Sensor function virtualization to support distributed intelligence in the internet of things

It is estimated that-by 2020-billion devices will be connected to the Internet. This number not only includes TVs, PCs, tablets and smartphones, but also billions of embedded sensors that will make up the "Internet of Things" and enable a whole new range of intelligent services in domains such as manufacturing, health, smart homes, logistics, etc. To some extent, intelligence such as data processing or access control can be placed on the devices themselves. Alternatively, functionalities can be outsourced to the cloud. In reality, there is no single solution that fits all needs. Cooperation between devices, intermediate infrastructures (local networks, access networks, global networks) and/or cloud systems is needed in order to optimally support IoT communication and IoT applications. Through distributed intelligence the right communication and processing functionality will be available at the right place. The first part of this paper motivates the need for such distributed intelligence based on shortcomings in typical IoT systems. The second part focuses on the concept of sensor function virtualization, a potential enabler for distributed intelligence, and presents solutions on how to realize it

Horizontal Integration of Warfighter Intelligence Data: A Shared Semantic Resource for the Intelligence Community

We describe a strategy that is being used for the horizontal integration of warfighter intelligence data within the framework of the US Army’s Distributed Common Ground System Standard Cloud (DSC) initiative. The strategy rests on the development of a set of ontologies that are being incrementally applied to bring about what we call the ‘semantic enhancement’ of data models used within each intelligence discipline. We show how the strategy can help to overcome familiar tendencies to stovepiping of intelligence data, and describe how it can be applied in an agile fashion to new data resources in ways that address immediate needs of intelligence analysts

Информационные технологии: тенденция, пути развития

Показано воздействие Business Intelligence на информационные технологии такие, как технологии предоставления услуг на основе сервисной модели в среде Grid и Cloud Computing. Рассмотрен термин «облачный компьютинг, вычисления в облаке, или облачный сервис».The influence of Business Intelligence on the information technologies, such as the provision of services based on a service model in the Grid and Cloud Computing environment is shown. The term «cloud computing, calculation in a cloud, or a cloud service» is considered.Показано вплив Business Intelligence на інформаційні технології такі, як технології надання послуг на основі сервісної моделі в середовищі Grid та Cloud Computing. Розглянуто термін «хмарний комп’ютинг, обчислення в хмарі, або сервіс у хмарах»

How Fluffy is the Cloud?: Cloud Intelligence for a Not-for-profit Organisation

Business Intelligence (BI) is becoming more accessible and less expensive with fewer risks through various deployment options available in the Cloud. Cloud computing facilitates the acquisition of custom solutions for not-for-profit (NFP) organisations at affordable and scalable costs on a flexible pay-as-you-go basis. In this paper, we explore the key technical and organisational aspects of BI in the Cloud (Cloud Intelligence) deployment in an Australian NFP whose BI maturity is rising although still low. This organisation aspires to Cloud Intelligence for improved managerial decision making yet the issues surrounding the adoption of Cloud Intelligence are complex, especially where corporate and Cloud governance is concerned. From the findings of the case study, a conceptual framework has been developed and presented which offers a view of how governance could be deployed so that NFPs gain maximum leverage through their adoption of the Cloud

T-spline based unifying registration procedure for free-form surface workpieces in intelligent CMM

With the development of the modern manufacturing industry, the free-form surface is widely used in various fields, and the automatic detection of a free-form surface is an important function of future intelligent three-coordinate measuring machines (CMMs). To improve the intelligence of CMMs, a new visual system is designed based on the characteristics of CMMs. A unified model of the free-form surface is proposed based on T-splines. A discretization method of the T-spline surface formula model is proposed. Under this discretization, the position and orientation of the workpiece would be recognized by point cloud registration. A high accuracy evaluation method is proposed between the measured point cloud and the T-spline surface formula. The experimental results demonstrate that the proposed method has the potential to realize the automatic detection of different free-form surfaces and improve the intelligence of CMMs