An eco-friendly hybrid urban computing network combining community-based wireless LAN access and wireless sensor networking

Computer-enhanced smart environments, distributed environmental monitoring, wireless communication, energy conservation and sustainable technologies, ubiquitous access to Internet-located data and services, user mobility and innovation as a tool for service differentiation are all significant contemporary research subjects and societal developments. This position paper presents the design of a hybrid municipal network infrastructure that, to a lesser or greater degree, incorporates aspects from each of these topics by integrating a community-based Wi-Fi access network with Wireless Sensor Network (WSN) functionality. The former component provides free wireless Internet connectivity by harvesting the Internet subscriptions of city inhabitants. To minimize session interruptions for mobile clients, this subsystem incorporates technology that achieves (near-)seamless handover between Wi-Fi access points. The WSN component on the other hand renders it feasible to sense physical properties and to realize the Internet of Things (IoT) paradigm. This in turn scaffolds the development of value-added end-user applications that are consumable through the community-powered access network. The WSN subsystem invests substantially in ecological considerations by means of a green distributed reasoning framework and sensor middleware that collaboratively aim to minimize the network's global energy consumption. Via the discussion of two illustrative applications that are currently being developed as part of a concrete smart city deployment, we offer a taste of the myriad of innovative digital services in an extensive spectrum of application domains that is unlocked by the proposed platform

An Ontology Framework for Addressing Cost Overrun through Risk Modeling: A Risk Path Approach

Whether forced by economic conditions or internal motivations, contractors may choose to minimize their mark-up margins in order to maximize their chances of winning a bid. Such bidding conditions render contractors sensitive towards all types of risks associated with executing a project. This research aims at providing contractors with a framework through which they can reduce their bid prices to be able to compete in low biding conditions. This aim is realized through identifying risk elements that have the greatest impact on projects’ costs in the Egyptian construction industry. Work on this research follows a risk path approach consisting of risk sources, risk events, and risk consequences, and vulnerability factors consisting of robustness factors, resistance factors and sensitivity factors, whose relationships and risk paths are mapped through an ontology model. The weights characterizing that relationship between each of these elements is estimated through a three-phase model that utilizes both optimization and Artificial Neural Networks (ANN), through 52 risks cenarios collected from 35 experts in the Egyptian Construction industry. Outputs generated by the model comprise of five sets of weights. Each set represents the effect of one risk path element on a subsequent element, collectively demonstrating the relations connecting the risk path elements to cost overruns. The model’s outputs showed that that 35 percent of the top 20 Robustness factors are related to project design. Lack of contractor’s technical resources rank higher than that of contractor’s financial resources in terms of their effect on Risk events. Project type has the most impact on project cost overrun, followed by Project delivery method. Further, delays due to bureaucracy whether from the owner or the government’s side rank at the bottom of the list

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

A BIM-based value for money assessment in public-private partnership: an overall review

Public-private partnerships (PPPs) have proliferated and adapted to public development in recent decades; within it, the value for money (VfM) assessment defines the feasibility of the project procurement model as one of the essential components of PPP. However, evaluating the VfM in PPPs remains problematic. Given concerns about PPP profitability, a more integrated VfM evaluation is urgently needed to manage multiple indicators along the project lifecycle. Building information management (BIM), popular in architecture, engineering, and construction, provides resources that could support the VfM to a great extent. This paper uses a review approach to identify the current issues that are affecting VfM assessments and suggests that BIM, functioning throughout the PPP lifecycle, could support decision-making in VfM processes in order to satisfy service targets

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped upon decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

An ontology-based approach supporting holistic structural design with the consideration of safety, environmental impact and cost

Early stage decision-making for structural design critically influences the overall cost and environmental performance of buildings and infrastructure. However, the current approach often fails to consider the multi-perspectives of structural design, such as safety, environmental issues and cost in a comprehensive way. This paper presents a holistic approach based on knowledge processing (ontology) to facilitate a smarter decision-making process for early design stage by informing designers of the environmental impact and cost along with safety considerations. The approach can give a reasoning based quantitative understanding of how the design alternatives using different concrete materials can affect the ultimate overall performance. Embodied CO2 and cost are both considered along with safety criteria as indicative multi-perspectives to demonstrate the novelty of the approach. A case study of a concrete structural frame is used to explain how the proposed method can be used by structural designers when taking multi performance criteria into account. The major contribution of the paper lies on the creation of a holistic knowledge base which links through different knowledge across sectors to enable the structural engineer to come up with much more comprehensive decisions instead of individual single objective targeted delivery

Business Ontology for Evaluating Corporate Social Responsibility

This paper presents a software solution that is developed to automatically classify companies by taking into account their level of social responsibility. The application is based on ontologies and on intelligent agents. In order to obtain the data needed to evaluate companies, we developed a web crawling module that analyzes the company’s website and the documents that are available online such as social responsibility report, mission statement, employment structure, etc. Based on a predefined CSR ontology, the web crawling module extracts the terms that are linked to corporate social responsibility. By taking into account the extracted qualitative data, an intelligent agent, previously trained on a set of companies, computes the qualitative values, which are then included in the classification model based on neural networks. The proposed ontology takes into consideration the guidelines proposed by the “ISO 26000 Standard for Social Responsibility”. Having this model, and being aware of the positive relationship between Corporate Social Responsibility and financial performance, an overall perspective on each company’s activity can be configured, this being useful not only to the company’s creditors, auditors, stockholders, but also to its consumers.corporate social responsibility, ISO 26000 Standard for Social Responsibility, ontology, web crawling, intelligent agent, corporate performance, POS tagging, opinion mining, sentiment analysis

Managing the Hydra in integration: developing an integrated assessment tool for agricultural systems

Keywords: modelling, bio-economic, farm, simulation, ontology, knowledge management, Europe, agricultural management, database, scenario Ex-ante assessment through science-based methods can provide insight into the impacts of potential policy measures or innovations to manage complex problems (e.g. environmental pollution, climate change, or farmers’ welfare). Integrated Assessment and Modelling (IAM) is a method that supports ex-ante assessment through modelling and modelling tools. One type of IAM links models focusing on particular processes on a specific scale into model chains covering multiple scales and disciplines. To achieve an operational model chain for IAM, methodological, semantic and technical integration is required of models, data sources, indicators and scenarios. In this thesis, methodological, semantic and technical integration focuses on two case studies. The first case study is on integration within bio-economic farm models covering two hierarchical systems levels involving a small team of scientists. The second case refers to modelling European agricultural systems. In this case, the integration covers five hierarchical systems levels and different types of models were linked by a large team of about hundred scientists. In the context of these two case studies, many different integration topics and challenges have been addressed: a review of the state-of-the-art in bio-economic farm models, a generic method to define alternative agricultural activities, development of a generic bio-economic farm model, development of an integrated database for agricultural systems, linking different agricultural models and a shared definition of scenarios across disciplines, models and scales. Ultimately, elaborating the methodological, semantic and technical integration greatly contributed to the development of an integrated assessment tool for European agricultural systems. This integrated assessment tool can be used across disciplines and for multi-scale analysis, and allows the assessment of many different policy and technology changes. </p