Pub Date : 2013-04-15DOI: 10.1109/SysCon.2013.6549883
T. Walworth, M. Yearworth, J. Davis, Paul J. Davies
We address the problem of rework in complex project management by the use of System Dynamics modeling and estimated planned performance profiles. We propose that early indications of problems arising with a project can be generated by comparing estimated planed performance profiles with actual performance profiles. Estimating project quality for use in the System Dynamics models thus becomes the key challenge to enable the use of this leading indicator. Estimates of project quality based on experience of project type, size and complexity within the organization can be used to parameterize the System Dynamics models to generate model generated estimated planned performance profiles. Early results indicate that the morphology of these profiles shows good agreement with project data emerging from the metrics initiative within Thales UK.
{"title":"Early estimation of project performance: The application of a system dynamics rework model","authors":"T. Walworth, M. Yearworth, J. Davis, Paul J. Davies","doi":"10.1109/SysCon.2013.6549883","DOIUrl":"https://doi.org/10.1109/SysCon.2013.6549883","url":null,"abstract":"We address the problem of rework in complex project management by the use of System Dynamics modeling and estimated planned performance profiles. We propose that early indications of problems arising with a project can be generated by comparing estimated planed performance profiles with actual performance profiles. Estimating project quality for use in the System Dynamics models thus becomes the key challenge to enable the use of this leading indicator. Estimates of project quality based on experience of project type, size and complexity within the organization can be used to parameterize the System Dynamics models to generate model generated estimated planned performance profiles. Early results indicate that the morphology of these profiles shows good agreement with project data emerging from the metrics initiative within Thales UK.","PeriodicalId":218073,"journal":{"name":"2013 IEEE International Systems Conference (SysCon)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128664608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-15DOI: 10.1109/SysCon.2013.6549944
G. Hellestrand
Engineering safe, complex real-time systems is challenging. Engineering mobile systems of systems that are safe and possibly autonomous, requires considerable support from competent specification based architecture, model-based design processes and concomitant large-scale, heterogeneous simulation capabilities. Safety - the dominatrix of autonomy - is determined by requirements that then propagate through the specification, architecture, design, verification, validation and calibration phases of the real-time engineering process. In real-time systems, time is a 1st class, functional property of the system. The paper describes a specification-based architecture for the engineering of safe mobile system of systems and the modeling and simulation technology required to produce them.
{"title":"Engineering safe autonomous mobile systems of systems using specification (model) based systems architecture & engineering","authors":"G. Hellestrand","doi":"10.1109/SysCon.2013.6549944","DOIUrl":"https://doi.org/10.1109/SysCon.2013.6549944","url":null,"abstract":"Engineering safe, complex real-time systems is challenging. Engineering mobile systems of systems that are safe and possibly autonomous, requires considerable support from competent specification based architecture, model-based design processes and concomitant large-scale, heterogeneous simulation capabilities. Safety - the dominatrix of autonomy - is determined by requirements that then propagate through the specification, architecture, design, verification, validation and calibration phases of the real-time engineering process. In real-time systems, time is a 1st class, functional property of the system. The paper describes a specification-based architecture for the engineering of safe mobile system of systems and the modeling and simulation technology required to produce them.","PeriodicalId":218073,"journal":{"name":"2013 IEEE International Systems Conference (SysCon)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129661167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-15DOI: 10.1109/SysCon.2013.6549920
E. Pereira, Camille Potiron, C. Kirsch, R. Sengupta
In this paper we address the problem of modelling and controlling heterogeneous mobile robotic systems at a structure-level abstraction. We consider a system of mobile robotic entities that are able to observe, control, compute, and communicate. They operate upon an abstraction of the structure of the world that entails location and connectivity as first-class concepts. Our approach is to model mobile robotic entities as bigActors [18], a model of computation that combines bigraphs with the actor model for modeling structure-aware computation. As case study, we model a mission of heterogeneous unmanned vehicles performing an environmental monitoring mission.
{"title":"Modeling and controlling the structure of heterogeneous mobile robotic systems: A bigactor approach","authors":"E. Pereira, Camille Potiron, C. Kirsch, R. Sengupta","doi":"10.1109/SysCon.2013.6549920","DOIUrl":"https://doi.org/10.1109/SysCon.2013.6549920","url":null,"abstract":"In this paper we address the problem of modelling and controlling heterogeneous mobile robotic systems at a structure-level abstraction. We consider a system of mobile robotic entities that are able to observe, control, compute, and communicate. They operate upon an abstraction of the structure of the world that entails location and connectivity as first-class concepts. Our approach is to model mobile robotic entities as bigActors [18], a model of computation that combines bigraphs with the actor model for modeling structure-aware computation. As case study, we model a mission of heterogeneous unmanned vehicles performing an environmental monitoring mission.","PeriodicalId":218073,"journal":{"name":"2013 IEEE International Systems Conference (SysCon)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127484003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-15DOI: 10.1109/SysCon.2013.6549922
S. Santos, S. Givigi, C. Nascimento
This paper presents an adaptive approach based on the Reinforcement Learning (RL) method to manipulate and transport parts and also assemble 3-D structures in a moderately constrained and dynamic environment using a quad-rotor. Nowadays, complex construction tasks using mobile robots are characterized by two fundamental problems such as task planning and motion planning. However, to obtain the task and path planning that define a specific sequence of operations for construction of a given structure is generally very complex. In this context, we propose and investigate a system in which an aerial robot learns the assembly and construction tasks of multiple 3-D structures. This process involves the learning of the sequence of maneuvers of a vehicle, the assembly sequence of the parts and also the correct types of structural elements for each assembly point of the structure. A heuristic search algorithm is used in the learning process to find the optimal path for the quad-rotor so that its navigation through the dynamic environment is performed. The experimental results show that a 3-D structure can be built using the task planning approach derived from a learning algorithm combined with a heuristic search method.
{"title":"Autonomous construction of structures in a dynamic environment using Reinforcement Learning","authors":"S. Santos, S. Givigi, C. Nascimento","doi":"10.1109/SysCon.2013.6549922","DOIUrl":"https://doi.org/10.1109/SysCon.2013.6549922","url":null,"abstract":"This paper presents an adaptive approach based on the Reinforcement Learning (RL) method to manipulate and transport parts and also assemble 3-D structures in a moderately constrained and dynamic environment using a quad-rotor. Nowadays, complex construction tasks using mobile robots are characterized by two fundamental problems such as task planning and motion planning. However, to obtain the task and path planning that define a specific sequence of operations for construction of a given structure is generally very complex. In this context, we propose and investigate a system in which an aerial robot learns the assembly and construction tasks of multiple 3-D structures. This process involves the learning of the sequence of maneuvers of a vehicle, the assembly sequence of the parts and also the correct types of structural elements for each assembly point of the structure. A heuristic search algorithm is used in the learning process to find the optimal path for the quad-rotor so that its navigation through the dynamic environment is performed. The experimental results show that a 3-D structure can be built using the task planning approach derived from a learning algorithm combined with a heuristic search method.","PeriodicalId":218073,"journal":{"name":"2013 IEEE International Systems Conference (SysCon)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130167174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-15DOI: 10.1109/SysCon.2013.6549901
K. Bhasin, Patrick Barnes, Jessica M. Reinert, Bert Golden
System engineering practices for complex systems and networks now require that requirement, architecture, and concept of operations product development teams, simultaneously harmonize their activities to provide timely, useful and cost-effective products. When dealing with complex systems of systems, traditional systems engineering methodology quickly falls short of achieving project objectives. This approach is encumbered by the use of a number of disparate hardware and software tools, spreadsheets and documents to grasp the concept of the network design and operation. In case of NASA's space communication networks, since the networks are geographically distributed, and so are its subject matter experts, the team is challenged to create a common language and tools to produce its products. Using Model Based Systems Engineering methods and tools allows for a unified representation of the system in a model that enables a highly related level of detail. To date, Program System Engineering (PSE) team has been able to model each network from their top-level operational activities and system functions down to the atomic level through relational modeling decomposition. These models allow for a better understanding of the relationships between NASA's stakeholders, internal organizations, and impacts to all related entities due to integration and sustainment of existing systems. Understanding the existing systems is essential to accurate and detailed study of integration options being considered. In this paper, we identify the challenges the PSE team faced in its quest to unify complex legacy space communications networks and their operational processes. We describe the initial approaches undertaken and the evolution toward model based system engineering applied to produce Space Communication and Navigation (SCaN) PSE products. We will demonstrate the practice of Model Based System Engineering applied to integrating space communication networks and the summary of its results and impact. We will highlight the insights gained by applying the Model Based System Engineering and provide recommendations for its applications and improvements.
{"title":"Applying model based systems engineering to NASA's space communications networks","authors":"K. Bhasin, Patrick Barnes, Jessica M. Reinert, Bert Golden","doi":"10.1109/SysCon.2013.6549901","DOIUrl":"https://doi.org/10.1109/SysCon.2013.6549901","url":null,"abstract":"System engineering practices for complex systems and networks now require that requirement, architecture, and concept of operations product development teams, simultaneously harmonize their activities to provide timely, useful and cost-effective products. When dealing with complex systems of systems, traditional systems engineering methodology quickly falls short of achieving project objectives. This approach is encumbered by the use of a number of disparate hardware and software tools, spreadsheets and documents to grasp the concept of the network design and operation. In case of NASA's space communication networks, since the networks are geographically distributed, and so are its subject matter experts, the team is challenged to create a common language and tools to produce its products. Using Model Based Systems Engineering methods and tools allows for a unified representation of the system in a model that enables a highly related level of detail. To date, Program System Engineering (PSE) team has been able to model each network from their top-level operational activities and system functions down to the atomic level through relational modeling decomposition. These models allow for a better understanding of the relationships between NASA's stakeholders, internal organizations, and impacts to all related entities due to integration and sustainment of existing systems. Understanding the existing systems is essential to accurate and detailed study of integration options being considered. In this paper, we identify the challenges the PSE team faced in its quest to unify complex legacy space communications networks and their operational processes. We describe the initial approaches undertaken and the evolution toward model based system engineering applied to produce Space Communication and Navigation (SCaN) PSE products. We will demonstrate the practice of Model Based System Engineering applied to integrating space communication networks and the summary of its results and impact. We will highlight the insights gained by applying the Model Based System Engineering and provide recommendations for its applications and improvements.","PeriodicalId":218073,"journal":{"name":"2013 IEEE International Systems Conference (SysCon)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132472410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-15DOI: 10.1109/SysCon.2013.6549864
R. Hernandez, John Faella
Much research has been performed that concentrates on providing processing throughput enhancements to existing algorithms. Many systems have performance requirements that constrain their volume and/or power consumption. For volume and power consumption constrained systems, throughput cannot be the only decision factor when selecting a computational engine. Typical studies can aid in the selection of computational engines that meet the throughput requirements of a system, but may be of little help with respect to the volume, power and thermal constraints. This paper takes a different approach to help provide a different perspective on the constrained design problem. The research performed in this paper emphasizes the cost due to the power, size and Non-Recurring Engineering (NRE) costs of various computational engines. The computational engines researched in this paper are: Central Processing Unit (CPU), mobile CPU, Digital Signal Processor (DSP), and mobile Graphics Processing Unit (GPU). The various architectures are compared against each other with respect to throughput, power, size and NRE costs. The authors hope that the process outlined in this paper may serve as a possible guideline for other Systems Engineers to perform similar Analysis of Alternatives of computational engines. Furthermore, the authors hope that the methods used for the relative performance evaluations will serve as a starting point to help shape policy in the selection of computational engines for future designs.
{"title":"Towards policy and guidelines for the selection of computational engines","authors":"R. Hernandez, John Faella","doi":"10.1109/SysCon.2013.6549864","DOIUrl":"https://doi.org/10.1109/SysCon.2013.6549864","url":null,"abstract":"Much research has been performed that concentrates on providing processing throughput enhancements to existing algorithms. Many systems have performance requirements that constrain their volume and/or power consumption. For volume and power consumption constrained systems, throughput cannot be the only decision factor when selecting a computational engine. Typical studies can aid in the selection of computational engines that meet the throughput requirements of a system, but may be of little help with respect to the volume, power and thermal constraints. This paper takes a different approach to help provide a different perspective on the constrained design problem. The research performed in this paper emphasizes the cost due to the power, size and Non-Recurring Engineering (NRE) costs of various computational engines. The computational engines researched in this paper are: Central Processing Unit (CPU), mobile CPU, Digital Signal Processor (DSP), and mobile Graphics Processing Unit (GPU). The various architectures are compared against each other with respect to throughput, power, size and NRE costs. The authors hope that the process outlined in this paper may serve as a possible guideline for other Systems Engineers to perform similar Analysis of Alternatives of computational engines. Furthermore, the authors hope that the methods used for the relative performance evaluations will serve as a starting point to help shape policy in the selection of computational engines for future designs.","PeriodicalId":218073,"journal":{"name":"2013 IEEE International Systems Conference (SysCon)","volume":"6 13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132324286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-15DOI: 10.1109/SysCon.2013.6549965
C. Insaurralde, Y. Pétillot
Current research projects are developing technologies that require more and more the integration of different system capabilities placed at geographically-dispersed locations. The challenge when integrating system capabilities is to choose the right system components to be integrated in order to fulfill the deadline given by the project milestones. This paper proposes a method that shows how project objectives are achieved by means of tracing the requirements across the system development lifecycle until the milestones are reached. The approach proposed turns project objectives and its context into user requirements as well as evaluation cases into project milestones. The integration process consists of integrating functional capabilities from the system modules which are the foundation to support operational capabilities. This paper also presents a review of the stages of the system development lifecycle, and architectural elements of the system under development. It also describes aspects of the planning and scheduling for the implementation of an illustrative case study based on an autonomous maritime system, and their impact on the integration process.
{"title":"From research project objectives to milestones by means of requirements traceability Realization of an autonomous maritime system","authors":"C. Insaurralde, Y. Pétillot","doi":"10.1109/SysCon.2013.6549965","DOIUrl":"https://doi.org/10.1109/SysCon.2013.6549965","url":null,"abstract":"Current research projects are developing technologies that require more and more the integration of different system capabilities placed at geographically-dispersed locations. The challenge when integrating system capabilities is to choose the right system components to be integrated in order to fulfill the deadline given by the project milestones. This paper proposes a method that shows how project objectives are achieved by means of tracing the requirements across the system development lifecycle until the milestones are reached. The approach proposed turns project objectives and its context into user requirements as well as evaluation cases into project milestones. The integration process consists of integrating functional capabilities from the system modules which are the foundation to support operational capabilities. This paper also presents a review of the stages of the system development lifecycle, and architectural elements of the system under development. It also describes aspects of the planning and scheduling for the implementation of an illustrative case study based on an autonomous maritime system, and their impact on the integration process.","PeriodicalId":218073,"journal":{"name":"2013 IEEE International Systems Conference (SysCon)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127878131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-15DOI: 10.1109/SysCon.2013.6549945
Reem Al Junaibi, A. Farid
In recent years, electric vehicles (EVs) have gained much attention as a potential enabling technology to support CO2 emissions reduction targets. Furthermore, many of the cost and vehicle technology barriers that have prevented their adoption in the past are increasingly being addressed by vehicle manufacturers. Nevertheless, the question remains as to whether EVs themselves will be technically feasible within the larger infrastructure systems with which they interact. Fundamentally, EVs interact with three interconnected `systems-of-systems': the (physical) transportation system, the electric power grid, and their supporting information systems often called intelligent transportation systems (ITS). These systems affect the EV operation in potentially constraining ways that can negatively impact the EV user's final transportation experience. This paper seeks to understand and assess these interactions in such a way as to evaluate their ultimate technical feasibility in relation to their supporting infrastructure systems. A new assessment method based upon modeling tools for each infrastructure system is proposed. For the traffic system, a microscopic discrete-time traffic operations simulator is used to study the kinematic state of the EV fleet at all times. For the electric power system, power flow analysis is used to determine the electrical charging loads required by the EV traffic usage patterns. Finally, UML is used to model the intelligent transportation system functionality as compared to a template of functions deemed necessary to support EV integration. The final method of technical feasibility assessment is demonstrated on a hypothetical scenario which conceptualizes the EV adoption scenario by a taxi service operator.
{"title":"A method for the technical feasibility assessment of electrical vehicle penetration","authors":"Reem Al Junaibi, A. Farid","doi":"10.1109/SysCon.2013.6549945","DOIUrl":"https://doi.org/10.1109/SysCon.2013.6549945","url":null,"abstract":"In recent years, electric vehicles (EVs) have gained much attention as a potential enabling technology to support CO2 emissions reduction targets. Furthermore, many of the cost and vehicle technology barriers that have prevented their adoption in the past are increasingly being addressed by vehicle manufacturers. Nevertheless, the question remains as to whether EVs themselves will be technically feasible within the larger infrastructure systems with which they interact. Fundamentally, EVs interact with three interconnected `systems-of-systems': the (physical) transportation system, the electric power grid, and their supporting information systems often called intelligent transportation systems (ITS). These systems affect the EV operation in potentially constraining ways that can negatively impact the EV user's final transportation experience. This paper seeks to understand and assess these interactions in such a way as to evaluate their ultimate technical feasibility in relation to their supporting infrastructure systems. A new assessment method based upon modeling tools for each infrastructure system is proposed. For the traffic system, a microscopic discrete-time traffic operations simulator is used to study the kinematic state of the EV fleet at all times. For the electric power system, power flow analysis is used to determine the electrical charging loads required by the EV traffic usage patterns. Finally, UML is used to model the intelligent transportation system functionality as compared to a template of functions deemed necessary to support EV integration. The final method of technical feasibility assessment is demonstrated on a hypothetical scenario which conceptualizes the EV adoption scenario by a taxi service operator.","PeriodicalId":218073,"journal":{"name":"2013 IEEE International Systems Conference (SysCon)","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129181947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-15DOI: 10.1109/SysCon.2013.6549850
J. Elm, Dennis R. Goldenson
This paper summarizes the results of a survey that had the goal of quantifying the connection between the application of systems engineering (SE) best practices to projects and programs and the performance outcomes of those projects and programs. The survey population consisted of projects and programs executed by system developers reached through the National Defense Industrial Association (NDIA) Systems Engineering Division, the Institute of Electrical and Electronics Engineers (IEEE) Aerospace and Electronic Systems Society, and the International Council on Systems Engineering (INCOSE). Analysis of survey responses revealed strong statistical relationships between project performance and several categories of specific SE best practices. The survey results show notable differences in the relationship between SE best practices and performance between more challenging and less challenging projects. The statistical relationship with project performance is quite strong for survey data of this kind when both SE capability and project challenge are considered together.
{"title":"Quantifying the effectiveness of systems engineering","authors":"J. Elm, Dennis R. Goldenson","doi":"10.1109/SysCon.2013.6549850","DOIUrl":"https://doi.org/10.1109/SysCon.2013.6549850","url":null,"abstract":"This paper summarizes the results of a survey that had the goal of quantifying the connection between the application of systems engineering (SE) best practices to projects and programs and the performance outcomes of those projects and programs. The survey population consisted of projects and programs executed by system developers reached through the National Defense Industrial Association (NDIA) Systems Engineering Division, the Institute of Electrical and Electronics Engineers (IEEE) Aerospace and Electronic Systems Society, and the International Council on Systems Engineering (INCOSE). Analysis of survey responses revealed strong statistical relationships between project performance and several categories of specific SE best practices. The survey results show notable differences in the relationship between SE best practices and performance between more challenging and less challenging projects. The statistical relationship with project performance is quite strong for survey data of this kind when both SE capability and project challenge are considered together.","PeriodicalId":218073,"journal":{"name":"2013 IEEE International Systems Conference (SysCon)","volume":"4 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120891933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-15DOI: 10.1109/SysCon.2013.6549967
Nikhil Mantrawadi, Mais Nijim, Young Lee
The interpretation of remotely sensed images in a spatiotemporal context is becoming a valuable research topic. Today's optical sensor systems on satellite provide large-area images with 1-m resolution and better, which can deliver complement information to traditional acquired data. However, the constant growth of data volume in remote sensing imaging makes reaching conclusions based on collected data a challenging task. One of the main problems that arise during the data mining process is treating data that contains temporal information. However, two important issues must be considered in order to provide more accurate decisions on object identification and pattern recognition. First, the continuous growth of the dataset storage space and the advances in remote sensing sensors which generate a huge amount of satellite images making the manual image interpretation a difficult task. Second, the space/time components are inherent to satellite images; systems being developed to identify objects must take into account the spatiotemporal context to better interpret the collected image data. Spatial relations between objects are widely used in context-based image retrieval. This paper outlines the challenges and proposes in creation of a data mines capable of supporting the requirements of the system, which, inevitably demand a high level of cooperation between many disparate sources of spatial data.
{"title":"Object identification and classification in a high resolution satellite data using data mining techniques for knowledge extraction","authors":"Nikhil Mantrawadi, Mais Nijim, Young Lee","doi":"10.1109/SysCon.2013.6549967","DOIUrl":"https://doi.org/10.1109/SysCon.2013.6549967","url":null,"abstract":"The interpretation of remotely sensed images in a spatiotemporal context is becoming a valuable research topic. Today's optical sensor systems on satellite provide large-area images with 1-m resolution and better, which can deliver complement information to traditional acquired data. However, the constant growth of data volume in remote sensing imaging makes reaching conclusions based on collected data a challenging task. One of the main problems that arise during the data mining process is treating data that contains temporal information. However, two important issues must be considered in order to provide more accurate decisions on object identification and pattern recognition. First, the continuous growth of the dataset storage space and the advances in remote sensing sensors which generate a huge amount of satellite images making the manual image interpretation a difficult task. Second, the space/time components are inherent to satellite images; systems being developed to identify objects must take into account the spatiotemporal context to better interpret the collected image data. Spatial relations between objects are widely used in context-based image retrieval. This paper outlines the challenges and proposes in creation of a data mines capable of supporting the requirements of the system, which, inevitably demand a high level of cooperation between many disparate sources of spatial data.","PeriodicalId":218073,"journal":{"name":"2013 IEEE International Systems Conference (SysCon)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115166151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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