Cooperative Human-Centric Sensing Connectivity

Human-centric sensing (HCS) is a new concept relevant to Internet of Things (IoT). HCS connectivity, referred to as “smart connectivity,” enables applications that are highly personalized and often time-critical. In a typical HCS scenario, there may be many hundreds of sensor stream connections, centered around the human, who would be the determining factor for the number, the purpose, the direction, and the frequency of the sensor streams. This chapter examines the concepts of HCS communications, outlines the challenges, and defines a roadmap for solutions for realizing HCS networks. This chapter is organized as follows. Section 1 introduces the concept of cooperation in information and communications technologies (ICT), and in the context of IoT. Section 2 discusses cooperation in the context of the personal and extra-personal user space and identifies the remaining open challenges and requirements for realizing the benefits of this approach to enabling more resources and services in a hyper-connected society. Section 3 defines a roadmap toward realizing simple, efficient, and trustable systems based on advanced technologies combining security, cloud, and IoT/big data technologies and outlines the challenges related to this vision. Section 4 concludes the chapter

The Internet-of-Things Meets Business Process Management: Mutual Benefits and Challenges

The Internet of Things (IoT) refers to a network of connected devices collecting and exchanging data over the Internet. These things can be artificial or natural, and interact as autonomous agents forming a complex system. In turn, Business Process Management (BPM) was established to analyze, discover, design, implement, execute, monitor and evolve collaborative business processes within and across organizations. While the IoT and BPM have been regarded as separate topics in research and practice, we strongly believe that the management of IoT applications will strongly benefit from BPM concepts, methods and technologies on the one hand; on the other one, the IoT poses challenges that will require enhancements and extensions of the current state-of-the-art in the BPM field. In this paper, we question to what extent these two paradigms can be combined and we discuss the emerging challenges

Using Social Robots in Health Settings: Implications of Personalization on Human-Machine Communication

In view of the shortage of healthcare workers and a growing aging population, it is worthwhile to explore the applicability of new technologies in improving the quality of healthcare and reducing its cost. However, it remains a challenge to deploy such technologies in environments where individuals have limited knowledge about how to use them. Thus, this paper explores how the social robots designed for use in health settings in Australia have sought to overcome some of the limitations through personalization. Deployed in aged care and home-based care facilities, the social robots are person-centered, emphasizing the personalization of care with human-like attributes (e.g., human appearances) to engage in reciprocal communication with users. While there have been debates over the advantages and disadvantages of personalization, this paper discusses the implications of personalization on the design of the robots for enhancing engagement, empowerment and enablement in health settings

Hybrid Internal Anomaly Detection System for IoT: Reactive Nodes with Cross-Layer Operation

We present a hybrid internal anomaly detection system that shares detection tasks between router and nodes. It allows nodes to react instinctively against the anomaly node by enforcing temporary communication ban on it. Each node monitors its own neighbors and if abnormal behavior is detected, the node blocks the packets of the anomaly node at link layer and reports the incident to its parent node. A novel RPL control message, Distress Propagation Object (DPO), is formulated and used for reporting the anomaly and network activities to the parent node and subsequently to the router. The system has configurable profile settings and is able to learn and differentiate between the nodes normal and suspicious activities without a need for prior knowledge. It has different subsystems and operation phases that are distributed in both the nodes and router, which act on data link and network layers. The system uses network fingerprinting to be aware of changes in network topology and approximate threat locations without any assistance from a positioning subsystem. The developed system was evaluated using test-bed consisting of Zolertia nodes and in-house developed PandaBoard based gateway as well as emulation environment of Cooja. The evaluation revealed that the system has low energy consumption overhead and fast response. The system occupies 3.3 KB of ROM and 0.86 KB of RAM for its operations. Security analysis confirms nodes reaction against abnormal nodes and successful detection of packet flooding, selective forwarding, and clone attacks. The system’s false positive rate evaluation demonstrates that the proposed system exhibited 5% to 10% lower false positive rate compared to simple detection system

Low power wide area network, cognitive radio and the internet of things : potentials for integration

The Internet of Things (IoT) is an emerging paradigm that enables many beneficial and prospective application areas, such as smart metering, smart homes, smart industries, and smart city architectures, to name but a few. These application areas typically comprise end nodes and gateways that are often interconnected by low power wide area network (LPWAN) technologies, which provide low power consumption rates to elongate the battery lifetimes of end nodes, low IoT device development/purchasing costs, long transmission range, and increased scalability, albeit at low data rates. However, most LPWAN technologies are often confronted with a number of physical (PHY) layer challenges, including increased interference, spectral inefficiency, and/or low data rates for which cognitive radio (CR), being a predominantly PHY layer solution, suffices as a potential solution. Consequently, in this article, we survey the potentials of integrating CR in LPWAN for IoT-based applications. First, we present and discuss a detailed list of different state-of-the-art LPWAN technologies; we summarize the most recent LPWAN standardization bodies, alliances, and consortia while emphasizing their disposition towards the integration of CR in LPWAN.We then highlight the concept of CR in LPWAN via a PHY-layer front-end model and discuss the benefits of CR-LPWAN for IoT applications. A number of research challenges and future directions are also presented. This article aims to provide a unique and holistic overview of CR in LPWAN with the intention of emphasizing its potential benefits.This work was supported by the Council for Scientific and Industrial Research, Pretoria, South Africa, through the Smart Networks collaboration initiative and Internet of Things (IoT)-Factory Program (funded by the Department of Science and Innovation (DSI), South Africa).http://www.mdpi.com/journal/sensorsam2021Electrical, Electronic and Computer Engineerin

Safe Intelligent Driver Assistance System in V2X Communication Environments based on IoT

In the modern world, power and speed of cars have increased steadily, as traffic continued to increase. At the same time highway-related fatalities and injuries due to road incidents are constantly growing and safety problems come first. Therefore, the development of Driver Assistance Systems (DAS) has become a major issue. Numerous innovations, systems and technologies have been developed in order to improve road transportation and safety. Modern computer vision algorithms enable cars to understand the road environment with low miss rates. A number of Intelligent Transportation Systems (ITSs), Vehicle Ad-Hoc Networks (VANETs) have been applied in the different cities over the world. Recently, a new global paradigm, known as the Internet of Things (IoT) brings new idea to update the existing solutions. Vehicle-to-Infrastructure communication based on IoT technologies would be a next step in intelligent transportation for the future Internet-of-Vehicles (IoV). The overall purpose of this research was to come up with a scalable IoT solution for driver assistance, which allows to combine safety relevant information for a driver from different types of in-vehicle sensors, in-vehicle DAS, vehicle networks and driver`s gadgets. This study brushed up on the evolution and state-of-the-art of Vehicle Systems. Existing ITSs, VANETs and DASs were evaluated in the research. The study proposed a design approach for the future development of transport systems applying IoT paradigm to the transport safety applications in order to enable driver assistance become part of Internet of Vehicles (IoV). The research proposed the architecture of the Safe Intelligent DAS (SiDAS) based on IoT V2X communications in order to combine different types of data from different available devices and vehicle systems. The research proposed IoT ARM structure for SiDAS, data flow diagrams, protocols. The study proposes several IoT system structures for the vehicle-pedestrian and vehicle-vehicle collision prediction as case studies for the flexible SiDAS framework architecture. The research has demonstrated the significant increase in driver situation awareness by using IoT SiDAS, especially in NLOS conditions. Moreover, the time analysis, taking into account IoT, Cloud, LTE and DSRS latency, has been provided for different collision scenarios, in order to evaluate the overall system latency and ensure applicability for real-time driver emergency notification. Experimental results demonstrate that the proposed SiDAS improves traffic safety

Functional Programming for Embedded Systems

Embedded Systems application development has traditionally been carried out in low-level machine-oriented programming languages like C or Assembler that can result in unsafe, error-prone and difficult-to-maintain code. Functional programming with features such as higher-order functions, algebraic data types, polymorphism, strong static typing and automatic memory management appears to be an ideal candidate to address the issues with low-level languages plaguing embedded systems. However, embedded systems usually run on heavily memory-constrained devices with memory in the order of hundreds of kilobytes and applications running on such devices embody the general characteristics of being (i) I/O- bound, (ii) concurrent and (iii) timing-aware. Popular functional language compilers and runtimes either do not fare well with such scarce memory resources or do not provide high-level abstractions that address all the three listed characteristics. This work attempts to address this gap by investigating and proposing high-level abstractions specialised for I/O-bound, concurrent and timing-aware embedded-systems programs. We implement the proposed abstractions on eagerly-evaluated, statically-typed functional languages running natively on microcontrollers. Our contributions are divided into two parts - Part 1 presents a functional reactive programming language - Hailstorm - that tracks side effects like I/O in its type system using a feature called resource types. Hailstorm’s programming model is illustrated on the GRiSP microcontroller board.Part 2 comprises two papers that describe the design and implementation of Synchron, a runtime API that provides a uniform message-passing framework for the handling of software messages as well as hardware interrupts. Additionally, the Synchron API supports a novel timing operator to capture the notion of time, common in embedded applications. The Synchron API is implemented as a virtual machine - SynchronVM - that is run on the NRF52 and STM32 microcontroller boards. We present programming examples that illustrate the concurrency, I/O and timing capabilities of the VM and provide various benchmarks on the response time, memory and power usage of SynchronVM

Dinamičko formiranje distribuiranog mikro okruženja u računarstvu u oblaku

This thesis presents research in the field of distributed systems. We present the dynamic organization of geodistributed edge nodes into micro data-centers forming micro clouds to cover any arbitrary area and expand capacity, availability, and reliability. A cloud organization is used as an influence with adaptations for a different environment with a clear separation of concerns, and native applications model that can leverage the newly formed system. With the separation of concerns setup, edge-native applications model, and a unified node organization, we are moving towards the idea of edge computing as a service, like any other utility in cloud computing. We also give formal models for all protocols used for the creation of such a system.U sklopu disertacije izvršeno je istraživanje u oblasti distribuiranih sistema. Predstavili smo dinamičku organizaciju geo-distribuiranih čvorova u mikro centre za obradu podataka koji formiraju mikro okruženja računarstva u oblaku kako bi pokrili bilo koje proizvoljno područje i proširili kapacitet, dostupnost i pouzdanost. Koristili smo organizaciju računarstva u oblaku kao inspiraciju, sa adaptacijama za drugačije okruženje sa jasnom podelom nadležnosti, i modelom aplikacija koji može da iskoristi novoformirani sistem. Jasna podela nadležnosti, model aplikacija i dinamička organizacijom čvorova, čine da se predstavljeni model ponude kao i bilo koji drugi uslužni servis. Takođe dajemo formalne modele za sve protokole koji se koriste za stvaranje takvog sistema