the service robot light-weight with minimum hardware and software requirements while working well in a smart home environment. In addition, the matching process for object recognition is simple since only a few image processing techniques are employed. Our object recognition scheme on the basis of MPEG-7 visual descriptors is under development and includes color, texture, and shape. It will also be incorporated into our mobile service robotics system.

The experience of full automation without explicit user direction may induce anxiety among smart space users. The use of explicit mediators between users and fully automated systems may help to mitigate users’ anxiety. While robots mediators are one possible solution, several issues remain, including high complexity and limited collaboration between robots and smart space platforms, reducing overall system reliability. This paper proposes the Integrated Control Architecture for Robotic mediator in Smart environments (ICARS) as a solution to improve the integration and reliability of robot mediators within automated smart spaces. Assuming relatively thin network robots as robotic mediators to enable a wide distribution with less cost, ICARS provides a well-organized software framework consisting of three layers to integrate robots and smart spaces: a flexible communication/device model, an adaptive service model for the integrated robot control architecture, and a behavior-based high-level collaboration model. In this paper, we also present details of the design, implementation, and an application scenario conducted with ICARS. The results show that ICARS enables flexible integration of the diverse devices associated with robots and environments, adaptive service provision for collaborative services, and easier development of high-level collaborative applications with decent performance.

The Internet of Things (IoT) is envisioned as a ubiquitous computing infrastructure in which everything becomes connected, enabling gigantic information exchange among Things and people. These connected smart Things generate an enormous amount of data which need to be efficiently managed to form a unified global IoT. Unfortunately, due to the lack of acceptable open standards, communication protocols, and support for device/service discovery, the recent IoT deployments in smart environments (e.g., smart home, smart building, smart city) are posing imperative challenges related to interoperability, discovery, and the configuration of deployed objects, since the number of objects is expected to grow over time. Therefore, it is of utmost importance to provide open and scalable solutions for the discovery of devices (i.e., Things), their configuration, and data management. This paper introduces an open and scalable IoT platform by adopting the modular characteristics of edge computing for smart environments. This paper: (i) performs a systematic literature review of IoT-based infrastructures and analyzes the scalability requirements; (ii) proposes a layered IoT platform for smart environments that fosters heterogeneity, interoperability, discovery, and scalability; and (iii) demonstrates the applicability of the proposed solution by relying on a comprehensive study of a Väre smart building use case at Aalto University.

In this paper an experiment aimed to demonstrate that a distributed system of embedded microcontrollers is presented. In the experiment described, didactic mobile robot, People Bot from mobile robots has been used, but the entire solution can be easily ported for the implementation of an intelligent wheelchair, capable either to carry an elderly or disabled person, or to move independently in a smart environment, as a sensorial extension of the assisted individual. A number of control modules are located on the mobile robot while others are deployed in an ¿intelligent environment¿ can significantly reduce the cost of developing a robotic assistant for the elderly and disabled. The structure of the experimental setup is described in detail, as well as the main algorithms used for each individual task: path following, obstacle avoidance, data acquisition. An obstacle avoidance algorithm, based on ricochet method, named ¿the bubble rebound algorithm¿, is presented, too.

Efficient resource and energy management is a key research and business area in todays IT markets. Cyber-physical ecosystems, like smart homes (SHs) and smart Environments (SEs) get interconnected, the efficient allocation of resources will become essential. Machine Learning and Semantic Web techniques for improving resource allocation and management are the focus of our research. They allow machines to process information on all levels, inferring expressive knowledge from raw data, in particular resource predictions from usage patterns. Our aim is to devise a novel approach for a machine learning (ML) and resource Management (RM) framework in SEs. It combines ML and Semantic Web techniques and integrates user interaction The main objective is to enable the creation of platforms that decrease the overall resource consumption by learning and predicting various usage patterns, and furthermore making decisions based on user-feedback. For this purpose, we evaluate recent research and applications, elicit framework requirements, and present a framework architecture. The approach and components are assessed and a prototype implementation is described.

The study aims to describe the implementation of a primary practitioner physiotherapy service within a large regional ED and to evaluate its impact on waiting time and length of stay. Integration and scope of practice of the physiotherapy service within the ED were described. Retrospective analysis of waiting time and length of stay data for the 3 years, 1 October 2008 to 30 September 2011, was performed. The performance of the physiotherapy service was compared with the Australasian College for Emergency Medicine (ACEM) waiting time guidelines, the Victorian Department of Health length of stay targets and to a similar group of patients seen by medical staff. The primary practitioner physiotherapy service saw 5641 patients of which 33% were less than 18 years old. The most common presentations seen by the service were limb fractures, soft tissue injuries and low back pain. Ninety-two per cent of patients were seen within the ACEM waiting time guidelines, and 91% of patients who went home were discharged within 4 h. Non-randomised comparisons with similar patients seen by medical staff indicated that patients seen by the physiotherapy practitioner service had shorter waiting times and length of stay. The current study found that patients with musculoskeletal problems seen by a primary practitioner physiotherapy service had improved waiting times and length of stay relative to ACEM and Victorian Department of Health targets, and though constrained by a retrospective non-randomised design, to a similar group of patients seen by medical staff. Further evaluation of the physiotherapy practitioner service is required.

Smart homes can provide complementary information to assist home service robots. We present a robotic misplaced item finding (MIF) system, which uses human historical trajectory data obtained in a smart home environment. First, a multi-sensor fusion method is developed to localize and track a resident. Second, a path-planning method is developed to generate the robot movement plan, which considers the knowledge of the human historical trajectory. Third, a real-time object detector based on a convolutional neural network is applied to detect the misplaced item. We present MIF experiments in a smart home testbed and the experimental results verify the accuracy and efficiency of our solution.

The use of Smart Environments in the delivery of pervasive care is a research topic that has witnessed increasing interest in recent years. These environments aim to deliver pervasive care through ubiquitous sensing by monitoring the occupants Activities of Daily Living. In order for these environments to succeed in achieving their goal, it is crucial that sensors deployed in the environment perform faultlessly. In this research we investigate addressing anomalous sensor behavior through the utilization of a mobile robot. The robot’s role is twofold; it must provide substitution in the presence of suspected sensor faults and act as an observer of anomalous sensor behavior in order to understand the changes that occur in the behavior of sensors deployed within the environment over time. The aim of this work is to explore a paradigm shift to the use of Autonomic Ambient Assisted Living.We have discovered that the use of a mobile robot is a viable means of introducing this paradigm to a Smart Environment.

This article is concerned with 2D indoor environment mapping produced by a sensor data fusion algorithm. A measurement subsystem assembled on a mobile robot uses its sensors to gather data from its surroundings. In this article, an algorithm is proposed and evaluated to fuse data acquired by the following low-cost sensors: a visual sensor (a wireless webcam with a laser pointer) and three range finder sensors (two infrared units and a sonar transducer). The main steps of the proposed solution are: (a) at each accurate robot pose an occupancy grid (OG) probabilistic map is generated for each type of sensor, (b) the three OG maps are merged using competitive fusion and the RANSAC algorithm is employed to extract line segments, (c) the line segments are further processed using competitive and/or complementary fusion resulting in a feature-based map for each robot pose. The previous steps are repeated until all robots pose are computed. The feature-based maps for all robot poses are then merged using competitive fusion, and a final precise OG map of the environment is generated. The proposed algorithm was evaluated using data gathered by the SLAMVITA robot sensors in two small test environments. The experimental results have shown that the proposed algorithm was able to build precise maps of the test environments (error less than 1.5 %).

PurposeDespite increasing attentions to sustainable service supply chain management (SSSCM), a framework for performance evaluation of sustainable service only supply chain management (SSOSCM) is still missing. This paper tries to fill this gap and provides a novel conceptual framework.Design/methodology/approachThe articles related to SSSCM are fetched from the databases of SCOPUS and Web of Science. Analysis of 174 articles identified by the systematic literature review is further carried out.FindingsThis research identifies the sustainable practices for service only supply chain (SOSC) as environmental management, social management, economic management, customer management, health, safety and risk management, technical sustainability, institutional sustainability, information and technology management as well as two performance measurement criteria as operational performance and organizational performance. This paper provides a novel conceptual framework for the performance evaluation of SSOSCM. The results call for future exploration in the following three broad directions-(1) customer's perception, involvement and their behaviour towards sustainability in SOSC context; (2) trade-off, incentive mechanism and multilevel evaluation for achieving sustainability in SOSC and (3) sustainability in SOSC from various point of views.Practical implicationsThe managers can use the framework to assess the performance of the organization while researchers can explore the discussed research gaps.Originality/valueThis is the first paper that provides a novel conceptual framework for the performance evaluation of SSOSCM as well as potential future research directions.

The practical application of human nose for fragrance recognition is severely limited by the fact that our sense of smell is subjective and gets tired easily. Consequently, there is a significant need for an instrument that can be a substitution of the human sense of smell. Development of an electronic nose devices is an active area of research starting from pioneering research of Dodd and Persuad in the mid-1980s. Such systems are used in growing number of applications. They comprise an array of several electrochemical gas sensors with partial specificity and a pattern recognition algorithms. Since most of the existing types of sensors are characterized by low selectivity, they can all be used in the construction of electronic noses. Most electronic nose systems are based only on one type of gas sensors. However, different types of sensors have different advantages and disadvantages. In this article, an electronic nose system for the purpose of incorporating different types of sensors has been proposed developed. Such approach allows to benefit from advantages of different type of sensors, and thus improve the operation of the entire system.

During the last 2 years, a combined integrity-corrosion analysis technique was developed and implemented, for the assessment of high pressure gas wells, with the following objectives: To address variations in active damage mechanisms incidence, due to changes in operating conditions.To calculate metal loss rates on affected components.To assess fitness for service and estimate residual life. As a result of this approach, the following developments were possible: Increase in production rates without sensible risk increment due to corrosion and erosion-corrosion damage.Metal loss rates and thickness evolution prediction due to potentially active damage mechanisms.Specific fitness for service evaluation, identifying segments with eventual compromise and defining specific limits for metal loss.Residual life estimates, considering both potential leak and mechanical failures scenarios. Based on these results, the current Well Integrity Program was upgraded, including new prediction and mitigation methods, with focus on ensuring continuous fitness for service, safe operation, risk management and periodic performance evaluation. As key elements of this new program, specific plans were designed and initiated, including damage mechanisms monitoring and mitigation, well and pipeline inspection, preemptive maintenance and periodic risk and integrity evaluation.

Exploring the potential of a mobile eye tracker as an intuitive indoor pointing device: A case study in cultural heritage

PurposeTo describe a new approach to the performance evaluation and benchmarking of analytical laboratory services and their associated supply chains.Design/methodology/approachLife cycle and industrial process approaches are adapted for consideration of the environmental performance of multidisciplinary laboratories as found in large multifunctional facilities. Models are developed to facilitate performance evaluation.FindingsThe laboratory product model (LPM) considers laboratory service delivery from a whole‐of‐life perspective. It defines an information product as a standard unit of production that facilitates performance evaluation of laboratories using both normalised and absolute values. Performance evaluation boundaries are extended beyond the internal laboratory processes to incorporate the supply chain, i.e. from sample collection to the end use of the information product.Research limitations/implicationsApplication of the research is limited by the availability of relevant corporate data. Future work could address routine collection of data appropriate to environmental performance evaluation so as to reduce the need for extensive life cycle inventories.Practical implicationsFocus is on a practical approach to improving the environmental performance of laboratory services through objective evaluation of laboratory and facility performance. The research provides a means of comparing laboratories founded in different disciplines, e.g. chemistry and microbiology.Originality/valueAddresses laboratory supply chain issues by providing new tools for performance evaluation and benchmarking of laboratories. It uses new approaches to laboratory performance evaluation that help achieve sustainability.