Showing papers on "System integration published in 2015"

Materials that couple sensing, actuation, computation, and communication

Abstract: BACKGROUND The tight integration of sensing, actuation, and computation that biological systems exhibit to achieve shape and appearance changes (like the cuttlefish and birds in flight), adaptive load support (like the banyan tree), or tactile sensing at very high dynamic range (such as the human skin) has long served as inspiration for engineered systems. Artificial materials with such capabilities could enable airplane wings and vehicles with the ability to adapt their aerodynamic profile or camouflage in the environment, bridges and other civil structures that could detect and repair damages, or robotic skin and prosthetics with the ability to sense touch and subtle textures. The vision for such materials has been articulated repeatedly in science and fiction (“programmable matter”) and periodically has undergone a renaissance with the advent of new enabling technology such as fast digital electronics in the 1970s and microelectromechanical systems in the 1990s. ADVANCES Recent advances in manufacturing, combined with the miniaturization of electronics that has culminated in providing the power of a desktop computer of the 1990s on the head of a pin, is enabling a new class of “robotic” materials that transcend classical composite materials in functionality. Whereas state-of-the-art composites are increasingly integrating sensors and actuators at high densities, the availability of cheap and small microprocessors will allow these materials to function autonomously. Yet, this vision requires the tight integration of material science, computer science, and other related disciplines to make fundamental advances in distributed algorithms and manufacturing processes. Advances are currently being made in individual disciplines rather than system integration, which has become increasingly possible in recent years. For example, the composite materials community has made tremendous advances in composites that integrate sensing for nondestructive evaluation, and actuation (for example, for shape-changing airfoils), as well as their manufacturing. At the same time, computer science has created an entire field concerned with distributed algorithms to collect, process, and act upon vast collections of information in the field of sensor networks. Similarly, manufacturing has been revolutionized by advances in three-dimensional (3D) printing, as well as entirely new methods for creating complex structures from unfolding or stretching of patterned 2D composites. Finally, robotics and controls have made advances in controlling robots with multiple actuators, continuum dynamics, and large numbers of distributed sensors. Only a few systems have taken advantage of these advances, however, to create materials that tightly integrate sensing, actuation, computation, and communication in a way that allows them to be mass-produced cheaply and easily. OUTLOOK Robotic materials can enable smart composites that autonomously change their shape, stiffness, or physical appearance in a fully programmable way, extending the functionality of classical “smart materials.” If mass-produced economically and available as a commodity, robotic materials have the potential to add unprecedented functionality to everyday objects and surfaces, enabling a vast array of applications ranging from more efficient aircraft and vehicles, to sensorial robotics and prosthetics, to everyday objects like clothing and furniture. Realizing this vision requires not only a new level of interdisciplinary collaboration between the engineering disciplines and the sciences, but also a new model of interdisciplinary education that captures both the disciplinary breadth of robotic materials and the depth of individual disciplines.

Quality and productivity outcomes relating to continuous integration in GitHub

Abstract: Software processes comprise many steps; coding is followed by building, integration testing, system testing, deployment, operations, among others. Software process integration and automation have been areas of key concern in software engineering, ever since the pioneering work of Osterweil; market pressures for Agility, and open, decentralized, software development have provided additional pressures for progress in this area. But do these innovations actually help projects? Given the numerous confounding factors that can influence project performance, it can be a challenge to discern the effects of process integration and automation. Software project ecosystems such as GitHub provide a new opportunity in this regard: one can readily find large numbers of projects in various stages of process integration and automation, and gather data on various influencing factors as well as productivity and quality outcomes. In this paper we use large, historical data on process metrics and outcomes in GitHub projects to discern the effects of one specific innovation in process automation: continuous integration. Our main finding is that continuous integration improves the productivity of project teams, who can integrate more outside contributions, without an observable diminishment in code quality.

Development and Evaluation of a UAV-Photogrammetry System for Precise 3D Environmental Modeling

Abstract: The specific requirements of UAV-photogrammetry necessitate particular solutions for system development, which have mostly been ignored or not assessed adequately in recent studies. Accordingly, this paper presents the methodological and experimental aspects of correctly implementing a UAV-photogrammetry system. The hardware of the system consists of an electric-powered helicopter, a high-resolution digital camera and an inertial navigation system. The software of the system includes the in-house programs specifically designed for camera calibration, platform calibration, system integration, on-board data acquisition, flight planning and on-the-job self-calibration. The detailed features of the system are discussed, and solutions are proposed in order to enhance the system and its photogrammetric outputs. The developed system is extensively tested for precise modeling of the challenging environment of an open-pit gravel mine. The accuracy of the results is evaluated under various mapping conditions, including direct georeferencing and indirect georeferencing with different numbers, distributions and types of ground control points. Additionally, the effects of imaging configuration and network stability on modeling accuracy are assessed. The experiments demonstrated that 1.55 m horizontal and 3.16 m vertical absolute modeling accuracy could be achieved via direct geo-referencing, which was improved to 0.4 cm and 1.7 cm after indirect geo-referencing.

Development of underground mine monitoring and communication system integrated ZigBee and GIS

Abstract: An automated underground mine monitoring and communication system based on the integration of new technologies is introduced to promote safety and health, operational management and cost-effectiveness. The proposed system integration considering Wireless Sensor Network (WSN) assisted Geographic Information System (GIS) enables to monitor and control underground mining applications from surface office. Based on the capabilities of WSNs, ZigBee network is adapted for near real-time monitoring, ventilation system control and emergency communication in underground mine. ZigBee nodes were developed to sense environmental attributes such as temperature, humidity and gases concentration; switching ON and OFF ventilation fans; and texting emergency messages. A trigger action plan for monitored attributes above normal and threshold value limits is programmed in the surface GIS management server. It is designed to turn the auxiliary fans on remotely or automatically in orange condition and sending evacuation messages for underground miners in unsafe (red) condition. Multi-users operation and 3D visualisations are other successful achievements of the proposed system for the underground monitoring and communication.

Knowledge-based instruction of manipulation tasks for industrial robotics

Abstract: When robots are working in dynamic environments, close to humans lacking extensive knowledge of robotics, there is a strong need to simplify the user interaction and make the system execute as autonomously as possible, as long as it is feasible. For industrial robots working side-by-side with humans in manufacturing industry, AI systems are necessary to lower the demand on programming time and system integration expertise. Only by building a system with appropriate knowledge and reasoning services can one simplify the robot programming sufficiently to meet those demands while still getting a robust and efficient task execution.In this paper, we present a system we have realized that aims at fulfilling the above demands. The paper focuses on the knowledge put into ontologies created for robotic devices and manufacturing tasks, and presents examples of AI-related services that use the semantic descriptions of skills to help users instruct the robot adequately. HighlightsWe present a system for knowledge-based task specification in assembly.Robotic skills are described in ontologies and used as building blocks for task specification and synthesis.Robotic skills are declarative, compositional, and reusable.An architecture to maintain and use industrial robotics knowledge is provided.

Autonomous Greenhouse Mobile Robot Driving Strategies From System Integration Perspective: Review and Application

Abstract: Agricultural operations are constantly becoming technology-driven mainly due to labor shortages, increase in labor cost, and trends in new and advanced technology applications. In this paper, we have presented a system-of-systems approach to design and development of a mobile robotic platform for agricultural applications. Similar to other field robots, the mobile platform for agricultural applications requires a different set of predefined attributes for its operation. We have designed, fabricated, and demonstrated the mobile platform for pesticide spraying application. The design and development includes synergistic integration of mechanical, sensor and actuator, navigational and control, and electronic and software interfacings. The autonomous navigation aspect of the development was achieved via three stages: learning stage, implementation stage (training stage), and testing stage. In the learning stage, we defined the path patterns and studied and recorded the behavior of the vehicle in real-world environment. In the training stage, various steering algorithms for four-wheel driving system were developed and inherent errors were compensated using advanced tools and methods. In the testing stage, we put the robotic platform on an arbitrary path pattern and demonstrated its success in autonomous navigation. The medium-sized mobile robot can be commercialized for greenhouse-based agricultural operations.

A Challenging Future for the IC Engine: New Technologies and the Control Role

Abstract: New regulations on pollutants and, specially, on CO2 emissions could restrict the use of the internal combustion engine in automotive applications. This paper presents a review of different technologies under development for meeting such regulations, ranging from new combustion concepts to advanced boosting methods and after-treatment systems. Many of them need an accurate control of the operating conditions and, in many cases, they impose demanding requirements at a system integration level. In this framework, engine control disciplines will be key for the implementation and development of the next generation engines, taking profit of recent advancements in models, methods and sensors. According to authors’ opinion, the internal combustion engine will still be the dominant technology in automotive applications for the next decades.

A vision for the development of i-campus

Abstract: The development of a smart campus is part of the development of a smart city. The development of information and communication technologies poses new challenges to teaching and learning. Stakeholders in education will have different requirements on intelligence which in turn requires various supporting technologies. Examples of smart educational systems are given to illustrate the common characteristics of smartness. Essential elements in constructing intelligent campus: data considerations, procedural knowledge and system integration are discussed.

Condition based maintenance-systems integration and intelligence using Bayesian classification and sensor fusion

Abstract: System integration in condition based maintenance (CBM) is one of the biggest challenges that need to be overcome for widespread deployment of the CBM methodology. CBM system architectures investigated in this work include an independent monitoring and control unit with no communication with machine control (Architecture 1) and a data acquisition and control unit integrated with the machine control (Architecture 2). Based on these architectures, three different CBM system applications are discussed and deployed. A verification of the third system was done by performing a destructive bearing test, causing a spindle to seize due to lubrication starvation. This test validated the CBM system developed, as well as provided insights into using sensor fusion for a better detection of bearing failure. The second part of the work discusses intelligence in a CBM system using a Bayesian probabilistic decision framework and data generated while running validation tests, it is demonstrated how the Naive Bayes classifier can aid in the decision making of stopping the machine before catastrophic failure occurs. Discussing value in combining information supplied by more than one sensor (sensor fusion), it is demonstrated how a catastrophic failure can be prevented. The work is concluded with open issues on the topic with ongoing work and future opportunities.

Cognitive Learning, Monitoring and Assistance of Industrial Workflows Using Egocentric Sensor Networks

Abstract: Today, the workflows that are involved in industrial assembly and production activities are becoming increasingly complex. To efficiently and safely perform these workflows is demanding on the workers, in particular when it comes to infrequent or repetitive tasks. This burden on the workers can be eased by introducing smart assistance systems. This article presents a scalable concept and an integrated system demonstrator designed for this purpose. The basic idea is to learn workflows from observing multiple expert operators and then transfer the learnt workflow models to novice users. Being entirely learning-based, the proposed system can be applied to various tasks and domains. The above idea has been realized in a prototype, which combines components pushing the state of the art of hardware and software designed with interoperability in mind. The emphasis of this article is on the algorithms developed for the prototype: 1) fusion of inertial and visual sensor information from an on-body sensor network (BSN) to robustly track the user’s pose in magnetically polluted environments; 2) learning-based computer vision algorithms to map the workspace, localize the sensor with respect to the workspace and capture objects, even as they are carried; 3) domain-independent and robust workflow recovery and monitoring algorithms based on spatiotemporal pairwise relations deduced from object and user movement with respect to the scene; and 4) context-sensitive augmented reality (AR) user feedback using a head-mounted display (HMD). A distinguishing key feature of the developed algorithms is that they all operate solely on data from the on-body sensor network and that no external instrumentation is needed. The feasibility of the chosen approach for the complete action-perception-feedback loop is demonstrated on three increasingly complex datasets representing manual industrial tasks. These limited size datasets indicate and highlight the potential of the chosen technology as a combined entity as well as point out limitations of the system.

Research on IoT based Cyber Physical System for Industrial big data Analytics

Abstract: The purpose of this paper is to provide a comprehensive solution for industry through research and development of an Internet of Things (IoT) based Cyber Physical System for Industrial Informatics Analytics with the following objectives. This study conducted a review regarding big data analytics in industry and designed a cyber physical system with the integration of various existing and proprietary data analytics systems based on their business needs so that themodules can be reconfigurable and interchangeable. The paper designs a new context intelligence framework to handle industrial informatics regarding location, sensor and unstructured data for big data mining. A case study isused to illustrate the concept of the proposed cyberphysical system. Further study on system integration and migration from existing factories to smart factories should be conducted so as to realize the next industrial paradigm shift.

A system-of-systems approach for integrated energy systems modeling and simulation

Abstract: Energy systems integration combines energy carriers, including electricity, with infrastructures, to maximize efficiency and minimize waste. In order to study systems at a variety of physical scales---from individual buildings to distribution systems---interconnected through these energy infrastructures, NREL is developing an Integrated Energy System Model (IESM), with an initial focus on the electricity system. Today's electricity grid is the most complex system ever built---and the future grid is likely to be even more complex because it will incorporate distributed energy resources (DERs) such as wind, solar, and various other sources of generation and energy storage. The complexity is further augmented by the possible evolution to new retail market structures that would provide incentives to owners of DERs to support the grid. The IESM can be used to understand and test the impact of new retail market structures and technologies such as DERs, demand-response equipment, and energy management systems on the system's ability to provide reliable electricity to all customers. The IESM is composed of a power flow simulator (GridLAB-D), building and appliance models including home energy management system implemented using either GAMS or Pyomo, a market layer, and is able to include hardware-in-the-loop simulation (testing appliances such as air conditioners, dishwashers, etc.). The IESM is a system-of-systems (SoS) simulator wherein the constituent systems are brought together in a virtual testbed. We will describe an SoS approach for developing a distributed simulation environment. We will elaborate on the methodology and the control mechanisms used in the co-simulation illustrated by a case study.

Uav-Based Point Cloud Generation for Open-Pit Mine Modelling

Abstract: . Along with the advancement of unmanned aerial vehicles (UAVs), improvement of high-resolution cameras and development of vision-based mapping techniques, unmanned aerial imagery has become a matter of remarkable interest among researchers and industries. These images have the potential to provide data with unprecedented spatial and temporal resolution for three-dimensional (3D) modelling. In this paper, we present our theoretical and technical experiments regarding the development, implementation and evaluation of a UAV-based photogrammetric system for precise 3D modelling. This system was preliminarily evaluated for the application of gravel-pit surveying. The hardware of the system includes an electric powered helicopter, a 16-megapixels visible camera and inertial navigation system. The software of the system consists of the in-house programs built for sensor calibration, platform calibration, system integration and flight planning. It also includes the algorithms developed for structure from motion (SfM) computation including sparse matching, motion estimation, bundle adjustment and dense matching.

On the model design of integrated intelligent big data analytics systems

Abstract: – Although big data analytics has reaped great business rewards, big data system design and integration still face challenges resulting from the demanding environment, including challenges involving variety, uncertainty, and complexity. These characteristics in big data systems demand flexible and agile integration architectures. Furthermore, a formal model is needed to support design and verification. The purpose of this paper is to resolve the two problems with a collective intelligence (CI) model. , – In the conceptual CI framework as proposed by Schut (2010), a CI design should be comprised of a general model, which has formal form for verification and validation, and also a specific model, which is an implementable system architecture. After analyzing the requirements of system integration in big data environments, the authors apply the CI framework to resolve the integration problem. In the model instantiation, the authors use multi-agent paradigm as the specific model, and the hierarchical colored Petri Net (PN) as the general model. , – First, multi-agent paradigm is a good implementation for reuse and integration of big data analytics modules in an agile and loosely coupled method. Second, the PN models provide effective simulation results in the system design period. It gives advice on business process design and workload balance control. Third, the CI framework provides an incrementally build and deployed method for system integration. It is especially suitable to the dynamic data analytics environment. These findings have both theoretical and managerial implications. , – In this paper, the authors propose a CI framework, which includes both practical architectures and theoretical foundations, to solve the system integration problem in big data environment. It provides a new point of view to dynamically integrate large-scale modules in an organization. This paper also has practical suggestions for Chief Technical Officers, who want to employ big data technologies in their companies.

Cross-organism analysis using InterMine.

Abstract: Summary InterMine is a data integration warehouse and analysis software system developed for large and complex biological data sets. Designed for integrative analysis, it can be accessed through a user-friendly web interface. For bioinformaticians, extensive web services as well as programming interfaces for most common scripting languages support access to all features. The web interface includes a useful identifier look-up system, and both simple and sophisticated search options. Interactive results tables enable exploration, and data can be filtered, summarized, and browsed. A set of graphical analysis tools provide a rich environment for data exploration including statistical enrichment of sets of genes or other entities. InterMine databases have been developed for the major model organisms, budding yeast, nematode worm, fruit fly, zebrafish, mouse, and rat together with a newly developed human database. Here, we describe how this has facilitated interoperation and development of cross-organism analysis tools and reports. InterMine as a data exploration and analysis tool is also described. All the InterMine-based systems described in this article are resources freely available to the scientific community. genesis 53:547–560, 2015. © 2015 Wiley Periodicals, Inc.

Strawman: A Batch In Situ Visualization and Analysis Infrastructure for Multi-Physics Simulation Codes

Abstract: We present Strawman, a system designed to explore the in situ visualization and analysis needs of simulation code teams planning for multi-physics calculations on exascale architectures. Strawman's design derives from key requirements from a diverse set of simulation code teams, including lightweight usage of shared resources, batch processing, ability to leverage modern architectures, and ease-of-use both for software integration and for usage during simulation runs. We describe the Strawman system, the key technologies it depends on, and our experiences integrating Strawman into three proxy simulations. Our findings show that Strawman's design meets our target requirements, and that some of its concepts may be worthy of integration into our community in situ implementations.

Master data system integration method based on enterprise service bus (ESB)

Abstract: The invention provides a master data system integration method based on an enterprise service bus (ESB). The method includes: a unified master data production system, a master data consuming system, a master data management system, and the unified master data management service interface and the master data updating interface of the master data management system are built; the master data management system is connected with the other systems through the ESB and manages all master data changer events generated in the other systems, and all synchronous coordination and optimization integration related to master data are overall controlled by the master data management system; the master data consuming system provides a port which is used for receiving the master data and registered to the ESB; the master data production system performs synchronous adding, deleting and modification on the master data through the ESB, transmits a data change signal to the master data management system at the same time, and pushes the changed master data to the master data receiving port, registered to the ESB, of the master data consuming system so as to achieve data synchronization.

RFID-based system for school children transportation safety enhancement

Abstract: This paper presents a system to monitor pick-up/drop-off of school children to enhance the safety of children during the daily transportation from and to school. The system consists of two main units, a bus unit and a school unit. The bus unit the system is used to detect when a child boards or leaves the bus. This information is communicated to the school unit that identifies which of the children did not board or leave the bus and issues an alert message accordingly. The system has a developed web-based database-driven application that facilities its management and provides useful information about the children to authorized personal. A complete prototype of the proposed system was implemented and tested to validate the system functionality. The results show that the system is promising for daily transportation safety.

Integration Technologies for a Fully Modular and Hot-Swappable MV Multi-Level Concept Converter

Abstract: In order to fully exploit the benefits of modular converters, dedicated hard- and software integration technologies have been developed to complement modular multi-level circuit topologies. The technologies investigated include a wireless auxiliary power supply, a two-phase cooling, solid insulation, wireless optical communication, redundant EtherCAT networking and advanced IGBT junction temperature diagnostics. Emphasis was set on three key aspects of modularity: scalability, configurability and pluggability. To validate the technologies and to demonstrate their benefits, a medium voltage concept converter was built and operated. The combination of these technologies finally also enabled a 'hot swap' functionality, where power modules can be replaced during converter operation. Hot swap has successfully been tested for a DC-link voltage of 3.3 kV and output power of 550 kW.

An Application of Horizontal and Vertical Integration in Cyber-Physical Production Systems

Abstract: It has a need to meet the demands of individual customers and solve the problems in current production caused by changing of the markets and the global influence and general competition situation. Utilization of the progress achieved in the information and communication technologies are expected in the future for many manufacturing companies. This leads to the increasing and consistent integration of Information and Communication Technology (ICT) into the production systems in smaller and smaller subsystems and components. Cyber-Physical System will be more and more involved in production systems. Mechatronic systems become cyber-physical systems through additional communication skills and autonomy in behavior on external influences and internally stored settings. In the Cyber-Physical Production System, the horizontal integration through value networks and the vertical integration through networked manufacturing systems can be built to realize smart factory and smart production. In a laboratory environment at the Experimental and Digital Factory at the Chemnitz University of Technology, an innovative logistical system is built up to apply the horizontal and vertical integration into practice for research investigations. A research question to be answered is how the communication between components in this system related to the horizontal and vertical integration can be implemented. The other issue is how to test the integration and the functionalities.

Versioning in cyber-physical production system engineering: best-practice and research agenda

Abstract: The parallel engineering of cyber-physical production systems (CPPSs), an important type of sCPS, needs the collaboration of several engineering disciplines, which use a wide range of heterogeneous tools and data sources. Systems engineers and process participants need an overview on the engineering artifact versions and their relationships on the project level. Unfortunately, the version management of engineering artifacts typically is conducted on the file level and does not support the versioning of engineering model elements. Recently, the Automation ML standard has been introduced to facilitate the data exchange between systems engineering tools. In this paper, we discuss the challenges of versioning related model views during the engineering of CPPSs to achieve a mechatronic view on the engineering artifacts. Based on real-world examples, we discuss (a) the strengths and limitations of best-practice approaches in CPPS engineering and (b) how software engineering contributions can provide the foundation for effectively addressing the challenge of versioning engineering model elements to provide a mechatronic view. From this analysis, we derive research issues for future work.

A PT-SOA Model for CPS/IoT Services

Abstract: Service computing technologies have been widely applied to many application domains to facilitate rapid system integration for desired goals. However, existing service models need to be enhanced for cyber-physical systems (CPS) and internet-of-things (IoT). In this paper, we develop an ontology model for the specification of services in CPS/IoT. First, we discuss the major differences in modeling software services and services in CPS/IoT. Then, we propose a novel PT-SOA (PT stands for physical things) model, which is mainly extended from OWL-S, to enhance existing service models for CPS/IoT systems. Finally, we show a case study system to illustrate how our model can facilitate proper service selection and composition.

Integration of clinical and basic sciences in concept maps: a mixed-method study on teacher learning

Abstract: The explication of relations between clinical and basic sciences can help vertical integration in medical curricula. Concept mapping might be a useful technique for this explication. Little is known about teachers’ ability regarding the articulation of integration. We examined therefore which factors affect the learning of groups of clinicians and basic scientists on different expertise levels who learn to articulate the integration of clinical and basic sciences in concept maps. After a pilot for fine-tuning group size and instructions, seven groups of expert clinicians and basic scientists and seven groups of residents with a similar disciplinary composition constructed concept maps about a clinical problem that fit their specializations. Draft and final concepts maps were compared on elaborateness and articulated integration by means of t-tests. Participants completed a questionnaire on motivation and their evaluation of the instructions. ANOVA’s were run to compare experts’ and residents’ views. Data from video tapes and notes were qualitatively analyzed. Finally, the three data sources were interpreted in coherence by using Pearson’s correlations and qualitative interpretation. Residents outshone experts as regards learning to articulate integration as comparison of the draft and final versions showed. Experts were more motivated and positive about the concept mapping procedure and instructions, but this did not correlate with the extent of integration fond in the concept maps. The groups differed as to communication: residents interacted from the start (asking each other for clarification), whereas overall experts only started interaction when they had to make joint decisions. Our results suggest that articulation of integration can be learned, but this learning is not related to participants’ motivation or their views on the instructions. Decision making and interaction, however, do relate to the articulation of integration and this suggests that teacher learning programs for designing integrated educational programmes should incorporate co-construction tasks. Expertise level turned out to be decisive for both the level of articulation of integration, the ability to improve the articulated integration and the cooperation pattern.

Mass Customization: Opportunities, Methods, and Challenges for Manufacturers

Abstract: * Introduction* Intelligent Manufacturing Technologies* Problems in Smart Factory Projects* Future Challenges* New ICT Technologies* Alternative Factory Floor Interface Devices* New Manufacturing Technologies* Software Integration* Going Cloud* Designing and Communicating the Vision* Commissioning* Implementation Process* References