Towards the Internet of Behaviors in Smart Cities through a Fog-To-Cloud Approach

Recent advances in the Internet of Things (IoT) and the rise of the Internet of Behavior (IoB) have made it possible to develop real-time improved traveler assistance tools for mobile phones, assisted by cloud-based machine learning and using fog computing in between the IoT and the Cloud. Within the Horizon2020-funded mF2C project, an Android app has been developed exploiting the proximity marketing concept and covers the essential path through the airport onto the flight, from the least busy security queue through to the time to walk to the gate, gate changes, and other obstacles that airports tend to entertain travelers with. It gives travelers a chance to discover the facilities of the airport, aided by a recommender system using machine learning that can make recommendations and offer vouchers based on the traveler’s preferences or on similarities to other travelers. The system provides obvious benefits to airport planners, not only people tracking in the shops area, but also aggregated and anonymized view, like heat maps that can highlight bottlenecks in the infrastructure, or suggest situations that require intervention, such as emergencies. With the emergence of the COVID-19 pandemic, the tool could be adapted to help in social distancing to guarantee safety. The use of the fog-to-cloud platform and the fulfillment of all centricity and privacy requirements of the IoB give evidence of the impact of the solution. Doi: 10.28991/HIJ-2021-02-04-01 Full Text: PD

Weathering Heights: The Emergence of Aeronautical Meteorology as an Infrastructural Science

The first half of the 20th century was an era of weathering heights. As the development of powered flight made the free atmosphere militarily and economically relevant, meteorologists encountered new kinds of weather conditions at altitude. Pilots also learned to weather heights, as they struggled to survive in an atmosphere that revealed surprising dangers like squall lines, fog, icing, and turbulence. Aeronautical meteorology evolved out of these encounters, a heterogeneous body of knowledge that included guidelines for routing aircraft, networks for observing the upper air using scientific instruments, and procedures for synthesizing those observations into weather forecasts designed for pilots. As meteorologists worked to make the skies safe for aircraft, they remade their science around the physics of the free atmosphere. The dissertation tracks a small group of Scandinavian meteorologists, the “Bergen School,” who came to be the dominant force in world meteorology by forecasting for Arctic exploration flights, designing airline weather services, and training thousands of military weather officers during World War II. After the war, some of these military meteorologists invented the TV weather report (now the most widely consumed genre of popular science) by combining the narrative of the pre-fight weather briefing with the visual style of comic-illustrated training manuals. The dissertation argues that aeronautical meteorology is representative of what I call the “infrastructural sciences,” a set of organizationally intensive, purposefully invisible, applied sciences. These sciences enable the reliable operation of large technological systems by integrating theory-derived knowledge with routine environmental observation. The dissertation articulates a set of characteristics for identifying and understanding infrastructural science, and then argues that these culturally modest technical practices play a pervasive role in maintaining industrial lifeways. It concludes by noting that while meteorology successfully helped aviation become a reliable, taken-for-granted part of the transportation system, the interests of aviation created a meteorology that centered on the needs of pilots, to the detriment of fields like agricultural climatology

Urban Air Mobility Market Study

The Booz Allen Team explored market size and potential barriers to Urban Air Mobility (UAM) by focusing on three potential markets – Airport Shuttle, Air Taxi, and Air Ambulance. We found that the Airport Shuttle and Air Taxi markets are viable, with a significant total available market value in the U.S. of $500 billion, for a fully unconstrained scenario. In this unconstrained best-case scenario, passengers would have the ability to access and fly a UAM at any time, from any location to any destination, without being hindered by constraints such as weather, infrastructure, or traffic volume. Significant legal and regulatory, weather, certification, public perception, and infrastructure constraints exist, which reduce the market potential for these applications to only about 0.5$2.5 billion, in the near term. However, we determined that these constraints can be addressed through ongoing intra-governmental partnerships, government and industry collaboration, strong industry commitment, and existing legal and regulatory enablers. We found that the Air Ambulance market is not a viable market if served by electric vertical takeoff and landing (eVTOL) vehicles due to technology constraints but may potentially be viable if a hybrid VTOL aircraft are utilized

Standardization Roadmap for Unmanned Aircraft Systems, Version 2.0

This Standardization Roadmap for Unmanned Aircraft Systems, Version 2.0 (“roadmap”) is an update to version 1.0 of this document published in December 2018. It identifies existing standards and standards in development, assesses gaps, and makes recommendations for priority areas where there is a perceived need for additional standardization and/or pre-standardization R&D. The roadmap has examined 78 issue areas, identified a total of 71 open gaps and corresponding recommendations across the topical areas of airworthiness; flight operations (both general concerns and application-specific ones including critical infrastructure inspections, commercial services, and public safety operations); and personnel training, qualifications, and certification. Of that total, 47 gaps/recommendations have been identified as high priority, 21 as medium priority, and 3 as low priority. A “gap” means no published standard or specification exists that covers the particular issue in question. In 53 cases, additional R&D is needed. As with the earlier version of this document, the hope is that the roadmap will be broadly adopted by the standards community and that it will facilitate a more coherent and coordinated approach to the future development of standards for UAS. To that end, it is envisioned that the roadmap will continue to be promoted in the coming year. It is also envisioned that a mechanism may be established to assess progress on its implementation

Application of systems engineering to complex systems and system of systems

2017 Spring.Includes bibliographical references.This dissertation is an investigation of system of systems (SoS). It begins with an analysis to define, with some rigor, the similarities and differences between complex systems and SoS. With this foundation, the baseline concept is development for several different types of systems and they are used as a practical approach to compare and contrast complex systems versus SoS. The method is to use a progression from simple to more complex systems. Specifically, a pico hydro electric power generation system, a hybrid renewable electric power generation system, a LEO satellites system, and Molniya orbit satellite system are investigated. In each of these examples, systems engineering methods are applied for the development of a baseline solution. While these examples are complex, they do not rise to the level of a SoS. In contrast, a multi-spectral drone detection system for protection of airports is investigated and a baseline concept for it is generated. The baseline is shown to meet the minimum requirements to be considered a SoS. The system combines multiple sensor types to distinguish drones as targets. The characteristics of the drone detection system which make it a SoS are discussed. Since emergence is considered by some to be a characteristic of a SoS, it is investigated. A solution to the problem of determining if system properties are emergent is presented and necessary and sufficient conditions for emergence are developed. Finally, this work concludes with a summary and suggestions for additional work

Defense Technical Information Center thesaurus

This DTIC Thesaurus provides a basic multidisciplinary subject term vocabulary used by DTIC to index and retrieve scientific and technical information from its various data bases and to aid DTIC`s users in their information storage and retrieval operations. It includes an alphabetical posting term display, a hierarchy display, and a Keywork Out of Context (KWOC) display

A Unified Recommendation Framework for Data-driven, People-centric Smart Home Applications

With the rapid growth in the number of things that can be connected to the internet, Recommendation Systems for the IoT (RSIoT) have become more significant in helping a variety of applications to meet user preferences, and such applications can be smart home, smart tourism, smart parking, m-health and so on. In this thesis, we propose a unified recommendation framework for data-driven, people-centric smart home applications. The framework involves three main stages: complex activity detection, constructing recommendations in timely manner, and insuring the data integrity. First, we review the latest state-of-the-art recommendations methods and development of applications for recommender system in the IoT so, as to form an overview of the current research progress. Challenges of using IoT for recommendation systems are introduced and explained. A reference framework to compare the existing studies and guide future research and practices is provided. In order to meet the requirements of complex activity detection that helps our system to understand what activity or activities our user is undertaking in relatively high level. We provide adequate resources to be fit for the recommender system. Furthermore, we consider two inherent challenges of RSIoT, that is, capturing dynamicity patterns of human activities and system update without a focus on user feedback. Based on these, we design a Reminder Care System (RCS) which harnesses the advantages of deep reinforcement learning (DQN) to further address these challenges. Then we utilize a contextual bandit approach for improving the quality of recommendations by considering the context as an input. We aim to address not only the two previous challenges of RSIoT but also to learn the best action in different scenarios and treat each state independently. Last but not least, we utilize a blockchain technology to ensure the safety of data storage in addition to decentralized feature. In the last part, we discuss a few open issues and provide some insights for future directions

System elements required to guarantee the reliability, availability and integrity of decision-making information in a complex airborne autonomous system

Current air traffic management systems are centred on piloted aircraft, in which all the main decisions are made by humans. In the world of autonomous vehicles, there will be a driving need for decisions to be made by the system rather than by humans due to the benefits of more automation such as reducing the likelihood of human error, handling more air traffic in national airspace safely, providing prior warnings of potential conflicts etc. The system will have to decide on courses of action that will have highly safety critical consequences. One way to ensure these decisions are robust is to guarantee that the information being used for the decision is valid and of very high integrity. [Continues.