Deutsche Telekom (Slovakia)

Object recognition tasks are commonplace in industrial and medical applications, but resource-limited end devices common to the Internet of Things (IoT) are limited in capabilities and commonly require offloading of compute-intensive tasks. We evaluate the negative latency concept as a new approach to image detection and object recognition applications in low-bandwidth scenarios without a feedback channel. We employ image quality assessment and risk estimators associated with image quality degradation for progressively transmitted images to realize negative latency. Our comprehensive evaluation on image recognition and object detection tasks shows that image quality assessment over progressively transmitted images can be enabled by using risk estimators associated with image quality degradation during progressive transmission. In turn, our approach provides the framework for service latency and resource use reductions.

Physical-layer network codes for consensus-testing (CT) via a relay are proposed, where each of two parties knows a message and can find out if all messages are equal, e.g. as an integrity check in a decentralized storage system or the control of mobile autonomous robots. By assumption, the encoders cannot randomize. The proposed codes achieve the CT capacity for channels with a memoryless uplink multiple-access channel that is a binary adder channel or a pair of q-ary symmetric or erasure channels. There, the capacity of noiseless uplinks can always be achieved, by using generalized deterministic identification (ID) codes for the uplink, testing consensus at the relay, and broadcasting the one-bit result using zero rate. For pairs of Gaussian channels and Gaussian adder channels, the capacity bounds equal those known for ID over certain noiseless uplinks, where the code sizes scale superexponentially in the block length. Using a recent derandomization result for decoders, it is shown that for general channels, the ID capacity of certain noiseless uplinks upper-bounds the CT capacity. In contrast, both for transmission coding for the uplink and additive linear network codes, the asymptotically achievable code sizes and necessary block lengths are shown to be suboptimal.

The present article analyses combustible fractions in mixed municipal waste and packaging and the calculation of energy value. Methods of thermal treatment of waste and methods of preparation ofalternative fuels and classifications are presented and described. The article describes the method of analysis of caloric values with which we determined the energy values of individual fractions. For theresearch, we also used two thermal analyses, with which we considered individual fractions, thermogravimetric analysis, and differential dynamic calorimetry. The article presents the results of boththermal analyses, with which we observe the responses of individual types of plastics at different temperatures and the change in physical and chemical properties. The problem we have analysed in this article is mainly recyclable plastic that can no longer be reused due to various factors. The results of the structural analysis of household waste collection are also presented and described; on the basis of the analysis, the energy value of the container of mixed municipal waste and the reasonableness of waste reuse are recalculated.

The demonstrator described in this work shows wireless multi-path communication to enable Ultra Reliable Low Latency Communication (URLLC) for mobile industrial applications in demanding scenarios, that implement closed-loop control systems in a cloud-native manner. We show mobile vehicles that are coordinated precisely through an intersection, controlled by a central entity located in an edge cloud. In order to ensure seamless operation, the connection to the controller needs to be ultra-reliable and with low latency, otherwise the mobile vehicles may crash. To enable this we use a WiFi network as well as a Non Public Network (NPN) of the 5th Generation of cellular mobile communications (5G) network in parallel to increase robustness against delays and losses on each individual link. The audience can experience the benefits of multi-path communication by interacting with the demonstration.

Seamless global connectivity in 6G requires a 3-dimensional network (or 3D network) that unifies terrestrial and non-terrestrial networks (NTN), which encompasses aerial and satellite networks to provide connectivities for a mass number of devices in industrial IoT. Even though computing resources in 3D networks can be used for computation offloading, scheduling communication and computing resources in such a highly dynamic and resource-constrained environment is challenging. This paper addresses the challenge by identifying research questions regarding resource allocation, considering handover dynamics and energy efficiency. Subsequently, we highlight the current status of our studies towards an intelligent scheduling strategy in softwarized 3D networks.

Communication technologies play an important role in people’s lives. They help us stay connected to others. However, there is a community of deaf and hard-of-hearing people who cannot perceive information normally like other human beings, nor can they express their thoughts clearly, and therefore cannot participate in normal conversations or group interactions. In this article, we introduce mobile assistive technology, which we created to help the community of hearing impaired people alleviate their daily communication barriers so that they can better integrate into society. The main requirement was to create a reliable mobile application running in the cloud for the transcription of incoming speech in the Slovak language in real-time.

Accurate orientation estimation is crucial in many application areas, including unmanned ground and aerial navigation for industrial automation and human motion tracking for human-robot interaction. State-of-the-art techniques leverage Inertial Measurement Units (IMU) due to their small size, low energy footprint, and ever-increasing accuracy, which provide Magnetic, Angular Rate, and Gravity (MARG) sensor measurements. Available attitude determination techniques rely on advanced signal processing algorithms to compensate for the gyroscope integration drift. The comparison of different algorithms depends solely on the collected ground-truth data set, which is difficult to replicate. This paper introduces a lightweight software framework to generate synthetic IMU sensor data. We generate the ground-truth orientation of the sensor body frame and apply an inverse navigation process to obtain corresponding synthetic sensor data. Additionally, we compare two well-known orientation estimation algorithms applied to the synthetically generated data from our framework. Evaluation results demonstrate that the proposed software framework represents a fast and easy-to-use solution to the problem of evaluation of different orientation estimation algorithms while providing access to ground truth measurements.

In vehicles, noise and seat vibrations can be perceived by the driver, depending on their signal properties, as annoying or unpleasant. Because perception is a complex process, it is necessary to consider both types of stimuli at the same time to assess annoyance in such situations. A perception experiment was carried out to investigate the interaction between simultaneous noise and seat vibrations, as well as the influence of seat vibration frequency in vehicle situations. For the experiment, acoustic and optical stimuli such as seat vibrations were recorded in a mini excavator and a refuse collection vehicle from the view of the driver. The recordings were prepared for plausible reproduction in a laboratory experiment. The participants of the experiment were presented with two different vehicle scenes with simultaneous noise, seat vibrations and visuals. The average total levels of vibration and noise, as well as the vibration frequency ranges of the various vehicle scenes, were varied. The results suggest that an interaction effect between noise and vibration should be accounted for when assessing total annoyance in such situations. Models for the prediction of the relative total annoyance causes of variations in noise and vibration levels were developed.

The increasingly difficult challenges in managing big data are inciting for revolutionary and fundamental techniques, as well as for technologies that can handle the complexity and the never-before-seen volume of data. Our goal is to enable high-density industrial networks to transmit and store production-related information efficiently and confidentially while retaining any existing network infrastructure. As the deployment of sensors leads to both the benefits and the challenges of industrial big data, our Bitteiler solution represents a means to reduce the data volume at the early stages of the data cycle to curb its impact on communications and storage systems. Bitteiler is a plug-and-play solution that allows customers to leverage smart IoT solutions to the fullest to achieve an industry 4.0-ready production process that is both efficient and secure. Our practical demonstration provides a hands-on experience with the Bitteiler technology – including in-network compression and coding – using a number of live IoT devices that can be manipulated by the audience.

Recently private 5G networks so called 5G campus networks have gained a lot of public attention. Typically, such networks are associated to be implemented in huge production companies to control assembly lines. However, we present a demonstrator for the deployment of a private 5G network in a SME. Our demonstrator was designed in cooperation with a local bakery to relocate dough pieces in the middle of the night. This is an example of a monotones task, which alikes can be found in even the smallest companies. Such tasks can be better solved by robots, providing human workers more time for varied and creative tasks. We also point out some options how SMEs can get 5G campus networks at reasonable costs.