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Introduction
Publications
Publications (583)
The increasingly large availability of sensors in modern houses, due to the establishment of home assistants , allow to think in terms of smart houses where behaviours can be automatized based on user habits. Common tasks required to this aim include activity prediction, i.e., the task of forecasting what is the next activity a human is going to pe...
Intrusion Detection Systems (IDS) based on deep learning models can identify and mitigate cyberattacks in IoT applications in a resilient and systematic manner. These models, which support the IDS’s decision, could be vulnerable to a cyberattack known as adversarial attack. In this type of attack, attackers create adversarial samples by introducing...
The advent of the digital economy and Industry 4.0 enables financial organizations to adapt their processes and mitigate the risks and losses associated with the fraud. Machine learning algorithms facilitate effective predictive models for fraud detection for Industry 4.0. This study aims to identify an efficient and stable model for fraud detectio...
The development of activity recognition based on multi-modal data makes it possible to reduce human intervention in the process of monitoring. This paper proposes an efficient and cost-effective multi-modal sensing framework for activity monitoring, it can automatically identify human activities based on multi-modal data, and provide help to patien...
This paper firstly introduces common wearable sensors, smart wearable devices and the key application areas. Since multi-sensor is defined by the presence of more than one model or channel, e.g. visual, audio, environmental and physiological signals. Hence, the fusion methods of multi-modality and multi-location sensors are proposed. Despite it has...
Glaucoma causes blindness in long-time untreated cases. So, its early diagnosis is very important. Moving from that, there have been lots of Deep Learning oriented studies to diagnose Glaucoma from color fundus images. However, it is important to know about how humans can trust to black-box level Deep Learning models in their decision makings. In t...
Motion capture technology has been widely used in the sport analysis to improve their performance and reduce the injury risk. Kayak, a popular outdoor sport, employs coordination of multiple muscles and skeletons especially those of upper limbs that must be investigated carefully. The fine time phase segmentation of rowing cycle plays an important...
For simplifying and speeding up the development of the Internet of Things (IoT) ecosystem, there has been a proliferation of IoT platforms, built up according to different design principles, computing paradigms, technologies, and targets. This paper proposes a review of main examples populating the wide landscape of IoT platforms and their comparis...
The papers in this special section focus on advanced networking technologies used to combat the outbreak of epidemic diseases. Currently, COVID-19 is a major global public health challenge. Worse, this epidemic could last for 2 years, according to US experts. To address it, scientific research institutions attempt to actively leveraged networking t...
Computing has emerged from traditional computers to pervasive scenarios where smart wearable and mobile devices are essential to provide human-centric uninterrupted services anywhere and at any time. Wearable computing systems, along with their enabling technology known as Body Sensor Network, represent a ground-breaking innovation with extremely d...
INTER-IoT presents a novel layer-oriented solution for interoperability, to provide interoperability at any layer and across layers among different IoT systems and platforms. Contrary to a more general global approach, the INTER-IoT layered approach has a higher potential in order to provide interoperability. It facilitates a tight bidirectional in...
The Internet of Things (IoT) is a jeopardized ecosystem in which heterogeneity is intrinsic at all levels, from physical devices to communication protocols till high-level application semantics. The absence of IoT standards increases the complexity of integration and interoperability among heterogeneous platforms. This generates a strong demand for...
Cascade failures are one of the key issues restricting the widespread application of the Internet of Things (IoT). Under different routing modes, the cascade failure process of the IoT is also different. In this work, in order to reasonably characterize the cascade process of the IoT, we developed a directional load metric: the IoT-oriented router...
Among the various reasons behind vehicle accidents, drivers' aggressiveness and distractions play a significant role. Deep learning (DL) algorithms inside a car mobile edge (CME) have been used for driver monitoring and to perform automated decision-making processes. Training and retraining the DL models in resource-constrained CME devices come wit...
Cyber-physical systems (CPS) are increasingly commonplace, with applications in energy, health, transportation, and many other sectors. One of the major requirements in CPS is that the interaction between cyber-world and man-made physical world (exchanging and sharing of data and information with other physical objects and systems) must be safe, es...
In the Cloud of Things, data are stored and processed in the cloud and the results are sent to IoT Smart Objects (SOs) with, generally, a network latency overhead due to the distances between the cloud and the local IoT networks. Moreover, trusting inappropriate counterparts can expose SOs to threats and to mitigate them we propose a clustering rep...
Activity Prediction is foreseeing the following activity people are going to execute. This is a crucial task in smart home environments, i.e., in order to facilitate the daily routines of elderly people with or without special needs. In this paper, we focused on Activity Daily Living prediction and we proposed a novel activity prediction technique...
With the continuous attempts to develop effective machine learning methods, information fusion approaches play an important role in integrating data from multiple sources and improving these methods' performance. Among the different fusion techniques, decision-level fusion has unique advantages to fuse the decisions of various classifiers and getti...
The limited battery capacity of sensor nodes is one of the challenges for achieving sustainable precision agriculture in 5G. When the sensor nodes run out of energy, the data center will not be able to grasp the information of the environment, and the corresponding decisions and actions will not be performed. To solve this problem, this study prese...
A multi-level framework that combines a simulation and optimization approach is proposed to evaluate the performance of complex systems triggered by real-time IoT-fed “service requests”. The idea behind the conceptual framework is centered on the use of simulation to mimic system organization, rules and behavior, whereas optimization is used to sea...
Establishing a scale-free topology is widely regarded as one of the effective methods that can significantly improve the fault tolerance performance of wireless sensor networks (WSNs). However, the scale-free topology is very vulnerable to malicious attacks in which the nodes with high importance are attacked first, and its energy efficiency is als...
Traffic congestion is increasing in over populated urban areas, our traditional traffic management system can no longer solve this problem. However, this problem can be solved by converting our road networks into queueing networks. This paper proposes, the use of an open Jackson Queueing Model which can be equated with our existing road network to...
Cyber-physical-social systems (CPSS) as an emerging computing paradigm are revolutionizing the relationship between humans, devices and physical environments and will be expected to have a fundamental impact and influence in our daily lives. In a typical CPSS scenario, plenty of nodes (or devices) often adopt wireless distributed contention protoco...
Aspect-based sentiment analysis (ABSA) can help consumers provide clear and objective sentiment recommendations through massive quantities of data and is conducive to overcoming ambiguous human weaknesses in subjective judgments. However, the robustness and accuracy of existing sentiment analysis methods must still be improved. We first propose a d...
Emergence of communication technologies made the automotive industries across the globe to embrace Advanced Driver Assistance Systems (ADAS) by considerable investments to ensure accident-free travel, reduction of pollution, fuel conservation. ADAS achieves its goals by integrating complex subsystems such as obstacle avoidance, overtaking advice, l...
Prostate cancer is one of the most common forms of cancer in men in many countries. The survival rate can be significantly enhanced with early detection of the cancer so that appropriate intervention can be administered. In this work, a novel automated classification algorithm by fusing a number of deep learning approaches has been proposed to dete...
With the widespread application of artificial intelligence and the Internet of Things, the intellectualization of the IIoT (Industrial Internet of Things, IIoT) has received more and more attention. There is quite much demand from machine learning services in such scenarios. Therefore, it is urgent to find an adaptive solution for the machine learn...
The conventional diagnostic process and tools of cardiovascular autonomic neuropathy (CAN) can easily identify the two main categories of the condition: severe/definite CAN and normal/healthy without CAN. Conventional techniques encounter significant challenges when identifying CAN in its early or atypical stages due to the inherent imbalanced and...
As wireless networks play an increasingly key role in everyday life, it is necessary to secure them from radio frequency attacks, such as jamming, which are hard to detect, especially because they may be easily mistaken for other network conditions. Within this challenging context, the paper proposes a framework for jamming detection in drone netwo...
Critical infrastructures across many industries such as smart water treatment and distribution networks (SWTDN) and power generation and public transport networks depend on the supervisory control and data acquisition (SCADA) system. However, being the core component of the critical infrastructures has made the SCADA-based SWTDN system an attractiv...
To suppress the spread of COVID-19, accurate diagnosis at an early stage is crucial, chest screening with radiography imaging plays an important role in addition to the real-time reverse transcriptase polymerase chain reaction (RT-PCR) swab test. Due to the limited data, existing models suffer from incapable feature extraction and poor network conv...
Electricity theft is one of the major issues in developing countries which is affecting their economy badly. Especially with the introduction of emerging technologies, this issue became more complicated. Though many new energy theft detection (ETD) techniques have been proposed by utilising different data mining (DM) techniques, state & network (S&...
Non-orthogonal multiple access (NOMA) with a grant-free access has received a lot of attention due to its support to massive machine-type communication (mMTC) devices. The devices in grant-free systems are allowed to transmit information without undergoing an authentication process. Therefore, in such systems base station needs to distinguish betwe...
Renal failure is a fatal disease raising global concerns. Previous risk models for renal failure mostly rely on the diagnosis of chronic kidney disease, which lacks obvious clinical symptoms and thus is mostly undiagnosed, causing significant omission of high-risk patients. In this paper, we proposed a framework to predict the risk of renal failure...
The Internet of Things (IoT) enables the interconnection of new cyber–physical devices that generate significant traffic of distributed, heterogeneous, and dynamic data at the network edge. Since several IoT applications demand for short response times (e.g., industrial applications, emergency management, real-time systems, and healthcare systems)...
Object recognition from live video streams comes with numerous challenges such as the variation in illumination conditions and poses. Convolutional neural networks (CNNs) have been widely used to perform intelligent visual object recognition. Yet, CNNs still suffer from severe accuracy degradation, particularly on illumination-variant datasets. To...
Fall prevalence is high among elderly people, which is challenging due to the severe consequences of falling. This is why rapid assistance is a critical task. Ambient assisted living (AAL) uses recent technologies such as 5G networks and the internet of medical things (IoMT) to address this research area. Edge computing can reduce the cost of cloud...
Fall prevalence is high among elderly people, which is challenging due to the severe consequences of falling. This is why rapid assistance is a critical task. Ambient assisted living (AAL) uses recent technologies such as 5G networks and the internet of medical things (IoMT) to address this research area. Edge computing can reduce the cost of cloud...
Object recognition from live video streams comes with numerous challenges such as the variation in illumination conditions and poses. Convolutional neural networks (CNNs) have been widely used to perform intelligent visual object recognition. Yet, CNNs still suffer from severe accuracy degradation, particularly on illumination-variant datasets. To...
With the increasing number of vehicles, the traffic congestion is becoming more and more serious. In order to alleviate such a problem, this article considers transmission and inference delay of cloud centralized computing in the software defined Internet of Vehicles (SDIoV), and builds a new SDIoV architecture based on edge intelligence, for suppo...
Machine Learning (ML) techniques are becoming an invaluable support for network intrusion detection, especially in revealing anomalous flows, which often hide cyber-threats. Typically, ML algorithms are exploited to classify/recognize data traffic on the basis of statistical features such as inter-arrival times, packets length distribution, mean nu...
Depression is the result of a complex interaction of social, psychological and physiological elements. It is now considered to be a major threat to people's physical health, and even as a threat to their lives. Research into the brain disorders of patients suffering from depression can help doctors to understand the pathogenesis of depression and f...
Machine Learning (ML) techniques are becoming an invaluable support for network intrusion detection, especially in revealing anomalous flows, which often hide cyber-threats. Typically, ML algorithms are exploited to classify/recognize data traffic on the basis of statistical features such as inter-arrival times, packets length distribution, mean nu...
With the ever-increasing diffusion of smart devices and Internet of Things (IoT) applications, a completely new set of challenges have been added to the Data Mining domain. Edge Mining and Cloud Mining refer to Data Mining tasks aimed at IoT scenarios and performed according to, respectively, Cloud or Edge computing principles. Given the orthogonal...
The recent revival of artificial intelligence (AI) is revolutionizing almost every branch of science and technology. Given the ubiquitous smart mobile terminals and Internet of Things (IoT) devices, it is expected that a majority of intelligent applications will be deployed at the edge networks. Therefore, providing intelligent and sustainable edge...
Nowadays, drones are not just deployed for defense and military establishments, but they are widely used in many applications such as natural disaster monitoring, soil and crop analysis, road and traffic surveillance, and consumer product delivery. Some information, such as drone identification and flight modes, can be transmitted to other drones....
With the explosive growth of multimedia contents in vehicular networks and the development of 5G technology come great challenges to the Internet of Vehicles system. By utilizing the storage capability of roadside units, popular contents can be cached in advance during nonpeak periods, which can bring better quality of experience to users. However,...
Human activity plays a significant role in various fields, such as manufacturing, healthcare, and public safety; therefore, recognizing human activity is crucial to enable smart innovative services. The development of ubiquitous sensing and pervasive computing allows studying what humans perform in real time and mobility. Single- and multi-user act...
Eye movement detection has attracted increasing attention in the fields of safety driving, eye motion tracking, psychological assessment and telemedicine. Soft multi-functional electronic skin (SMFES) is designed to collect electrooculogram (EOG), skin temperature and sweat signals simultaneously for eye movement detection. Serpentine structure is...
In a massive IoT systems, large amount of data are collected and stored in clouds, edge devices, and terminals, but the data are mostly isolated. For many new demands of various intelligent applications, self-organized collaborative learning on those data to achieve group decisions has been a new trend. However, in order to reach the goal of group...
In this paper, we explore the remote monitoring of patients in an on-demand service that can be implemented using the Internet of Medical Things (IoMT). Network congestion and delay are important issues that must be resolved to handle emergencies in IoMT. Backpressure scheduling is a well-known scheme to resolve network congestion and improve netwo...
Scheduling of small cells in Fifth-Generation (5G) mobile network is highly important for achieving energy-efficiency and providing Quality of Service (QoS) to the applications users. Minimization of energy consumption hampers QoS. This problem has been further complicated due to exponential increase of mobile application users demanding high data...
The purpose of the International Conference on Computer-Human Interaction Research and Applications (CHIRA) is to bring together professionals, academics and students who are interested in the advancement of research and practical applications of interaction design & human-computer interaction. Five parallel tracks will be held, covering different...
Hippotherapy is a new rehabilitation therapy for children with cerebral palsy (CP). Although it has been proved to be effective in clinical research, a quantitative evaluation of such results is still lacking in previous studies. In this research, one method for evaluating the effectiveness of hippotherapy based on body sensor network (BSN) is prop...
In the foreseeable future, the rapid growth of devices in the Internet of Things will make it difficult for 5G networks to ensure sufficient network resources. 6G technology has attracted increasing attention, bringing new design concepts to the dynamic real-time resource allocation. The resource requirements of devices are usually variable, so dyn...
Soft electronics have been widely applied to wearable electronics, hand gesture detection and human robot interaction (HRI). Soft wrist-worn sensor system (SWSS) with electromyography (EMG), strain/pressure sensing abilities has been created for continuous hand gesture recognition, which includes multi-source data sensing, data collection and proce...
This book discusses the design and implementation of, as well as experimentation on, an open cross-layer framework and associated methodology to provide voluntary interoperability among heterogeneous Internet of Things (IoT) platforms. It allows readers to effectively and efficiently develop smart IoT applications for various heterogeneous IoT plat...
The Internet of Things (IoT) is the latest example of the System of Systems (SoS), demanding for both innovative and evolutionary approaches to tame its multifaceted aspects. Over the years, different IoT methodologies, frameworks, platforms, and tools have been proposed by industry and academia, but the jumbled abundance of such development produc...
The term Body Sensor Network (BSN) was introduced less than twenty years ago. Since then, tremendous technical development and social changes attracted researchers from very diverse fields allowing to establish an incredibly rich interdisciplinary ecosystem. Although many former challenges have been tackled by consolidated literature, still today n...
In the context of new retail and personalized, small-batch, distributed collaborative production, orders arrive in real-time, and each workshop needs to organize production lines based on sub-orders in real-time under the constraints of smart contracts. However, the existing cloud centralized scheduling method has too high calculation and communica...
Mobile Device Cloud (MDC) has become a promising and lucrative cloud environment that exploits nearby mobile devices' idle resources to improve compute-intensive applications. Computing code at nearby mobile devices rather than a distant master cloud helps improve real-time applications' performance. However, it is non-trivial to motivate the worke...
Leveraging cloud infrastructure to the mobile edge computing helps the mobile users to get real time multimedia services in Fifth Generation (5G) network system. To ensure higher Quality-of-Experience (QoE), faster migration of mobile multimedia service instances is required to cope up with user mobility. By deploying the mobile multimedia service...
The “Internet of Things” (IoT) provide humans and smart objects with attractive services, based on the advanced features of the IoT devices, like high sensing, real-time acting and reasoning.
In our previous research we have highlighted that these features can be improved by promoting cooperation between smart objects, and we introduced the associa...
Motion phase plays an important role in the spatial–temporal parameters of human motion analysis. Multi-sensor fusion technology based on inertial sensors frees the monitoring of the human body phase from space constraints and improves the flexibility of the system. However, human phase segmentation methods usually rely on the determination of the...
The adoption of IoT for smart health applications is a relevant tool for distributed and intelligent automatic diagnostic systems. This work proposes the development of an integrated solution to monitor maternal and fetal signals for high risk pregnancies based on IoT sensors, feature extraction based on data analytics and an intelligent diagnostic...
Collaborative Robotics is one of the high-interest research topics in the area of academia and industry. It has been progressively utilized in numerous applications, particularly in intelligent surveillance systems. It allows the deployment of smart cameras or optical sensors with computer vision techniques, which may serve in several object detect...
Anomaly detection is concerned with identifying data patterns that deviate remarkably from the expected behaviour. This is an important research problem, due to its broad set of application domains, from data analysis to e-health, cybersecurity, predictive maintenance, fault prevention, and industrial automation. Herein, we review state-of-the-art...
In the past, most strategies were mainly designed to focus on stocks or futures as the trading target. However, due to the enormous number of companies in the market, it is not easy to select a set of stocks or futures for investment. By investigating each company’s financial situation and the trend of the overall financial market, people can inves...
In this paper, we propose a pen device capable of detecting specific features from dynamic handwriting tests for aiding on automatic Parkinson’s disease identification. The method used in this work uses machine learning to compare the raw signals from different sensors in the device coupled to a pen and extract relevant information such as tremors...
The papers in this special section focuses on artificial intelligent-driven informatics, sensing, imaging and big data analytics in dealing with the COVID-19 pandemic.
In the emerging wearable world, a plethora of smart devices are being designed to facilitate our daily life. More activities, such as student learning, desk office work, or driving are requiring human beings to spend a significant portion of their daily life sitting on a chair. As a result, there is increasing interest in the development of technol...
The Internet of Things (IoT) refers to a network of connected devices that collects and exchanges data through the Internet. These things can be artificial or natural and interact as autonomous agents that form a complex system. In turn, business process management (BPM) was established to analyze, discover, design, implement, execute, monitor, and...
The problem of maximizing lifetime of a sensor network is still challenging mainly due to the stringent delay-deadline of real-time applications and heterogeneity of sensor devices. The problem is further complicated when the network contains many obstacles. In maximizing network lifetime, existing literature works either merely address issues of a...
IoT devices dealing with complex tasks usually require powerful hardware capabilities or, as a possible alternative, to get on the Cloud those resources they need. When an IoT device is “virtualized” on the Cloud, it can take benefit from relying on one or more software agents and their social skills to mutually interact and cooperate. In particula...
New technologies are transforming medicine, and this revolution starts with data. Health data, clinical images, genome sequences, data on prescribed therapies and results obtained, data that each of us has helped to create. Although the first uses of artificial intelligence (AI) in medicine date back to the 1980s, it is only with the beginning of t...
Currently, the number of traffic accidents has been increased globally. One of the main reasons for this increase is the distraction of the driver on the road. Distracted driving can cause collisions and cause injury, death, or property damage. New techniques can help to mitigate this problem, and one of the recent approaches is to employ body wear...
Projects
Projects (12)
The Internet of Everything (IoE) model presents at its core the promise to aggregate the "four pillars" of people, data, processes and things, in order to extend and improve the processes already present in classical models and, in turn, to enrich the lives of people. One of the most intriguing challenges in IoE is the paradigm "connections among things" shifting to "connections among people, process, data and things". At the same time, in a similar manner, the concept of Industry 5.0 makes its way in the nowadays industrial ecosystem. A peculiar necessity in Industry 5.0 is to increase productivity while not removing human workers from the manufacturing processes. This can be tackled by defining and evaluating hybrid ecosystems in which smart machines are intertwined with humans as collaborators rather than competitors.
HIEMI 2022 aims at bringing together scientific and industrial communities on discussing, proposing, defining and evaluating innovative and hybrid models for IoE in Industry 5.0 ecosystems. Considering the novelty of the context, the workshop also aims at defining a collaborative research agenda to highlight future research directions.
The workshop focuses on a rapidly advancing context that is attracting a considerable attention both from academic and industrial communities. For instance, according to Semantic Scholar, since 2020 more than 1,700 scientific contributes have been published regarding IoE and relating concepts, such as 6G networks, healthcare systems and edge- and fog-based architectures. Larger mentions are present for Industry 5.0, with more than 250,000 contributes mentioning it. Instantiating a novel workshop on such contexts encourages researchers and practitioners to share new ideas and developments, in order to tackle well known challenges and to pose new ones.
