Enabling smart city resilience: Post-disaster response and structural health monitoring

The concept of Smart Cities has been introduced to categorize a vast area of activities to enhance the quality of life of citizens. A central feature of these activities is the pervasive use of Information and Communication Technologies (ICT), helping cities to make better use of limited resources. Indeed, the ASCE Vision for Civil Engineering in 2025 (ASCE 2007) portends a future in which engineers will rely on and leverage real-time access to a living database, sensors, diagnostic tools, and other advanced technologies to ensure that informed decisions are made. However, these advances in technology take place against a backdrop of the deterioration of infrastructure, in addition to natural and human-made disasters. Moreover, recent events constantly remind us of the tremendous devastation that natural and human-made disasters can wreak on society. As such, emergency response procedures and resilience are among the crucial dimensions of any Smart City plan. The U.S. Department of Homeland Security (DHS) has recently launched plans to invest $50 million to develop cutting-edge emergency response technologies for Smart Cities. Furthermore, after significant disasters have taken place, it is imperative that emergency facilities and evacuation routes, including bridges and highways, be assessed for safety. The objective of this research is to provide a new framework that uses commercial off-the-shelf (COTS) devices such as smartphones, digital cameras, and unmanned aerial vehicles to enhance the functionality of Smart Cities, especially with respect to emergency response and civil infrastructure monitoring/assessment. To achieve this objective, this research focuses on post-disaster victim localization and assessment, first responder tracking and event localization, and vision-based structural monitoring/assessment, including the use of unmanned aerial vehicles (UAVs). This research constitutes a significant step toward the realization of Smart City Resilience.National Science Foundation Grant No. 1030454Association of American RailroadsOpe

Enabling smart city resilience: post-disaster response and structural health monitoring

The concept of Smart Cities has been introduced to categorize a vast area of activities to enhance the quality of life of citizens. A central feature of these activities is the pervasive use of Information and Communication Technologies (ICT), helping cities to make better use of limited resources. Indeed, the ASCE Vision for Civil Engineering in 2025 (ASCE 2007) portends a future in which engineers will rely on and leverage real-time access to a living database, sensors, diagnostic tools, and other advanced technologies to ensure that informed decisions are made. However, these advances in technology take place against a backdrop of the deterioration of infrastructure, in addition to natural and human-made disasters. Moreover, recent events constantly remind us of the tremendous devastation that natural and human-made disasters can wreak on society. As such, emergency response procedures and resilience are among the crucial dimensions of any Smart City plan. The U.S. Department of Homeland Security (DHS) has recently launched plans to invest $50 million to develop cutting-edge emergency response technologies for Smart Cities. Furthermore, after significant disasters have taken place, it is imperative that emergency facilities and evacuation routes, including bridges and highways, be assessed for safety. The objective of this research is to provide a new framework that uses commercial off-the-shelf (COTS) devices such as smartphones, digital cameras, and unmanned aerial vehicles to enhance the functionality of Smart Cities, especially with respect to emergency response and civil infrastructure monitoring/assessment. To achieve this objective, this research focuses on post-disaster victim localization and assessment, first responder tracking and event localization, and vision-based structural monitoring/assessment, including the use of unmanned aerial vehicles (UAVs). This research constitutes a significant step toward the realization of Smart City Resilience

Acoustic Sensing: Mobile Applications and Frameworks

Acoustic sensing has attracted significant attention from both academia and industry due to its ubiquity. Since smartphones and many IoT devices are already equipped with microphones and speakers, it requires nearly zero additional deployment cost. Acoustic sensing is also versatile. For example, it can detect obstacles for distracted pedestrians (BumpAlert), remember indoor locations through recorded echoes (EchoTag), and also understand the touch force applied to mobile devices (ForcePhone). In this dissertation, we first propose three acoustic sensing applications, BumpAlert, EchoTag, and ForcePhone, and then introduce a cross-platform sensing framework called LibAS. LibAS is designed to facilitate the development of acoustic sensing applications. For example, LibAS can let developers prototype and validate their sensing ideas and apps on commercial devices without the detailed knowledge of platform-dependent programming. LibAS is shown to require less than 30 lines of code in Matlab to implement the prototype of ForcePhone on Android/iOS/Tizen/Linux devices.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143971/1/yctung_1.pd

Innovative Wireless Localization Techniques and Applications

Innovative methodologies for the wireless localization of users and related applications are addressed in this thesis. In last years, the widespread diffusion of pervasive wireless communication (e.g., Wi-Fi) and global localization services (e.g., GPS) has boosted the interest and the research on location information and services. Location-aware applications are becoming fundamental to a growing number of consumers (e.g., navigation, advertising, seamless user interaction with smart places), private and public institutions in the fields of energy efficiency, security, safety, fleet management, emergency response. In this context, the position of the user - where is often more valuable for deploying services of interest than the identity of the user itself - who. In detail, opportunistic approaches based on the analysis of electromagnetic field indicators (i.e., received signal strength and channel state information) for the presence detection, the localization, the tracking and the posture recognition of cooperative and non-cooperative (device-free) users in indoor environments are proposed and validated in real world test sites. The methodologies are designed to exploit existing wireless infrastructures and commodity devices without any hardware modification. In outdoor environments, global positioning technologies are already available in commodity devices and vehicles, the research and knowledge transfer activities are actually focused on the design and validation of algorithms and systems devoted to support decision makers and operators for increasing efficiency, operations security, and management of large fleets as well as localized sensed information in order to gain situation awareness. In this field, a decision support system for emergency response and Civil Defense assets management (i.e., personnel and vehicles equipped with TETRA mobile radio) is described in terms of architecture and results of two-years of experimental validation

Design and Implementation of System Components for Radio Frequency Based Asset Tracking Devices to Enhance Location Based Services. Study of angle of arrival techniques, effects of mutual coupling, design of an angle of arrival algorithm, design of a novel miniature reconfigurable antenna optimised for wireless communication systems

The angle of arrival estimation of multiple sources plays a vital role in the field of array signal processing as MIMO systems can be employed at both the transmitter and the receiver end and the system capacity, reliability and throughput can be significantly increased by using array signal processing. Almost all applications require accurate direction of arrival (DOA) estimation to localize the sources of the signals. Another important parameter of localization systems is the array geometry and sensor design which can be application specific and is used to estimate the DOA. In this work, various array geometries and arrival estimation algorithms are studied and then a new scheme for multiple source estimation is proposed and evaluated based on the performance of subspace and non-subspace decomposition methods. The proposed scheme has shown to outperform the conventional Multiple Signal Classification (MUSIC) estimation and Bartlett estimation techniques. The new scheme has a better performance advantage at low and high signal to noise ratio values (SNRs). The research work also studies different array geometries for both single and multiple incident sources and proposes a geometry which is cost effective and efficient for 3, 4, and 5 antenna array elements. This research also considers the shape of the ground plane and its effects on the angle of arrival estimation and in addition it shows how the mutual couplings between the elements effect the overall estimation and how this error can be minimised by using a decoupling matrix. At the end, a novel miniaturised multi element reconfigurable antenna to represent the receiver base station is designed and tested. The antenna radiation patterns in the azimuth angle are almost omni-directional with linear polarisation. The antenna geometry is uniplanar printed logspiral with striplines feeding network and biased components to improve the impedance bandwidth. The antenna provides the benefit of small size, and re-configurability and is very well suited for the asset tracking applications

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

IoT in smart communities, technologies and applications.

Internet of Things is a system that integrates different devices and technologies, removing the necessity of human intervention. This enables the capacity of having smart (or smarter) cities around the world. By hosting different technologies and allowing interactions between them, the internet of things has spearheaded the development of smart city systems for sustainable living, increased comfort and productivity for citizens. The Internet of Things (IoT) for Smart Cities has many different domains and draws upon various underlying systems for its operation, in this work, we provide a holistic coverage of the Internet of Things in Smart Cities by discussing the fundamental components that make up the IoT Smart City landscape, the technologies that enable these domains to exist, the most prevalent practices and techniques which are used in these domains as well as the challenges that deployment of IoT systems for smart cities encounter and which need to be addressed for ubiquitous use of smart city applications. It also presents a coverage of optimization methods and applications from a smart city perspective enabled by the Internet of Things. Towards this end, a mapping is provided for the most encountered applications of computational optimization within IoT smart cities for five popular optimization methods, ant colony optimization, genetic algorithm, particle swarm optimization, artificial bee colony optimization and differential evolution. For each application identified, the algorithms used, objectives considered, the nature of the formulation and constraints taken in to account have been specified and discussed. Lastly, the data setup used by each covered work is also mentioned and directions for future work have been identified. Within the smart health domain of IoT smart cities, human activity recognition has been a key study topic in the development of cyber physical systems and assisted living applications. In particular, inertial sensor based systems have become increasingly popular because they do not restrict users’ movement and are also relatively simple to implement compared to other approaches. Fall detection is one of the most important tasks in human activity recognition. With an increasingly aging world population and an inclination by the elderly to live alone, the need to incorporate dependable fall detection schemes in smart devices such as phones, watches has gained momentum. Therefore, differentiating between falls and activities of daily living (ADLs) has been the focus of researchers in recent years with very good results. However, one aspect within fall detection that has not been investigated much is direction and severity aware fall detection. Since a fall detection system aims to detect falls in people and notify medical personnel, it could be of added value to health professionals tending to a patient suffering from a fall to know the nature of the accident. In this regard, as a case study for smart health, four different experiments have been conducted for the task of fall detection with direction and severity consideration on two publicly available datasets. These four experiments not only tackle the problem on an increasingly complicated level (the first one considers a fall only scenario and the other two a combined activity of daily living and fall scenario) but also present methodologies which outperform the state of the art techniques as discussed. Lastly, future recommendations have also been provided for researchers

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity