Thesis (Ph. D.)--University of Wisconsin--Madison, 1975. / Typescript. Vita. Description based on print version record. Includes bibliographical references (leaves 148-152).

The random deployment of Wireless Sensor and Actuator Network (WSAN) nodes in areas often inaccessible, results in so-called coverage holes – i.e. areas in the network that are not adequately covered by nodes to suit the requirements of the network. Various coverage protocol algorithms have been designed to reduce or eliminate coverage holes within WSANs by indicating how to move the nodes. The effectiveness of such coverage protocols could be jeopardised by inaccuracy in the initial node location data that is broadcast by the respective nodes. This study examines the effects of location inaccuracies on five sensor deployment and reconfiguration algorithms – They include two algorithms which assume that mobile nodes are deployed (referred to as the VEC and VOR algorithms); two that assume static nodes are deployed (referred to as the CNPSS and OGDC algorithms); and a single algorithm (based on a bidding protocol) that assumes a hybrid scenario in which both static and mobile nodes are deployed. Two variations of this latter algorithm are studied. A location simulation tool was built using the GE Smallworld GIS application and the Magik programming language. The simulation results are based on three above-mentioned deployment scenarios; mobile, hybrid and static. The simulation results suggest the VOR algorithm is reasonably robust if the location inaccuracies are somewhat lower than the sensing distance and also if a high degree of inaccuracy is limited to a relatively small percentage of the nodes. The VEC algorithm is considerably less robust, but prevents nodes from drifting beyond the boundaries in the case of large inaccuracies. The bidding protocol used by the hybrid algorithm appears to be robust only when the static nodes are accurate and there is a low degree of inaccuracy within the mobile nodes. Finally the static algorithms are shown to be the most robust; the CPNSS algorithm appears to be immune to location inaccuracies whilst the OGDC algorithm was shown to reduce the number of active nodes in the network to a better extent than that of the CPNSS algorithm. Copyright / Dissertation (MSc)--University of Pretoria, 2010. / Computer Science / unrestricted

This thesis is addressing the fusion of geo-information from different data sources for time-critical geo-applications. Such geo-information is extracted from sensors that record earth observation (EO) data. In recent years the amount of sensors that provide geo-information experienced a major growth not least because of the rising market for small sensors that are nowadays integrated in smartphones or recently even in fitness wristbands that are carried at the body. The resulting flood of geo-information builds the basis for new, time-critical geo-applications that would have been inconceivable a decade ago. The real-time characteristics of geo-information, which is also getting more important for traditional sensors (e.g. remote sensors), require new methodologies and scientific investigations regarding aggregation and analysis that can be summarised under the term geo-information fusion. Thus, the main goal of this thesis is the investigation of fusing geo-information for time-critical geo-applications with the focus on the benefits as well as challenges and obstacles that appear. Three different use cases dealing with capturing, modelling and analysis of spatial information are studied. In that process, the main emphasis is on the added value and the benefits of geo-information fusion. One can speak of an “added value” if the informational content can only be derived by the combination of information from different sources, meaning that it cannot be derived from one source individually. Another goal of this thesis is the prototypical integration of the fusion approach in spatial data infrastructures (SDIs) to increase the interoperability of the developed methods. By doing so, the fusion can be provided (e.g. over the internet) and used by a multitude of users and developers. Above that, the integration is of high importance regarding systems and concepts like the Global Earth Observation System of Systems (GEOSS), the INSPIRE directive for Europe or the European monitoring system Copernicus. The results and findings of this thesis can be seen as the first advances and can be used for further research and studies in the field of geo-information fusion which will gain further importance and relevance for all spatial questions in the future.

Dieser Beitrag fokussiert auf Ansätze, die der Abschätzung des deutschen Bestandes von Wohn- und Nichtwohngebäuden dienen. Insbesondere werden rasterbasierte Gebäudedaten sowie gemeindescharfe Schätzergebnisse eines bereits etablierten Ansatzes vorgestellt, analysiert und bewertet. In Verbindung mit modernen Daten der amtlichen Geoinformation (Geobasisdaten) zeichnen sich neue, innovative Möglichkeiten ab, um künftig auf kleinräumiger Ebene den Gebäudebestand zu bestimmen. Das Leibniz-Institut für ökologische Raumentwicklung (IÖR) verfolgt vor diesem Hintergrund mit dem Projekt „Raumbezogenes Data Mining“ das Ziel, analytische Potenziale und Visualisierungsmöglichkeiten von zeitgemäßen Methoden des Data Mining und der Knowledge Discovery für die Raumforschung zu erschließen und in der Perspektive verborgene planungsrelevante Raummuster und Zusammenhänge im hochdimensionalen Geodatenbestand zu extrahieren.

This International Workshop is a high quality seminar providing a forum for the exchange of scientific achievements between research communities of different universities and research institutes in the area of innovation information technologies. It is a continuation of the Russian-German Workshops that have been organized by the universities in Dresden, Karlsruhe and Ufa before. The workshop was arranged in 9 sessions covering the major topics: Modern Trends in Information Technology, Knowledge Based Systems and Semantic Modelling, Software Technology and High Performance Computing, Geo-Information Systems and Virtual Reality, System and Process Engineering, Process Control and Management and Corporate Information Systems.

No description available.

Dieser Beitrag fokussiert auf Ansätze, die der Abschätzung des deutschen Bestandes von Wohn- und Nichtwohngebäuden dienen. Insbesondere werden rasterbasierte Gebäudedaten sowie gemeindescharfe Schätzergebnisse eines bereits etablierten Ansatzes vorgestellt, analysiert und bewertet. In Verbindung mit modernen Daten der amtlichen Geoinformation (Geobasisdaten) zeichnen sich neue, innovative Möglichkeiten ab, um künftig auf kleinräumiger Ebene den Gebäudebestand zu bestimmen. Das Leibniz-Institut für ökologische Raumentwicklung (IÖR) verfolgt vor diesem Hintergrund mit dem Projekt „Raumbezogenes Data Mining“ das Ziel, analytische Potenziale und Visualisierungsmöglichkeiten von zeitgemäßen Methoden des Data Mining und der Knowledge Discovery für die Raumforschung zu erschließen und in der Perspektive verborgene planungsrelevante Raummuster und Zusammenhänge im hochdimensionalen Geodatenbestand zu extrahieren.

This International Workshop is a high quality seminar providing a forum for the exchange of scientific achievements between research communities of different universities and research institutes in the area of innovation information technologies. It is a continuation of the Russian-German Workshops that have been organized by the universities in Dresden, Karlsruhe and Ufa before. The workshop was arranged in 9 sessions covering the major topics: Modern Trends in Information Technology, Knowledge Based Systems and Semantic Modelling, Software Technology and High Performance Computing, Geo-Information Systems and Virtual Reality, System and Process Engineering, Process Control and Management and Corporate Information Systems.

Logistics and supply chain in the Architecture, Engineering and Construction (AEC) industry can be seen as coordinated collaboration that is subject to managerial risks. The managerial risks are mitigated by Building Information Modelling (BIM) and Geo-Information Science (GIS), which are two distinctive digital transformative tools which are revolutionizing and accelerating the AEC industry in recent years. Many gains have been achieved concerning the capacity of BIM and GIS to enable collaborative workflows that minimize data loss and reduce inefficiencies in construction. In the past decade, most scholarly literature on BIM and GIS integration for supply chain management have focused on coordination and visualization to improve supply chain operational efficiency. While BIM optimizes visualization and manages the data related to specific projects, GIS coordinates and manages the data related to the outside environment of the project. An integrated BIM-GIS adoption for Construction Supply Chain Management (CSCM) offers value propositions for client and contracting organizations as information/data is seamlessly shared among them to guide decision making at every phase of the construction project.  However, no detailed study has been conducted so far on assessments of the value creation 4D BIM-GIS brings to the AEC industry when espoused for CSCM. To fill this gap, this paper aims to identify and prioritize the value propositions to 4D BIM-GIS adoption for CSCM in the Swedish AEC industry. Based on the reflective perceptions and evaluations of the AEC industry, the paper demonstrated the varied opinions from current active users and those who are yet to adopt 4D BIM-GIS for CSCM. ‘Time savings, ‘Increased efficiency and productivity and ‘Improved communication and information sharing’ were ranked as topmost drivers for 4D BIM-GIS adoption. The paper recommends corporate level training as pivotal in familiarizing workers with the new techniques that combine BIM and GIS in AEC practice. / Logistik och försörjningskedjan inom arkitektur, teknik och konstruktion (ABE) kan ses som ett samordnat samarbete med överhängande ledningsrisker. Riskerna som hanteras kan mildras av Byggnadsinformationsmodellering (BIM) och Geografiskt informationssystem (GIS), som är två digitalt distinkta transformativa verktyg som revolutionerat och påskyndat ABE-sektorn de senaste åren. Många vinster har uppnåtts med avseende på kapaciteten av BIM och GIS, vilket har möjliggjort ett samarbetsflöde som minimerat dataförlust och minskat ineffektiviteten i byggandet. Under det senaste decenniet har den mest vetenskapliga litteraturen om BIM- och GIS-integration för ledning av försörjningskedjan fokuserat på samordning och visualisering för att förbättra effektiviteten i försörjningskedjan. BIM optimerar visualisering och hantering av data, relaterat till specifika projekt, medan GIS samordnar och hanterar data relaterat till projektets omgivning. En integrerad BIM-GIS-antagande för konstruktionsledningen av försörjningskedjan (CSCM) erbjuder värdeförslag för klient- och beställarorganisationer, eftersom information / data sömlöst delas mellan dem för att kunna guida beslutsfattandet i varje fas av byggprojektet. Emellertid har ingen detaljerad studie hittills genomförts om bedömningar av värdeskapandet som 4D BIM-GIS ger till ABE-sektorn när de används för CSCM. För att fylla denna kunskapslucka syftar denna studie till att identifiera och prioritera värdeförslag till 4D BIM-GIS-antagande för CSCM i den svenska ABE-sektorn. Baserat på de reflekterande uppfattningarna och utvärderingarna från ABE-sektorn, visar studien de olika åsikterna från de nuvarande aktiva användare och de som ännu inte har antagit 4D BIM-GIS för CSCM. ”Tidsbesparingar,” Ökad effektivitet och produktivitet” och ”Förbättrad kommunikation och informationsdelning” rankades som de främsta drivkrafterna för 4D BIM-GIS-antagande. Studien rekommenderar utbildning på företagsnivå som en central faktor för att bekanta sig med de nya teknikerna som kombinerar BIM och GIS i ABE-sektorn.