We study the use of 3D Ray Tracing (RT) to construct radiomaps for WLAN Received Signal Strength (RSS) fingerprint-based positioning, in conjunction with calibration techniques to make the overall process device-independent. RSS data collection might be a tedious and time-consuming process and also the measured radiomap accuracy and applicability is subject to potential changes in the wireless environment. Therefore, RT becomes a more attractive and efficient way to generate radiomaps. Moreover, traditional fingerprint-based methods lead to radiomaps which are restricted to the device used to generate the radiomap and fail to provide acceptable performance when different devices are considered. We address both challenges by exploiting 3D RT-generated radiomaps and using linear data transformation to match the characteristics of various devices. We evaluate the efficiency of this approach in terms of the time spent to create the radiomap, the amount of data required to calibrate the radiomap for different devices and the positioning error which is compared against the case of using dedicated radiomaps collected with each device. � 2012 IEEE.

[No abstract available]

This paper presents a Wi-Fi Evil Twin, Man in the Middle attack (MiTM), which utilizes channel switch announcement (802.11h). The proposed technique examines and demonstrates through measurements the feasibility to perform a successful MiTM attack, when the target receives a lower received signal strength from the rogue access point (AP), compared to the received signal strength received by the legitimate AP. The above signal strength condition can allow the execution of a successful MiTM attack from relatively longer distances, since the rogue AP does not have to compete, signal strength wise, with the legitimate AP. Initial results suggest that the attack can be successfully performed. Furthermore, the attack is specific to a target and does not disrupt the operation of other targets, making the attack stealthy. � 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

This work proposes a novel methodology for the evaluation of indoor positioning systems, by adopting a binomial distribution approach during the evaluation process. The positioning accuracy achieved by any Real Time Localisation System (RTLS) is affected by various critical factors, such as the network infrastructure, the implemented positioning algorithms, the environment complexity, the dynamic changes that occur, the device diversity etc. The aim of the suggested methodology is to allow the evaluation of the expected accuracy of a deployed positioning system, under its actual operating conditions. The data collected by the binomial experiment is statistically processed, in order for the evaluator to calculate the strength of his evidence, and finally decide whether the declared accuracy can actually be met or not. The proposed approach, due to its robustness, can be of significant value in device diversity scenarios, organic and dynamic environments. � 2013 IEEE.

A modelling approach is presented, based on a modified form of the Fresnel diffraction integral. The approach combines contributions through different building elements and interfaces, e.g. windows, walls and doors, in order to calculate the overall signal contributed to a certain point inside a building. The method could be used to investigate coverage and interference issues when overlaying line of site microcells with in-building picocells or similar scenarios where there is a line of site with the building of interest. Two different cases are considered depending on the receiver position within the building. The first case refers to a receiver position in the first room next to the external wall, while the second case to a position anywhere else in the building. The predicted results are compared with a set of measured data recorded in 3 different UK cities.

One of the main advantages when comparing time over signal strength localization methods, is that the former do not require the creation of fingerprint databases. On the other hand, the majority of time based methods require some sort of clock synchronization due to the drifting of the local clocks. This paper presents an innovative time-based localization method which utilizes the information provided by 802.11 Beacon packet data. The advantage of this method over other time based methods is that the Mobile Terminal (MT) does not require to establish a connection to an Access Point (AP), or to send and receive packets as other time based methods do. Also, the proposed method does not require any clock synchronization. The method works by analyzing Beacon timestamp and MAC timestamp. By using Beacon Interval, Beacon timestamp and Service Set Identifier (SSID) of a packet, it has been made possible to optimally process the collected MAC timestamps to provide a hybrid TDoA-ToA localization method with an average error of less than 2.5 meters. � 2013 IEEE.

Low probability high impact events (LoPHIEs) disrupt organizations� processes severely. Existing methods used for the anticipation and management of such events, suffer from common limitations resulting in a huge impact to the quantification of probability, uncertainty and risk. Continues studies in the field of Crisis Informatics, present an opportunity for the development of a framework that fits the uncertainty related properties of LoPHIEs. The paper identifies the need for the development and conduction of a series of experiments, aiming to address the factors that qualify Collective Intelligence-enabled Information Systems with respect to their applicability towards support for LoPHIEs; and aims to propose an experiment framework as a methodology for scenario design in LoPHIEs settings. � 2017, Springer International Publishing AG.

A novel, multi-slope dual breakpoint model for predicting path-loss in Ultra-Wideband (UWB) off-body communication channels, is proposed. This model is based on real-body measurements, carried out in the frequency range between 3.5GHz-6.5GHz, in an anechoic chamber. New parameters that describe this specific propagation environment are presented and evaluated. Results show that the first breakpoint point angle lies in the lit region of the transmitter and increases exponentially with distance until it rises to its threshold value. Based on this finding the near and far field areas for BAP (Body to Access Point) channels are defined. In addition, newly estimated decay coefficients suggest severe degradation as the receiver moves in between the two critical angles. Finally, techniques for model expansion in two dimensions are discussed. � 2008 IEEE.

[No abstract available]

Robotic systems in Ageing Well, like GrowMeUp, are among those assistive technologies, providing companionship and offering functionality related to the support of active and independent living, monitoring and maintaining safety, and enhancement of health and psychological well-being of the elderly. The work presented in this paper is based on the context of GrowMeUp project and focuses on presenting the main novelties introduced with the GrowMeUp system, providing a robotic cloud ecosystem, able to support, encourage and engage the older persons to stay socially involved and longer active and independent, in carrying out their daily life at home. Emphasis is given on the important issues of end user's acceptance, usability and affordability and how technologies like cloud computing and different learning and intelligent dialoguing mechanisms are brought together in one solution to address these issues. � Springer International Publishing Switzerland 2016.

Time-based localization methods can be especially useful in dynamic environments, where the usefulness of Received Signal Strength (RSS) fingerprint based methods can be limited. Typical 'off the shelf' 802.11 network packet time-based methods, tend to collect a large number of packets and apply statistical analysis in order to localize a user. This packet collection process typically lies in the range of minutes, thus turning this type of localization into a non-real time process. This paper presents a method to accelerate network packet time based methods. By accelerating packet capturing in conjunction with packet validation, it has been shown that the localization process time can be shortened without reducing positioning accuracy. � 2014 IEEE.

[No abstract available]

This study proposes a unifying framework for m-Health video communication systems that provides for the joint optimization of video quality, bitrate demands, and encoding time. The framework is video modality and infrastructure independent and facilitates adaptation to the best available encoding mode that satisfies underlying technology and application imposed constraints. The scalability of the proposed algorithm is demonstrated using different HEVC encoding configurations and realistic modelling of 802.11? wireless infrastructure for emergency scenery and response videos. Extensive experimentation shows that a jointly optimal solution in the encoding time, bitrate, and video quality space is feasible. � 2015 IEEE.

The International Workshop on Adaptive Support for Team Collaboration (ASTC 2011) [1] was held in conjunction with the International Conference on User Modeling, Adaptation, and Personalization (UMAP2011), Girona, Spain, July 15, 2011. It was organized with the aim to bring together researchers from different scientific fields and research communities to exchange experiences on how collaboration within teams can be supported through the employment of adaptivity that is grounded on the characteristics of the teams and their individual members, their activities and social bonds. � 2012 Springer-Verlag.

In today's world, children are increasingly interacting with AI technologies as part of their daily routines. However, many children may not fully grasp how these technologies function or their implications. Misconceptions about AI capabilities, risks, and benefits abound, underlining the importance of early education on the subject. Designing educational tools and materials tailored for children necessitates a deep understanding of their existing knowledge and perceptions of AI. By leveraging children's insights and experiences with AI, we can develop effective educational strategies that cater to their specific needs and enhance their understanding of this rapidly evolving technology. � 2024 Owner/Author.

Artificial Intelligence (AI) advances in healthcare underpin timely and informed interventions that can elevate the quality of care for the benefit of the citizen. This can be especially beneficial for Intensive Care Unit (ICU) patients. The goal of this study is to develop an interoperable electronic health record (EHR) system, integrating reproducible AI-based algorithms for ICU services, linked with medical data and healthcare status visualizations, that will allow healthcare professionals to proceed to more informed diagnosis and targeted, personalized treatments. From a data science perspective, AI-based algorithms will first rely on the use of retrospective data via the openly available MIMIC dataset, investigating primarily the early prediction of Sepsis, and secondarily the length of ICU stay and rehospitalization probability. Emphasis will be given to explainability and ethical AI development. Within the context of the 'HospAItal' project, real-life pilots will take place at the Nicosia General Hospital (NGH) of Cyprus, assessing the clinical impact of the proposed system while using prospective data to retrain and advance the precision of the developed algorithms.Clinical Relevance: The proposed AI-based system targets timely and informed healthcare interventions for ICU patients at risk of Sepsis, aspiring to increase the quality of care while contributing to more efficient ICU expenditures management. � 2023 IEEE.

Artificial Intelligence (AI) advances are pushing the boundaries across research domains with AI-driven solutions in healthcare claiming a significant share. A key objective of these studies concerns the timely prediction of various pathological conditions. Sepsis is a life-threatening syndrome and one of the main causes of death in intensive care unit (ICU) patients. As it becomes a major health problem worldwide, sepsis early prediction could assist healthcare professionals towards making informed clinical decisions, and thereby, significantly reducing the sepsis' morbidity and mortality. A notable body of literature involving the use of AI for sepsis prediction exists. However, to the best of our knowledge, only a handful of studies focus on performing a systematic review of the AI enabled solutions for sepsis prediction in ICUs. In this context, the present paper aims to identify knowledge gaps, stimulate interest and yield motivations for future research. Moreover, to discuss ethical and explainability aspects and associated challenges. The literature search was conducted between February 2023 and April 2023 and considered eligible articles published within the last five years. � 2023 IEEE.

Planning and deploying a functional large scale Wireless Sensor Network (WSN) or a Network of Internet of Things (IoTs) is a challenging task, especially in complex urban environments. The typical complex urban environment distorts the RF signal from nodes due to multipath and as a result the connectivity of the network could be problematic. The need for accurate and reliable network simulators is mandatory to extract meaningful results. The fact that existing network layer simulators are unable to accurately simulate the physical layer effects, renders them inefficient to provide those results. In this work, we experimentally measure the signal strength of Crossbow TelosB node in different setups. The observations indicate that the actual behaviour of wireless nodes is highly variable and bimodal. Such an outcome stipulates the need of utilizing effective cross-layer simulators that can incorporate the physical layer conditions, in order to accurately simulate the performance of IoT networks in a complex urban environment. � 2019 Association for Computing Machinery.

Black swan Events or Low Probability High Impact Events (LoPHIEs), like wildfires, earthquakes and volcanic eruptions have significant and multifaceted implications in every economic sector of the area affected; among them, the hospitality and travel industry may be at the frontier of those affected in terms of span and impact. This paper outlines a vivid demonstration of the complexity of involved business processes and their interconnections through a case study. Appropriate preparations for hospitality and travel SMEs to such events have been identified and implemented through a purpose specific information system. To design this online platform, we followed a requirements analysis methodology. The main elements from the implementation of this platform have also been included, whereas elements of an initial usability evaluation have also been presented. � Springer Nature Switzerland AG 2020.

Fortunately, improvements in welfare and medical care will allow life expectancy in Europe�s population to increase by the year 2050. However, it is not always the case that living longer implies a healthier, more active and independent life. In this context, technologies and products that will act as assistive companions to elderly, who are living alone at their home, are attracting a growing interest from both a research and commercial perspective. Literature reports contradictory results on the preferences of elderly towards assistive technologies and more specifically, service robots. In this paper, we are called to present an empirical study, conducted in the scope of an EU � Horizon 2020 project, in order to explore people�s perceptions, attitudes and requirements towards the idea of a future service robot for the home. � Springer International Publishing Switzerland 2016.