A significant number of IoT devices are being deployed in the wild, mostly in remote locations and in untrusted conditions. This could include monitoring an electronic perimeter fence or a critical infrastructure such as telecom and power grids. Such applications rely on the fidelity of data reported from the IoT devices, and hence it is imperative to identify the trustworthiness of the remote device

App repackaging refers to the practice of customizing an existing mobile app and redistributing it in the wild to fool the final user into installing the repackaged app instead of the original one. In this way, an attacker can embed malicious payload into a legitimate app for different aims, such as access to premium features, redirect revenue, or access to user’s private data. In the Android ecosystem

Surveillance videos in smart environments have become commodities nowadays, which enable many novel applications, including various video analytics that turn videos into semantic results. In addition to live feeds, surveillance videos may be saved in a storage server for on-demand user-defined queries in the future. Different from on-demand video streaming servers, whose design objective is to maximize

Cyber Physical Systems (CPS) totally revolutionized the way we interact with the world providing useful services that can support the human being in many aspects of his life. Artificial Intelligence (AI) is another important player for bringing intelligence to CPS and allows the realization of Intelligent Cyber Physical Systems where smart applications can run. However, the constrained hardware of

Smartphone-based contact-tracing apps are a promising solution to help scale up the conventional contact-tracing process. However, low adoption rates have become a major issue that prevents these apps from achieving their full potential. In this paper, we present a national-scale survey experiment (N=1963) in the U.S. to investigate the effects of app design choices and individual differences on COVID-19

The outbreak of the COVID-19 pandemic has deeply influenced the lifestyle of the general public and the healthcare system of the society. As a promising approach to address the emerging challenges caused by the epidemic of infectious diseases like COVID-19, Internet of Medical Things (IoMT) deployed in hospitals, clinics, and healthcare centers can save the diagnosis time and improve the efficiency

WiFi time of flight (ToF) measurement has been supported recently by the wireless LAN protocols to improve WiFi localization. Specifically, the IEEE 802.11-2016 standard has a fine-time measurement (FTM) protocol that can be used to measure the WiFi signal round trip time (RTT). In this paper, we present the design and implementation of WiNar, a WiFi RTT-based indoor location determination system that

We present a System for Processing In-situ Bio-signal Data for Emotion Recog-nition and Sensing (SPIDERS+) – a low-cost, wireless, glasses-based platform for continuous in-situ monitoring of user’s facial expressions (apparent emotions) and real emotions. We present algorithms to provide four core functions to detect eye shape and eyebrow movements, pupillometry, zygomaticus muscle movements, and head

The demand for a ubiquitous and accurate indoor localization service is continuously growing. Cellular-based systems are a good candidate to provide such ubiquitous service due to their wide availability worldwide. One of the main barriers to the accuracy of such services is the large number of models of cell phones, which results in variations of the measured received signal strength (RSS), even at

Internet of Things(IoT) facilitates key technologies that rely on sensing, communication and processing in daily routines. As an IoT-enabled paradigm, mobile crowdsensing (MCS) can offer more possibilities for data collection to support various IoT applications and services. As an extension, MCS can be used for data gathering amid COVID-19 pandemic crisis. Bridging Artificial Intelligence and IoT can

Fine-grained, unobtrusive monitoring of gym exercises can help users track their own exercise routines and also provide corrective feedback. We propose W8-Scope, a system that uses a simple magnetic-cum-accelerometer sensor, mounted on the weight stack of gym exercise machines, to infer various attributes of gym exercise behavior. More specifically, using multiple machine learning models, W8-Scope

The integration between the Internet of Things (IoT) and fog computing can pave the way to a plethora of applications. Fog computing indeed allows IoT devices to offload complex tasks to computing resources, known as fog nodes, that are in their proximity (e.g., at the network edge). Fog proximity enables important advantages, first and foremost low latency. However, IoT device mobility endangers those

Edge computing is crucial for many of the new 5G business vertical use-cases, such as Industry 4.0 robots, safety-critical communications, and highly-efficient smart grids. However, the tighter integration of such impactful businesses into previously core network operations raises significant security, trustworthiness, and reliability issues. A business vertical must not compromise the Edge platform

The Internet of Things (IoT) has become a popular trend in the technology industry with the huge benefits it brings by enabling heterogeneous interconnected devices and systems. On the other hand, developments in the field also come with urgent requirements of security and privacy. Available authentication solutions are difficult to be applied into practice due to the resource constraints of IoT devices

In order to improve the quality of experience in executing computation-intensive tasks of real-time IoT applications in a fog-enabled IoT network, resource-constrained IoT devices can offload the tasks to resource-rich nearby fog nodes. It causes a reduction in energy consumption compared with local processing, although it extends task completion time due to communication latency. In this paper, we

With an ageing population, more and more older people are expected to remain in their living environment. Mobile robots, whose market is expected to increasingly grow, could assist them for specific tasks. Existing studies, however, show that potential users have privacy concerns. In this paper, we therefore aim at understanding factors influencing these concerns and exploring their preferences with

Sensing data collection and energy supplement are key issues of Wireless Rechargeable Sensor Network (WRSN). Using mobile vehicles to collect data and supplement energy can not only effectively reduce the node communication energy consumption, but also ensure the continuity of network operation. We propose an energy-minimization path construction algorithm based on dual-function vehicles for data collection

Momentary photography is enjoyed by many smartphone users, especially with the popularity of apps such as Snapchat and Instagram. Many traditional positive psychology interventions focus on lengthy writing tasks to express positive emotions experienced during past events, acts of kindness and gratuitous situations. In this work we developed SnapAppy, a smartphone application to integrate momentary

The daily and routine interactions of people with their smartphones in various situations make these devices valuable data sources to understand user behaviors. Passive users’ emotion recognition is one of the most essential user modeling areas and has been studied for various purposes so far. Psychological studies, on the other hand, show that the personality of users can influence their behavior

A large number of electric vehicles (EVs) operating in cities result in huge charging demands. For a charging station, it is important to balance between the charging cost and the future maintenance cost. In this paper, we present two bi-objective optimization models for optimizing charging cost and maintenance cost. From the perspective of maintenance cost, we consider to smooth the charging rate

Keystroke privacy is crucial for securing smartphone systems and user privacy. User’s private information may be leaked if the sequences of keystrokes on the numeric soft keyboard are obtained by an adversary in a certain way. Different keystrokes may lead to different finger movements, causing diverse interference to WiFi signals, which can be indicated by the fluctuation of Channel State Information

Managing the frequent congestion of the road networks of large cities is a major challenge for city management organizations. In order to deal with these phenomena, it is essential to have an in-depth understanding of the processes that lead to the occurrence of congestion and its spilling over into contiguous areas of the city. The professional literature has a long history of studying the propagation

Controller Area Network (CAN) is an in-vehicle communication protocol, which provides an efficient and reliable communication link between Electronic Control Units (ECUs) in real time. Recent studies have shown that attackers can take remote control of the targeted vehicle by exploiting the vulnerabilities of the CAN protocol. Motivated by this fact, we propose an Intrusion Detection System (IDS),

Wireless sensor networks (WSNs) and IoT are often deployed for long-term monitoring. However, the network lifetime of these applications is limited by non-rechargeable battery-powered. To vastly reduce energy consumption, this paper proposes a spatio-temporal approximate data collection (STAC) method to prolong the network lifetime. Under the tolerable accuracy, STAC utilizes spatial correlation among

In this work, the problem of localizing ground devices (GDs) is studied comparing the performance of four range-free (RF) localization algorithms that use a mobile anchor (MA). All the investigated algorithms are based on the so-called heard/not-heard (HnH) method, which allows the GDs to detect the MA at the border of their antenna communication radius. Despite the simplicity of this method, its efficacy

Mobile crowdsensing (MCS) paradigm enables users equipped with energy-constrained smart devices to participate in sensing and reporting of assigned tasks. To achieve seamless communication as well as effective energy and resource management, we leveraged the fog computing platform to propose a centralized, energy-efficient and robust data collection framework, called bioMCS, based on the topological

Organic Light-Emitting Diode (OLED) display panels have become increasingly popular in recent years due to their numerous advantages over traditional LCDs. The power consumption in OLED based displays highly depends on the displayed contents. This paper utilizes the image-dependent power-consuming quality of OLED displays to produce energy-efficient and contrast-enhanced images that consume less power

Computation offloading within Mobile Edge Computing (MEC) networks is a promising new technique, especially in the 5G era. This technique offers leading-edge services to the users of Smart Mobile Devices (SMDs) to reduce the processing time and battery drain. Thus, SMDs tend to offload their heavy processing tasks to preserve battery power and benefit from an important processing power. However, in

The study of self organized networks is considered a key element in developing the new generation of cellular networks. Mobile service providers are adopting new technologies such as small cells and precoding to deploy their networks according to 5G standards. As these type of technologies gain more importance and popularity, network self organization become a more essential function in operating the

The Internet of Things is envisioned to provide connectivity and communication between various devices all over the world. Based on the devices and applications involved, the nature of the network formed differs. Thus, an intelligent and holistic ecosystem needs to be created wherein clients, data sources, smart objects, and services can all co-exist and interact with each other. We present Adaptive

Pervasive applications are revolutionizing the perception that users have towards the environment. Indeed, pervasive applications perform resource-intensive computations over large amounts of stream sensor data collected from multiple sources. This allows applications to provide richer and deep insights into the natural characteristics that govern everything that surrounds us. A key limitation of these

Popularity and openness have made the Android platform a potential target of malware attacks. The hackers continuously evolve and improve attacking strategies to identify vulnerabilities in newer Android versions. Detection and analysis of malware attacks in Android platform pose unique challenges due to the security restrictions and resource limitations present in these devices. This paper proposes

Fog-Cloud computing empowered Internet of Things (IoT) technology has conceptualized the ideology of Industry 4.0. Inspired by this, the food industry 4.0 presents a unique concept for determining food quality in real-time. Conspicuously, the current research provides an IoT-based smart framework for evaluating the food-quality parameters in restaurants and food outlets. IoT technology is primarily

With the emergence of compute-intensive applications and rapid growth of mobile users and Internet of Things(IoT) devices, edge computing was proposed to provide cloud-like services in close proximity to meet the requirements of low-latency, security, and lower energy consumption. Ultra-dense network (UDN) is a promising technique to meet the requirements of explosive data traffic in 5G mobile communications

Nowadays, in Wireless Sensor Network (WSN), the ability to transfer data over the network via a better route seems to be the tactic aspect due to certain criteria like network lifetime, energy consumption, and so on. A lot of efforts has been taken so far on better routing in the network via the clustering technique. Since clustering is an effective and apt way of providing a better route that transmits

In Internet of Things (IoT), data are collected from various sources (e.g., sensors and databases) to describe a phenomenon under-observation. Due to the lack of knowledge about the measurement environment and the limited accuracy of data sources, the IoT data inevitably appears uncertain, imperfect, and conflicting. This would lead to high data conflict among different data sources, and the final

In Internet of things (IoT), one of the main concepts is wireless sensor networks where there are a large of resource-constrained sensor nodes. With the wide application of Internet of things (IoT), these resource-constrained sensor nodes have to suffer from more security threats. One of possible solutions is to establish a trustworthy IoT environment where the interactions are based on the trustworthiness

Delivering the right content at the right time is one of the main challenges in designing smart information delivery systems. Predicting the user’s preferences in the future and caching the required content in advance to improve the quality of service has been proposed and investigated before for different applications. In this paper, we explicitly consider a scenario with very high bandwidth and speed

In this paper we examine the contextual factors driving users’ decisions to change smartphone ringer modes, and in particular switching between a full (normal) mode where all notification modalities are enabled, and a discreet ringer mode (i.e. where audio is disabled). We add to the limited current literature through a qualitative study based on the theory of Reasoned Action Approach, and the longitudinal

Various performance benefits such as low latency and high bandwidth have turned fog computing into a well-accepted extension of the cloud computing paradigm. Many fog computing systems have been proposed so far, consisting of distributed compute nodes which are often organized hierarchically in layers. To achieve low latency, these systems commonly rely on the assumption that the nodes of adjacent

Edge computing relies on devices at the edge of the network to best meet the application’s needs, such as low communication latency and data caching. However, unbalanced networks and resource heterogeneity are challenging factors when optimizing data transfers and applications’ performances in the edge. In this paper, we explore these two concerns through a comprehensive set of benchmarks and illustrate

Nowadays, positioning technologies have become widely available providing then large datasets of individuals’ mobility data. Actually, annotating raw traces with contextual information brings semantics to them and then provides a better understanding of people behavior. To do so, literature work explored novel techniques to enrich raw mobility data with contextual information using either geographic

In this work, we propose a new Blockchain-based Identity Management system for smart industry. First, we describe an efficient biometric-based anonymous credential scheme, which supports selective disclosure, suspension/thaw and revocation of credentials/entities. Our system provides non-transferability through a freshly computed hidden biometric attribute, which is generated using a secure fuzzy extractor

Cities have limited resources that must be used efficiently to maintain their smooth operation. To facilitate efficient resource allocation and management in cities, in this paper, we study one such important problem: how long does it take to resolve non-emergency 311 service requests? We present SWIFT, a Non-emergency Response prediction system based on a recently developed structured regression model

The Internet of Things (IoT) brings opportunities to create new services and change how services are sold and consumed. The IoT is overpopulated by a large number of networks, millions of objects and a huge number of services and interactions. Despite this, the nature of IoT networks, such as the heterogeneity of resources, the dynamic topology, and the large number of similar services, makes service

The widespread diffusion of connected smart devices has greatly contributed to the rapid expansion and evolution of the Internet at its edge, where personal mobile devices follow the behavior of their human users and interact with other smart objects located in the surroundings. In such a scenario, the user context is represented by a large variety of information that can rapidly change, and the ability

Location-Based Games (LBGs) rely on the player’s location to change its game state. Developing worldwide LBGs is a challenging task due to the need to deploy game instances in multiple locations, while maintaining the same game balancing, features, and even correlations between locations of the game and the real world. Hence, it is virtually impossible to manually design interactions, challenges, and

This paper focuses on building a spatio-temporal AI inference engine for estimating hard disk reliability. Most electronic systems such as hard disks routinely collect such reliability parameters in the field to monitor the health of the system. Changes in parameters as a function of time are monitored and any observed changes are compared with the known failure signatures. If the trajectory of the

Ambient intelligence pursues the integration of intelligent approaches on an IoT infrastructure, mainly using everyday objects of the environment. The main hypothesis of the work is that the way in which a user interacts with a door handle is suitable to be used in the identification task. Our proposal contributes with a new method to identify persons in a seamless and unobstrusive way, suitable to

Real-time Collaborative Editors (RCEs) are popular distributed applications that permit large and dynamic groups of collaborators to share and update large multimedia documents across many sites in real time. However, the state-of-the-art models are either locally centralized or globally distributed using a central cloud server to keep shared data synchronized. Multi-access Edge Computing (MEC) is

Pedestrian road-safety applications require geolocation data at high refresh rate. This is achieved through high rate beaconing of the data from the safety devices owned by road users to servers. The servers perform threat analysis and send alerts to road users in case of risk of collisions. However, when low-battery devices like smartphones are used for such applications, they drain their energy rapidly

Recent advancements in wireless technologies enable pervasive and device free gesture recognition that enable assisted living utilizing off the shelf commercial Wi-Fi devices. This paper proposes a Device-Free Wi-Fi-based Sign Language Recognition (DF-WiSLR) for recognizing 30 static and 19 dynamic sign gestures. The raw Channel State Information (CSI) acquired from the Wi-Fi device for 49 sign gestures

Blockchain in IoT applications obviates the need for dependence on a single trusted authority, enhancing the potential for scalability and reliability. Existing consensus methods used in blockchain require high energy consumption, massive computational power with trusted authorities, or proof for mining a block. Resource constrained IoT devices need a lightweight and low latency consensus mechanism

In this study, a priority-aware lightweight secure sensing model for body area networks with clinical healthcare applications in internet of things is proposed. In this model, patients’ data is labeled according to the proposed prioritizing mechanism. This provides a prioritized and delay-less service in the server side for the patients with critical conditions. In the proposed model, the sensed data

As smartphones are increasingly an integral part of daily life, recent literature suggests a deeper relationship between personality traits and smartphone usage. However, this relationship depends on many complex factors such as geographic location, demographics, or cultural influence, just to name a few. These factors provide crucial knowledge for e.g. usage support, recommendations, marketing, general

Fog computing in 5G networks has played a significant role in increasing the number of users in a given network. However, Internet-of-Things (IoT) has driven system designers towards designing heterogeneous networks to support diverse task demands (e.g. heterogeneous tasks with different priority values) under interference constraints in the presence of limited communication and computational resources

Multi-access Edge Computing (MEC) recognized as an emerging technology that provides cloud computing services in the proximity of Radio Access Network (RAN). Mobile subscribers could offload their computation-intensive or memory-intensive tasks to the nearest Base Stations (BS) and deliver the cloud services from MEC servers. This technology can meet the requirements of low latency and location awareness

Achieving advanced Mobile Edge Computing (MEC) services such as dynamic resource assignment and slicing, maintaining Quality of Service (QoS), and enabling heterogeneous virtual functions are some of the technical challenges associated with edge-cloud enhanced 5G architectures now under consideration. This paper proposes a named-object based virtual network (NOVN) architecture to support low-latency

Automatic human activity detection, mainly transport-wise, is very relevant for architects and urban planners (among many others) when designing cities, roads, public transportation systems, etc. Such detection allows to better plan our cities and has been made possible with the widespread use of smartphones carrying several different sensors. We developed edgeTrans, a system based on a smartphone