—We present a data augmentation technique for generating location variant audio samples using ray-traced audio in virtual recreations of the real world. Hardware Audio-Based Location-Aware Systems are capable of locating audio sources in relation to mobile devices. This is a relevant technique in the context of location-based and person tracking in ubiquitous environments. However, this solution is limited in collecting vast data to train the machine learning model reliably. To overcome this problem, we constructed a virtual environment using the audio ray-tracing solution, NVidia VRWorks Audio in Unreal Engine 4, to simulate a real-world setting. The environmental sounds in the real-world scenario were imported into the virtual environment. This strategy could augment data for training Hardware Audio-Based Location-Aware Systems machine learning models with the necessary calibration of the unreal and real data sets. Our results show the audio ray-tracing framework could simulate real-world sound in the virtual environment to a certain extent.
Recent progress in Sensorics and Internet of Things (IoT) enables real-time data analytics based on data from multiple sensors covering the target industrial production system and its manufacturing processes. Diagnostics and prognosis can be implemented using the neural network approach on top of vibration and other sensed data. Neural network methods lead to high accuracy in fault detection and fault evolution. Nevertheless, transferring a neural network model to edge devices leads to performance issues and platform limitations. In this paper, we discuss the edge computing opportunities for diagnostics of industrial rotary machinery using well-known neural network methods. Keywords–Fault diagnosis; convolutional neural network; edge computing; vibration diagnostics.
In the age of digitalization, passwords play a significant role to protect user information. The growing number of data breaches has become a major problem allowing unauthorised parties to access confidential data. Over the years, passwords have been the first factor of authentication that is used in various segments, such as web applications, banking, e-commerce, and applications for authentication, etc. In most cases, the passwords are usually assigned to or created by the authorized user, and must be kept secret to keep unauthorized users from having access to information it is meant to protect. However, recent attacks have shown that these passwords are vulnerable to attacks such as, the dictionary, brute force, man in the middle, traffic interception, social engineering, and key logger attack, etc. In this paper, we discuss different types of passwords that prevent unauthorised access to protect users’ information. We analyze various attack techniques that are leveraged in many ways to obtain passwords. We also discuss the available protection techniques that aim to protect passwords. However, our analysis reveals that the protection techniques are not sturdy and fail to provide enough protection against the most utilised attack techniques, hence, requiring to have more advanced techniques in place. Keywords–graphical password; cryptographic key; password authentication; graphical authentication; biometric.
The blockchain is a decentralised technology distributing digital information through peer-to-peer, where the consensus protocol remains the most significant part ensuring the integrity of the recorded information. The consensus works as an agreement among the network nodes determining the authenticity of the network peers and also puts forward a set of rules. Nodes that do not comply with the consensus rules, fail to take part in the network activities. However, the major consensus protocols comprise severe weaknesses allowing malicious parties to conduct activities that are against the network rules. Although blockchain is based upon a sturdy structure solving many security issues, the robustness of it is still severely affected by various attack techniques. Most of the attacks were possible due to the weaknesses in the adopted consensus protocol. Many security proposals evolved to defend against the vulnerability but fully failed to minimise the attacking possibilities encouraging attackers even more to conduct such exploitation. In this research, we analyse 19 important consensus protocols that are adopted by major cryptocurrencies. We also discuss the most dreadful consensusbased attacks and major defense mechanisms. Our analysis shows that the weaknesses in the consensus protocol result in significant attacks. Keywords–Blockchain; Consensus; Cyber Attack.
Mobile cyber-physical systems consist of possibly moving heterogeneous execution units, which interact with their environment through sensors and actuators. Programming such systems without taking motion into account has already proven to be error-prone and complex, as challenges like communication or programming multiple different devices have to be considered by the developer. Corresponding programming models abstract from these challenges through the provision of transparencies. This allows the programmer to focus on describing the behavior of the system instead of managing its infrastructure. When mobility is taken into account, the devices tasks may depend on their positions in space. Therefore, location and motion awareness have to be supplied. This impedes the provision of distribution transparency, as the programmer has to consider the movement and positioning of certain objects. In contrast to supporting awareness, providing motion and location transparency allows to maintain distribution transparency. In exchange, this limits the developers ability to consider the positioning and movement of the devices. Therefore, a programming model, which bridges the gap between maintaining transparencies and providing awareness is required to enable the developer to focus on describing the behavior of the possibly mobile system as a whole. This paper aims to show that there is a need for research on such models. To achieve this goal, a systematic literature review is performed. Its main target is the assessment of existing programming models, regarding their provided types of awareness and transparency. To classify on which aspects of the system the considered programming models focus, an architectural model for mobile cyber-physical systems is introduced. Additionally, desired programming model properties are defined with respect to the presented architectural model. This allows to determine, in which way the considered approaches fail or succeed in handling the described challenges. Therefore, a conclusion on the need of programming models for mobile cyber-physical systems can be drawn. Keywords—cyber-physical systems; distribution; mobility; programming models; context awareness.
The Internet of Things is a result of decades of research in Ubiquitous Computing and Mobile Computing. It comes with many advantages for businesses, industry and consumers. Typical examples are a seamless integration of physical objects into digital workflows and improved modes of use for consumer products. However, if non-smart devices are replaced by smart ones, the integrated IT components might generate new risks that stem from different lifecycles of embedded software, libraries and protocols used, and the IT ecosystem needed. We strive for an exhaustive catalog of long-term risks for the operational life-span of smart devices. To this end, we describe an approach to identify risks which might materialize years after a smart device has been rolled out and purchased. Furthermore, we present the risks for a fragment of a smart device’s ecosystem we have identified so far.
—Internet of Things (IoT) is a key technological enabler to create smart environments and provide various benefits. In the context of a smart city, a huge number of IoT applications are being developed for emergency management operation and city traffic congestion management. These applications require fast system reaction to get the valuable data and make appropriate decisions. Therefore, it is essential to design and develop a service model that ensures an appropriate level of Quality of Service (QoS) for such applications. In this paper, we take advantage of Software-Defined Networking (SDN) technology integrated into the IoT system to propose a new QoS routing model for core transport SDN. In the model, the application QoS preferences and network elements status are directly considered in the resource allocation process aiming to satisfy the application expectation while maximizing network performance. We modeled a status-aware and Service-Level-Agreement-aware (SLA-aware) routing mechanism and implemented multi-path and load-balancing approaches in the model to enhance the network throughput and increase system availability.
Video data analytics has now become essentially oriented on edge-centric computing in Internet of Things (IoT). In this paper, we consider such video services that provide analytics to smart assistance in industrial IoT systems. We identify the opportunities of industrial video data analytics. We present an edge-centric architecture for constructing smart assistance services. Based on this architecture, we implemented several pilot services that demonstrate the opportunities of industrial video data analytics. The services are deployed and experimented in a real enterprise for monitoring industrial production equipment (technical state and its evolution, ongoing production processes, equipment operating conditions). Keywords–Video data analytics; Internet of Things; Smart Assistance Services; Edge-Centric Computing.
The article presents and discusses the problem of developing a robotic system for the care and supervision of people with disabilities. The main functions of the robotic system are telecommunications between patients and their guardians, automatic management of platform movement, manipulator movement and gripper. An overview of existing solutions (devices) on the robotics market that implement similar capabilities is presented. Each device is a complex and expensive system. In order for a robotic system to be widely accessible to all people, it is necessary to reduce the cost of its components. Inexpensive mechanical components have disadvantages in terms of movement accuracy. We propose a hypothesis about the possibility of using artificial intelligence to improve the accuracy of actions performed by a robotic system. Analysis of the video image of the manipulator movement can allow to adjust the speed and angle of rotation of the motors in the joints of the manipulator, thereby making the movements more accurate. Keywords–Robotics; Remote control; Manipulator; Alarm system; Smart capture.
This paper describes an indoor positioning technique using a video camera that captures LED light reflected by the floor. Indoor positioning for mobile devices can be very useful. In particular, localization techniques using LEDs and cameras, so-called visible light positioning, are known to be effective and have high accuracy. However, existing methods have the constraint that they must capture the light source directly. This requires a high-performance processor and a high-resolution image. However, light sources cannot always be detected directly (loss of signal: LOS). Our proposal aims to solve these problems by estimating the position of a camera that does not face the light directly but monitors light reflected by the floor. Specifically, individual LED ceiling lights emit sinusoidal waves modulated with different frequencies, and the camera captures the overlapped light from the LEDs reflected by the floor then demodulates the signal. The camera need not seek the ceiling lights directly from an image, unlike existing methods. The position can be estimated using any part of the image because usually the ceiling light is reflected by the whole floor. Experimental results show that the proposal requires less than 1/100 as many pixels for localization as existing methods and the position can be estimated within 0.4 m at the 90th percentile in a 2.5 m square room. We show that the cause of errors is mainly the difference between the LED diffusion model and the actual light diffusion, the occlusion and the noise and movement of the camera. Overcoming these problems remains as our future work.
—There have been many studies in recent years using the Textile planar Pressure Mapping (TPM) technology for computer-human interactions and ubiquitous activity recogni- tion. A TPM sensing system generates a time sequence of spatial pressure imagery. We propose a novel, comprehensive and unified feature set to evaluate TPM data from the space and time domain. The initial version of the TPM feature set presented in this paper includes 663 temporal features and 80 spatial features. We evaluated the feature set on 3 datasets from past studies in the scopes of ambient, smart object and wearable sensing. The TPM feature set has shown superior recognition accuracy compared with the ad-hoc algorithms from the corresponding studies. Furthermore, we have demonstrated the general approach to further reduce and optimise the feature calculation process for specific applications with neighbourhood component analysis.
—The progressing digitalization of factories coincides with a growing amount of raw data being available in order to create valuable, data driven application. The Edge Comput- ing paradigm is one of the key enablers to realize beneficial solutions, since it helps overcome obstacles such as capacity and latency restrictions or data privacy and protection requirements. However, realized industrial applications of Edge Computing Applications are rather limited as of today. Therefore, as part of the Factory Automation Edge Computing Operating System Reference Implementation (FAR-EDGE) project, a series of expert interviews covering viewpoints from both industry and academia was conducted in order to gain deeper insight on limiting factors and development challenges and expectations. The results are presented in this paper forming a brief snapshot of the current perception of Edge Computing contributing to the creation of an overall understanding of the needs of the manufacturing industry.
An approximate analytical model to analyse the performance of the handover process in cellular networks is proposed, where new and handover calls that arrive when insufficient free resources are available are queued instead of being lost. The approximation is based on the aggregation of states of the double infinite continuous-time Markov chain that models the system, and exhibits an excellent accuracy and low computational cost. The approximate model might be of interest to the next-generation of 5G mobile networks that must be engineered to achieve high QoS and extremely low latencies.
This study was financed in part by the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior— Brasil (CAPES)—Finance Code 001. Supported by project PLATAFORMA DE VEHICULOS DE TRANSPORTE DE MATERIALES Y SEGUIMIENTO AUTONOMO — TARGET. 463AC03. Project co-financed with Junta Castilla y Leon, Consejeria de Educacion and FEDER funds. This work was partially funded by FCT- Fundacao para a Ciencia e a Tecnologia through national funds and when applicable cofunded by FEDER – PT2020 partnership agreement under the project UID/EEA/50008/2019 and by Operacaoao Centro- 01-0145-FEDER-000019 – C4 – Centro de Competencias em Cloud Computing, co-financed by the Programa Operacional Regional do Centro (CENTRO 2020), through the Sistema de Apoio a Investigacao Cientifica e Tecnologica – Programas Integrados de ICDT. Including a cooperation with the project international cooperation project Control and History Management Based on the Privacy of Ubiquitous Environments— Brazil/Portugal.
