Fireground location understanding by semantic linking of visual objects and building information models

This paper presents an outline for improved localization and situational awareness in fire emergency situations based on semantic technology and computer vision techniques. The novelty of our methodology lies in the semantic linking of video object recognition results from visual and thermal cameras with Building Information Models (BIM). The current limitations and possibilities of certain building information streams in the context of fire safety or fire incident management are addressed in this paper. Furthermore, our data management tools match higher-level semantic metadata descriptors of BIM and deep-learning based visual object recognition and classification networks. Based on these matches, estimations can be generated of camera, objects and event positions in the BIM model, transforming it from a static source of information into a rich, dynamic data provider. Previous work has already investigated the possibilities to link BIM and low-cost point sensors for fireground understanding, but these approaches did not take into account the benefits of video analysis and recent developments in semantics and feature learning research. Finally, the strengths of the proposed approach compared to the state-of-the-art is its (semi -)automatic workflow, generic and modular setup and multi-modal strategy, which allows to automatically create situational awareness, to improve localization and to facilitate the overall fire understanding

Integrated mobility and resource management for cross-network resource sharing in heterogeneous wireless networks using traffic offload policies

The problem of efficient use of resources in wireless access networks becomes critical today with users expecting continuous high-speed network access. While access network capacity continues to increase, simultaneous operation of multiple wireless access networks presents an opportunity to increase the data rates available to end-users even further using intelligent cross-network resource sharing. This paper introduces a new integrated mobility and resource management (IMRM) framework for automatic execution of policies for cross-network resource sharing using traffic offload and pre-emptive resource reservation algorithms. The presented framework enables both mobile-initiated and network-initiated resource sharing policies to be executed. This paper presents the framework in detail and analyses its performance using extensive ns-2 simulations of the operation of a set of static policies based on measured signal strength, and dynamic pre-emptive network-initiated policies in a WiFi/WiMAX scenario. The detailed evaluation of the static policies clearly shows that the quality of voice applications shows large deviation, mostly due to very different levels of delay in access networks. Based on these conclusions, this paper presents a design of two new dynamic policies and shows that such policies, when efficiently implemented using the new IMRM framework can greatly improve the capacity of the network to serve voice traffic with a minimal impact on the data traffic and with a very low signalling overhead

Dynamic Bandwidth Allocation in ATM Networks

Today's new applications such as World Wide Web, video conferencing and multimedia have introduced a large amount of traffic into the network. Additionally new applications are also heading towards real time process. Instant access to the network, greater level of performances and higher degree of satisfaction has become the main concerns of users using these new applications. Although current transmission mediums have advanced in capacity through means such as optical fiber and Gigabit Ethernet, future and unknown new services tend to consume up the available bandwidth. ATM network is the new technology used to support a wide variety of services including data, voice, video and most possibly other future applications. Its flexibility, efficiency and high throughput have gained popularity but with greater complexity due to different approaches in handling different type of services.A high-speed network such as ATM networks must have an effective traffic management scheme in order to gain high data throughput with the least cost of operation. Thus, simulation and modeling are the effective methods used to design the trade-off between network parameters and their performances. Effective sharing of network resources such as bandwidth and buffer are studied through the dynamic allocation method. Static allocation scheme has been proven inefficient to provide high resources utilization as can be seen in STM networks compared to A TM networks. However, ATM networks should provide different dynamic allocation methods according to its different services and traffic characteristics. Four dynamic allocation strategies have been designed, evaluated and compared for their performances. They are called Static Bandwidth Allocation, Bandwidth Allocated Proportional to Expected Queue Length, Bandwidth Allocated Proportional to Expected Queue Length with Threshold Value and Bandwidth Allocated with Threshold Interrupt. Bandwidth Allocated with Threshold Interrupt is proven to be the most effective strategy as it could response to congestion immediately

Enhancing Capacity and Network Performance of Client-Server Architectures Using Mobile IPv6 Host-Based Network Protocol

A huge number of studies have been done supporting seamless mobility networks and mobile technologies over the years. The recent innovations in technology have unveiled another revolution from the static architectural approach to more dynamic and even mobile approaches for client-server networks. Due to the special equipments and infrastructure needed to support network mobility management, it is difficult to deploy such networks beyond the local network coverage without interruption of communications. Therefore, MIPv6 as developed by the Internet Engineering Task Force (IETF) and ancillary technologies were reviewed to provide clear insights on implementing MIPv6 in Client-Server architectures. However, MIPv6 technology presents weaknesses related to its critical handover latency which appears long for real-time applications such as Video Stream with potential loss of data packets during transmission

Enhancing Capacity and Network Performance of Client-Server Architectures Using Mobile IPv6 Host-Based Network Protocol

A huge number of studies have been done supporting seamless mobility networks and mobile technologies over the years The recent innovations in technology have unveiled another revolution from the static architectural approach to more dynamic and even mobile approaches for client-server networks Due to the special equipments and infrastructure needed to support network mobility management it is difficult to deploy such networks beyond the local network coverage without interruption of communications Therefore MIPv6 as developed by the Internet Engineering Task Force IETF and ancillary technologies were reviewed to provide clear insights on implementing MIPv6 in Client-Server architectures However MIPv6 technology presents weaknesses related to its critical handover latency which appears long for real-time applications such as Video Stream with potential loss of data packets during transmissio

Dynamic Quality-of-Service Management Under Software-Defined Networking Architectures

The Internet is facing new challenges emerging from new trends in Information and Communication Technologies (ICT) for example, cloud services, Big Data, increased mobile usage etc. Traditional IP networks rely in two design principles that, despite serving as an effective solution in the last decades, have become deprecated and not well fit for the new challenges. First, the control and data plane are tightly embedded in the networking devices and second, the structure is highly decentralized with no centralized point of management. This static and rigid architecture leaves no space for innovation with a consequence lack of scalability. Also, it leads to high management and operation costs. The SDN paradigm provides a more dynamic, manageable, cost-effective and adaptable architecture that is ready for the dynamic nature of today's applications. The goal of this thesis is a novel SDN-enabled solution that provides dynamic Quality of Service management for real-time and multimedia applications. This solution will be tested and implemented over a real, not-simulated testbed, composed by OpenFlow-enabled devices, the ONOS SDN controller and client terminals that produced/consume data streams. Furthermore, it is also expected to characterize and evaluate the benefits of the SDN-based solution against a traditional usage of the network (non-SDN)

Dynamic Adaptation of Software-defined Networks for IoT Systems: A Search-based Approach

The concept of Internet of Things (IoT) has led to the development of many complex and critical systems such as smart emergency management systems. IoT-enabled applications typically depend on a communication network for transmitting large volumes of data in unpredictable and changing environments. These networks are prone to congestion when there is a burst in demand, e.g., as an emergency situation is unfolding, and therefore rely on configurable software-defined networks (SDN). In this paper, we propose a dynamic adaptive SDN configuration approach for IoT systems. The approach enables resolving congestion in real time while minimizing network utilization, data transmission delays and adaptation costs. Our approach builds on existing work in dynamic adaptive search-based software engineering (SBSE) to reconfigure an SDN while simultaneously ensuring multiple quality of service criteria. We evaluate our approach on an industrial national emergency management system, which is aimed at detecting disasters and emergencies, and facilitating recovery and rescue operations by providing first responders with a reliable communication infrastructure. Our results indicate that (1) our approach is able to efficiently and effectively adapt an SDN to dynamically resolve congestion, and (2) compared to two baseline data forwarding algorithms that are static and non-adaptive, our approach increases data transmission rate by a factor of at least 3 and decreases data loss by at least 70%

Production Allocation of Reservoir Layers using Data-Driven Reservoir Modeling

The pros of having a commingled layer scheme would be considered high with successful reservoir management. If not, the cons will impact the production drastically as unfortunate consequences may result in reservoir fluids communication, well integrity issues, and production termination. Although the plane requires optimizing production with minimal capital investments and operating expenses, it is an enormous challenge considering commingled layers frequent surveillance and workover requirements. As the value of information is a decision tool for the surveillance frequency, the oil industry often uses static assumptions as an economical replacement of dynamic measurements such as KH static modeling. However, the last is misleading for not considering the effect of dynamic attributes such as reservoir pressure and fluid properties. Simultaneously, the evolution of Artificial Intelligence (AI) and Machine Learning (ML) made the challenge of allocating commingled layers allocation possible since AI does not build assumptions based on static properties but rather pick the static and dynamic patterns associated with rock and fluid properties. Accordingly, AI and ML application was used in this research as a new approach for commingled layers allocation estimation, which is known technically as Top-Down Modeling (TDM). TDM features the entire acquired static and dynamic field measurements through Artificial Intelligence and Data Science that utilizes Machine Learning, Fuzzy and crisp Logic via Neural Networks to develop a reservoir model. TDM was tested on a synthetic heterogeneous reservoir model with three commingled layers across 63 wells in conjunction with multi-random comingling schemes throughout wells\u27 lifespan. As the static KH modeling proven ambiguous in picking the effect of reservoir pressure on production profile per layer, a high certainty TDM modeling was successfully achieved both horizontally and vertically on a layer basis which confirms the capability of TDM in allocating commingled layers production in terms of certainty, and operational cost