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

mF2C: Towards a coordinated management of the IoT-fof-cloud continuum

Fog computing enables location dependent resource allocation and low latency services, while fostering novel market and business opportunities in the cloud sector. Aligned to this trend, we refer to Fog-tocloud (F2C) computing system as a new pool of resources, set into a layered and hierarchical model, intended to ease the entire fog and cloud resources management and coordination. The H2020 project mF2C aims at designing, developing and testing a first attempt for a real F2C architecture. This document outlines the architecture and main functionalities of the management framework designed in the mF2C project to coordinate the execution of services in the envisioned set of heterogeneous anddistributed resources.Postprint (author's final draft

A data quarantine model to secure data in edge computing

Edge computing provides an agile data processing platform for latency-sensitive and communication-intensive applications through a decentralized cloud and geographically distributed edge nodes. Gaining centralized control over the edge nodes can be challenging due to security issues and threats. Among several security issues, data integrity attacks can lead to inconsistent data and intrude edge data analytics. Further intensification of the attack makes it challenging to mitigate and identify the root cause. Therefore, this paper proposes a new concept of data quarantine model to mitigate data integrity attacks by quarantining intruders. The efficient security solutions in cloud, ad-hoc networks, and computer systems using quarantine have motivated adopting it in edge computing. The data acquisition edge nodes identify the intruders and quarantine all the suspected devices through dimensionality reduction. During quarantine, the proposed concept builds the reputation scores to determine the falsely identified legitimate devices and sanitize their affected data to regain data integrity. As a preliminary investigation, this work identifies an appropriate machine learning method, linear discriminant analysis (LDA), for dimensionality reduction. The LDA results in 72.83% quarantine accuracy and 0.9 seconds training time, which is efficient than other state-of-the-art methods. In future, this would be implemented and validated with ground truth data

Adoption of Industry 4.0 technologies in airports -- A systematic literature review

Airports have been constantly evolving and adopting digital technologies to improve operational efficiency, enhance passenger experience, generate ancillary revenues and boost capacity from existing infrastructure. The COVID-19 pandemic has also challenged airports and aviation stakeholders alike to adapt and manage new operational challenges such as facilitating a contactless travel experience and ensuring business continuity. Digitalisation using Industry 4.0 technologies offers opportunities for airports to address short-term challenges associated with the COVID-19 pandemic while also preparing for future long-term challenges that ensue the crisis. Through a systematic literature review of 102 relevant articles, we discuss the current state of adoption of Industry 4.0 technologies in airports, the associated challenges as well as future research directions. The results of this review suggest that the implementation of Industry 4.0 technologies is slowly gaining traction within the airport environment, and shall continue to remain relevant in the digital transformation journeys in developing future airports

Air Taxis: A Technological Breakthrough to Beat the Traffic Woes

Traffic problems across the major cities around the world and the ever-growing population have put immense stress on countries’ smart infrastructure needs and requirements, particularly in emerging economies such as India. In such countries, existing urban transport modes have failed to accommodate the rising travel demand, which means traffic congestion will likely multiply further in the coming years. This distressing situation creates opportunities for automobile and aircraft makers to develop state-of-the-art urban air mobility (UAM) solutions. The electric vertical take-off and landing (eVTOL) vehicles seem to represent the future of urban mobility. Commercialized air taxis have the potential to completely disrupt the urban transportation system and relieve the urban streets from congestion. The case discusses the factors facilitating a speedy drift towards adopting air taxis and the recent developments in the UAM industry. To explore the air taxi market opportunities and business feasibility, the case examines the UAM ecosystem, the related cost and technology components, the industry\u27s latest competitive landscape, and anticipated barriers to the successful implementation of the air taxi business. The case outlines allied businesses and complementary revenue streams that the UAM sector would encourage and, thus, help developing nations to grow technologically and economically

Condition-based maintenance for major airport baggage systems

Purpose: The aim of this paper is to develop a contribution to knowledge that adds to theempirical evidence of predictive condition-based maintenance by demonstrating how theavailability and reliability of current assets can be improved without costly capital investment,resulting in overall system performance improvements.Methodology: The empirical, experimental approach, technical action research (TAR), wasdesigned to study a major Middle-Eastern airport baggage handling operation. A predictivecondition-based maintenance prototype station was installed to monitor the condition of ahighly complex system of static and moving assets.Findings. The research provides evidence that the performance frontier for airport baggagehandling systems can be improved using automated dynamic monitoring of the vibration anddigital image data on baggage trays as they pass a service station. The introduction of low-endinnovation, which combines advanced technology and low-cost hardware, reduced assetfailures in this complex, high speed operating environment.Originality/Value: The originality derives from the application of existing hardware with thecombination of Edge and Cloud computing software through architectural innovation resultingin adaptations to an existing baggage handling system within the context of a time-criticallogistics system.Keywords: IoT, Condition-based maintenance, Predictive maintenance, Edge computing, IoT,Technical Action Research, Theory of Performance Frontiers,Case Stud

Enterprise IoT Security and Scalability : How Unikernels can Improve the Status Quo

Postprin

A holistic review of cybersecurity and reliability perspectives in smart airports

Advances in the Internet of Things (IoT) and aviation sector have resulted in the emergence of smart airports. Services and systems powered by the IoT enable smart airports to have enhanced robustness, efficiency and control, governed by real-time monitoring and analytics. Smart sensors control the environmental conditions inside the airport, automate passenger-related actions and support airport security. However, these augmentations and automation introduce security threats to network systems of smart airports. Cyber-attackers demonstrated the susceptibility of IoT systems and networks to Advanced Persistent Threats (APT), due to hardware constraints, software flaws or IoT misconfigurations. With the increasing complexity of attacks, it is imperative to safeguard IoT networks of smart airports and ensure reliability of services, as cyber-attacks can have tremendous consequences such as disrupting networks, cancelling travel, or stealing sensitive information. There is a need to adopt and develop new Artificial Intelligence (AI)-enabled cyber-defence techniques for smart airports, which will address the challenges brought about by the incorporation of IoT systems to the airport business processes, and the constantly evolving nature of contemporary cyber-attacks. In this study, we present a holistic review of existing smart airport applications and services enabled by IoT sensors and systems. Additionally, we investigate several types of cyber defence tools including AI and data mining techniques, and analyse their strengths and weaknesses in the context of smart airports. Furthermore, we provide a classification of smart airport sub-systems based on their purpose and criticality and address cyber threats that can affect the security of smart airport\u27s networks

A holistic review of cybersecurity and reliability perspectives in smart airports

Advances in the Internet of Things (IoT) and aviation sector have resulted in the emergence of smart airports. Services and systems powered by the IoT enable smart airports to have enhanced robustness, efficiency and control, governed by real-time monitoring and analytics. Smart sensors control the environmental conditions inside the airport, automate passenger-related actions and support airport security. However, these augmentations and automation introduce security threats to network systems of smart airports. Cyber-attackers demonstrated the susceptibility of IoT systems and networks to Advanced Persistent Threats (APT), due to hardware constraints, software flaws or IoT misconfigurations. With the increasing complexity of attacks, it is imperative to safeguard IoT networks of smart airports and ensure reliability of services, as cyber-attacks can have tremendous consequences such as disrupting networks, cancelling travel, or stealing sensitive information. There is a need to adopt and develop new Artificial Intelligence (AI)-enabled cyber-defence techniques for smart airports, which will address the challenges brought about by the incorporation of IoT systems to the airport business processes, and the constantly evolving nature of contemporary cyber-attacks. In this study, we present a holistic review of existing smart airport applications and services enabled by IoT sensors and systems. Additionally, we investigate several types of cyber defence tools including AI and data mining techniques, and analyse their strengths and weaknesses in the context of smart airports. Furthermore, we provide a classification of smart airport sub-systems based on their purpose and criticality and address cyber threats that can affect the security of smart airport\u27s networks

Systems approach for applying remote video technology and the Internet to real time weather and runway condition reporting for aviation use: Case study at rural airports in interior Alaska

Thesis (Ph.D.) University of Alaska Fairbanks, 2000Aviation is critical to the infrastructure of Alaska. However, systems that provide runway and weather condition information about rural airstrips are not meeting the needs of the aviation community. Accordingly, aviation safety is compromised, efficiency of operations is reduced and service to clients is mediocre. Research was conducted to determine methods of improving the accuracy and reliability of runway and weather condition reporting Systems in Interior Alaska. A thorough background study of current reporting systems was conducted. A statistical study of aviation accidents in Interior Alaska was completed to document the premise that runway condition and weather reporting systems contribute to the problem. Current reporting systems were analyzed to isolate root causes of system degradation. An analysis of primary stakeholders associated with aviation reporting systems was completed. An hypothesis was formed which favored the use of remote video camera technology to provide near real-time weather information directly to end users A $114 K grant was obtained to conduct a test of the capabilities and benefits that would accrue from transmitting images of distant runway and sky conditions onto the Internet. For nine months, images of the sky and runway from three distant airstrips in Ruby, Kaltag and Anaktuvuk Pass, Alaska were transferred every thirty minutes to a publicly accessible website for use by the aviation community in assessing current conditions for preflight planning. Technical feasibility was confirmed. It was clearly determined that the system exceeded the expectations of the aviation community and provided greatly improved weather information to pilots. The aviation community in Interior Alaska has embraced the concept, used it operationally and declared it to be a critical enhancement to current systems. The project was an overwhelming success as confirmed by surveys, national and international media releases, and intense interest in the project by both private and governmental agencies. Aspects of the system are now patent pending. The research concluded that the remote video concept should be expanded throughout Alaska under the auspices of the Federal Aviation Administration (FAA) and/or the National Weather Service (NWS). Strong evidence was obtained to support potential expansion throughout the United States and internationally