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

Centralized Oversight of the Regulatory State

Born out of a Reagan-era desire to minimize regulatory costs, and not fundamentally reconsidered since its inception, the centralized review of agency rulemakings has arguably become the most important institutional feature of the regulatory state. Yet it is a puzzling feature: although centralized review is sometimes justified on the ground it could harmonize the uncoordinated sprawl of the federal bureaucracy, the agency tasked with regulatory review, the Office of Management and Budget (OMB), has never embraced that role. It has instead doggedly clung to its original cost-reduction mission, justifying its function as a check on the federal bureaucracy with reference to the pervasive belief that agencies will systematically over-regulate. This article shows why this belief is wrong. The claim that agencies are systematically biased in favor of regulation finds little support in public choice theory, the political science literature, or elsewhere. In any event, theories predicting rampant over-regulation are no more plausible than alternative theories suggesting that agencies will routinely under regulate. Even if zealous agencies captured by powerful interest groups did characterize the regulatory state, OMB review is a curious and poorly designed counterweight. There is no reason to believe that OMB's location in the Executive Office of the President will inoculate OMB from the pathologies that afflict other agencies, and some reason to think that it will exacerbate them. As a response to these problems, we urge a reconsideration of the foundational role that centralized review should play in our regulatory state, and a revival and re-conceptualization of the neglected principles of harmonization that once ostensibly animated it.

Challenges of Public Housing in a Democratic Nigeria: a Case Study of the Presidential Mandate Housing Scheme

This study examined the challenges of public housing in a democratic Nigeria using the Presidential Mandate Housing Scheme as a case study. Data were derived from purposively selected members of staff of public institutions charged with the responsibility of implementing this scheme in urban areas of Southern Nigeria through interview enquiries and participant observation. These were analyzed using content analysis. The result shows that the scheme was implemented in very few States in Southern part of Nigeria with miniscule number of housing units constructed in those States. Poor programme conception and planning, funding inadequacies and the dearth of preferred building materials were identified as the key challenges that led to the failure of this scheme. The paper argues that despite the return of democratic rule in 1999 and subsequent adoption of the New National Housing and Urban Development Policy in 2002, low organizational capacity of public housing agencies, the lack of collaborations between these agencies and private sector organizations and the none availability of reliable local building materials constitute serious impediments to smooth and successful implementation of public housing programmes in Nigeria. It therefore suggests that the prospects of public housing in democratic Nigeria are contingent upon addressing these challenge

Cellular automata for population growth prediction: Tripoli-Libya case

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonDue to obstruction in the national plan of urbanization in Tripoli (Libya) and population growth, serious problems have emerged in the form of random settlements, overcrowding and poor infrastructure. After more than two decades of inertia, the government has created a national plan in order to resolve the problems, hence it has enforced the demolition of some zones and modified other (irregularly built) ones, however the process is extremely costly. This research introduces a solution through cellular automata (CA) model to predict growth trends; size of residential, industrial and utilities areas; and to project future population. The model is implemented using digitized land use maps of Tripoli to indicate each areas as group of cells to predict their growth. The model incorporates two types of fuzzy rules bases, the first of which is based on the inputs population and area, and the second of which is based on the three inputs of population, area and density. The population prediction is performed using three scenarios, namely decreasing, fixed and increasing growth rates, such that all possibilities of growth are covered. In addition, the residential area prediction is performed based on two cases: normal density and low density. The former is introduced since new areas tend to have more open spaces and bigger houses. Furthermore, the model considers the growth of the industrial areas to be slower than that of residential areas. The model is developed and validated for the period of 1980 to 2010. The prediction is performed for thirty years from 2010 to 2040. In addition to the CA model, a regression model is developed and tested on the three growth scenarios for the same period (30 years). The prediction results are very close for 2040 in terms of population. The model incorporates the introduction of public services areas that are distributed equally on the growth areas, which occupy about 15-20% of the total area. This model can help the government to develop areas in a proper way and controls the expansion to have well layout and planned of the city, improving people's standard of living sustainably, while protecting the environment with better planning

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 Protection

The Need for Non-Discretionary Interlocutory Appellate Review in Multidistrict Litigation

Multidistrict Litigation (MDL) is a tool for managing complex litigation by transferring cases with common questions of fact to a single judge for coordinated pretrial proceedings. The subject matter of the cases can run the gamut from airplane crashes to securities fraud to environmental disasters, such as the recent BP oil spill in the Gulf of Mexico. Today, about a third of all pending civil cases in federal court are part of the MDL system. A single judge renders all the important legal decisions in each MDL, exerting outsized impact on the parties and on the evolution of the law—and does so with virtually no scrutiny from other judges. This power centralization promotes efficient case management, but it can be an anathema to our conception of decentralized justice. One instance of unreviewable pretrial error can have immediate and sweeping impact on thousands of cases in one fell swoop. It is time to restore the balance of judicial power. This Article argues for an expansion of non-discretionary interlocutory appellate jurisdiction over certain legal rulings rendered in MDL cases. Any opportunity to appeal before the end of the case reflects an inherent value judgment that the immediate rights at stake outweigh the burdens that interlocutory review imposes on the courts. The discretionary approach to interlocutory appellate jurisdiction has proven generally adequate. But it is not adequate in the context of MDL proceedings, where the risks and consequences of legal error are heightened considerably. Ultimately, MDL cases tend to settle rather than proceed to final judgment, so the appellate courts rarely have an opportunity to clarify the law, and the settlements are often mispriced as a result of the uncertainty. The absence of appellate review also deprives our jurisprudence of one of its central features—the back-and-forth negotiation of legal principles that occurs when multiple jurists grapple with the same legal questions. Certain interlocutory MDL orders, then, warrant mandatory appellate jurisdiction. To qualify, the order should involve a pure issue of law in an unsettled area or in contravention of established precedent, and immediate appellate review should potentially be dispositive of a significant number of cases in the MDL. The guaranteed availability of immediate review in these circumstances would not come without costs, but the benefits would far outweigh them. Indeed, the right of immediate appeal would ensure the integrity of the MDL process on which our legal system has come so heavily to depend

The Need for Non-Discretionary Interlocutory Appellate Review in Multidistrict Litigation

Multidistrict Litigation (MDL) is a tool for managing complex litigation by transferring cases with common questions of fact to a single judge for coordinated pretrial proceedings. The subject matter of the cases can run the gamut from airplane crashes to securities fraud to environmental disasters, such as the recent BP oil spill in the Gulf of Mexico. Today, about a third of all pending civil cases in federal court are part of the MDL system. A single judge renders all the important legal decisions in each MDL, exerting outsized impact on the parties and on the evolution of the law—and does so with virtually no scrutiny from other judges. This power centralization promotes efficient case management, but it can be an anathema to our conception of decentralized justice. One instance of unreviewable pretrial error can have immediate and sweeping impact on thousands of cases in one fell swoop. It is time to restore the balance of judicial power. This Article argues for an expansion of non-discretionary interlocutory appellate jurisdiction over certain legal rulings rendered in MDL cases. Any opportunity to appeal before the end of the case reflects an inherent value judgment that the immediate rights at stake outweigh the burdens that interlocutory review imposes on the courts. The discretionary approach to interlocutory appellate jurisdiction has proven generally adequate. But it is not adequate in the context of MDL proceedings, where the risks and consequences of legal error are heightened considerably. Ultimately, MDL cases tend to settle rather than proceed to final judgment, so the appellate courts rarely have an opportunity to clarify the law, and the settlements are often mispriced as a result of the uncertainty. The absence of appellate review also deprives our jurisprudence of one of its central features—the back-and-forth negotiation of legal principles that occurs when multiple jurists grapple with the same legal questions. Certain interlocutory MDL orders, then, warrant mandatory appellate jurisdiction. To qualify, the order should involve a pure issue of law in an unsettled area or in contravention of established precedent, and immediate appellate review should potentially be dispositive of a significant number of cases in the MDL. The guaranteed availability of immediate review in these circumstances would not come without costs, but the benefits would far outweigh them. Indeed, the right of immediate appeal would ensure the integrity of the MDL process on which our legal system has come so heavily to depend

IoT and Sensor Networks in Industry and Society

The exponential progress of Information and Communication Technology (ICT) is one of the main elements that fueled the acceleration of the globalization pace. Internet of Things (IoT), Artificial Intelligence (AI) and big data analytics are some of the key players of the digital transformation that is affecting every aspect of human's daily life, from environmental monitoring to healthcare systems, from production processes to social interactions. In less than 20 years, people's everyday life has been revolutionized, and concepts such as Smart Home, Smart Grid and Smart City have become familiar also to non-technical users. The integration of embedded systems, ubiquitous Internet access, and Machine-to-Machine (M2M) communications have paved the way for paradigms such as IoT and Cyber Physical Systems (CPS) to be also introduced in high-requirement environments such as those related to industrial processes, under the forms of Industrial Internet of Things (IIoT or I2oT) and Cyber-Physical Production Systems (CPPS). As a consequence, in 2011 the German High-Tech Strategy 2020 Action Plan for Germany first envisioned the concept of Industry 4.0, which is rapidly reshaping traditional industrial processes. The term refers to the promise to be the fourth industrial revolution. Indeed, the first industrial revolution was triggered by water and steam power. Electricity and assembly lines enabled mass production in the second industrial revolution. In the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production. As opposed to the previous revolutions, Industry 4.0 takes advantage of Internet access, M2M communications, and deep learning not only to improve production efficiency but also to enable the so-called mass customization, i.e. the mass production of personalized products by means of modularized product design and flexible processes. Less than five years later, in January 2016, the Japanese 5th Science and Technology Basic Plan took a further step by introducing the concept of Super Smart Society or Society 5.0. According to this vision, in the upcoming future, scientific and technological innovation will guide our society into the next social revolution after the hunter-gatherer, agrarian, industrial, and information eras, which respectively represented the previous social revolutions. Society 5.0 is a human-centered society that fosters the simultaneous achievement of economic, environmental and social objectives, to ensure a high quality of life to all citizens. This information-enabled revolution aims to tackle today’s major challenges such as an ageing population, social inequalities, depopulation and constraints related to energy and the environment. Accordingly, the citizens will be experiencing impressive transformations into every aspect of their daily lives. This book offers an insight into the key technologies that are going to shape the future of industry and society. It is subdivided into five parts: the I Part presents a horizontal view of the main enabling technologies, whereas the II-V Parts offer a vertical perspective on four different environments. The I Part, dedicated to IoT and Sensor Network architectures, encompasses three Chapters. In Chapter 1, Peruzzi and Pozzebon analyse the literature on the subject of energy harvesting solutions for IoT monitoring systems and architectures based on Low-Power Wireless Area Networks (LPWAN). The Chapter does not limit the discussion to Long Range Wise Area Network (LoRaWAN), SigFox and Narrowband-IoT (NB-IoT) communication protocols, but it also includes other relevant solutions such as DASH7 and Long Term Evolution MAchine Type Communication (LTE-M). In Chapter 2, Hussein et al. discuss the development of an Internet of Things message protocol that supports multi-topic messaging. The Chapter further presents the implementation of a platform, which integrates the proposed communication protocol, based on Real Time Operating System. In Chapter 3, Li et al. investigate the heterogeneous task scheduling problem for data-intensive scenarios, to reduce the global task execution time, and consequently reducing data centers' energy consumption. The proposed approach aims to maximize the efficiency by comparing the cost between remote task execution and data migration. The II Part is dedicated to Industry 4.0, and includes two Chapters. In Chapter 4, Grecuccio et al. propose a solution to integrate IoT devices by leveraging a blockchain-enabled gateway based on Ethereum, so that they do not need to rely on centralized intermediaries and third-party services. As it is better explained in the paper, where the performance is evaluated in a food-chain traceability application, this solution is particularly beneficial in Industry 4.0 domains. Chapter 5, by De Fazio et al., addresses the issue of safety in workplaces by presenting a smart garment that integrates several low-power sensors to monitor environmental and biophysical parameters. This enables the detection of dangerous situations, so as to prevent or at least reduce the consequences of workers accidents. The III Part is made of two Chapters based on the topic of Smart Buildings. In Chapter 6, Petroșanu et al. review the literature about recent developments in the smart building sector, related to the use of supervised and unsupervised machine learning models of sensory data. The Chapter poses particular attention on enhanced sensing, energy efficiency, and optimal building management. In Chapter 7, Oh examines how much the education of prosumers about their energy consumption habits affects power consumption reduction and encourages energy conservation, sustainable living, and behavioral change, in residential environments. In this Chapter, energy consumption monitoring is made possible thanks to the use of smart plugs. Smart Transport is the subject of the IV Part, including three Chapters. In Chapter 8, Roveri et al. propose an approach that leverages the small world theory to control swarms of vehicles connected through Vehicle-to-Vehicle (V2V) communication protocols. Indeed, considering a queue dominated by short-range car-following dynamics, the Chapter demonstrates that safety and security are increased by the introduction of a few selected random long-range communications. In Chapter 9, Nitti et al. present a real time system to observe and analyze public transport passengers' mobility by tracking them throughout their journey on public transport vehicles. The system is based on the detection of the active Wi-Fi interfaces, through the analysis of Wi-Fi probe requests. In Chapter 10, Miler et al. discuss the development of a tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by Road Transport Enterprises (RTEs). The authors of this Chapter further provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The book ends with the two Chapters of the V Part on Smart Environmental Monitoring. In Chapter 11, He et al. propose a Sea Surface Temperature Prediction (SSTP) model based on time-series similarity measure, multiple pattern learning and parameter optimization. In this strategy, the optimal parameters are determined by means of an improved Particle Swarm Optimization method. In Chapter 12, Tsipis et al. present a low-cost, WSN-based IoT system that seamlessly embeds a three-layered cloud/fog computing architecture, suitable for facilitating smart agricultural applications, especially those related to wildfire monitoring. We wish to thank all the authors that contributed to this book for their efforts. We express our gratitude to all reviewers for the volunteering support and precious feedback during the review process. We hope that this book provides valuable information and spurs meaningful discussion among researchers, engineers, businesspeople, and other experts about the role of new technologies into industry and society