This paper introduces a hybrid framework combining graphical ray-tracing with Edge-based Light Diffraction for rapid, city-scale radio signal propagation prediction. Grounded in Fraunhofer diffraction theory, the framework’s core novelty is a pre-computation pipeline that transforms building edges into secondary, directional emitters by encoding their complete first-order diffraction field into standard Illuminating Engineering Society photometric profiles. This receiver-independent formulation deliberately operates in the intensity domain—omitting phase-dependent effects—to enable the direct and rapid prediction of the local mean power (power envelope), a methodological choice optimized for macro-scale coverage assessment rather than for detailed, small-scale channel modeling. The resulting framework generates coverage maps in tens of seconds, with performance that remains stable at high resolutions where conventional receiver-dependent solvers become computationally prohibitive. Validation against an independent test dataset from urban drive-test measurements demonstrates a root-mean-square error of (7.27 ± 0.40) dB and a Pearson correlation of R = 0.80 ± 0.08. The proposed framework provides a physically interpretable and scalable pathway for leveraging graphical computing techniques for practical, non-line-of-sight radio network planning.

The innovation of 6th generation mobile networks through High Altitude Pseudo-Satellites (HAPS) introduces unique cyber-physical security challenges. As remotely operated aerial platforms, HAPS require a comprehensive approach to the overall system design to ensure safe and fault-tolerant operations. This article presents a systematic cyber-physical threat analysis of HAPS, identifying threats, system vulnerabilities, and corresponding mitigation strategies. To support broad applicability, we define a generic yet representative HAPS system architecture along with its expected operational conditions in the stratosphere. We adopt a STRIDE-based threat modeling methodology, leveraging prior research, to conduct a structured security assessment. A data flow diagram is developed to systematically identify threats using the STRIDE-per-element technique. System vulnerabilities are identified and possible mitigation measures are proposed, including robust network security design, integration of autonomous safety mechanisms to complement software-driven processes, and mitigation measures for vulnerable design points in electronics, construction and energy management subsystems. We further provide a qualitative risk assessment to support prioritization of these measures. These insights aim to serve as a baseline for HAPS developers to enhance the security and reliability of future HAPS systems.

Forklift-worker collisions often result in serious injuries. Although researchers have addressed this issue, a fully satisfactory solution remains elusive. This paper presents an analysis of technologies suitable for preventing forklift-human collisions. The analysis considers factors such as accuracy, range, computational cost, localization, and identification capabilities. Based on these criteria, a data fusion approach combining Bluetooth Low Energy (BLE) and 77 GHz radar technologies is investigated. This combination enhances identification using BLE technology and radar detection accuracy. By developing a data fusion application, we demonstrate that the proposed approach is an effective solution for mitigating forklift-worker collisions.

We propose a sensing system for the acquisition of technological data in the concept of the Industrial Internet of Things. One of the most demanding requirements of the Internet of Things, i.e., increased security risks of connecting devices to the Internet, is mitigated by designing a system that does not need to be connected to the cloud. All received data are stored on the SD card of the sensing system and in the client database after connecting to the sensing system web page, i.e., it operates in offline mode, and optionally on the client device when accessing the HTTP or HTTPS server of the sensing system in local area network or wide area network, respectively. We consider wire and wireless connection of sensors fulfilling the basic requirement for Low Power Wide Area Networks, i.e., low consumption, and user-friendly data visualization. By developing a prototype of the heated filter insert, we successfully demonstrate the proposed sensing system is an effective secure solution of technological data collection in the Industrial Internet of Things ecosystem.

The tremendous growth of Internet of Things (IoT) systems and the popularity of distributed systems, which were brought back into fashion by containerisation, create new challenges for system maintenance. Each IoT-specific service is characterised by a specific domain, or environment, making the maintenance of distributed IoT systems with dozens of agents a challenging task. This paper proposes a fractal-based mathematical model, called the fractal multi-agent IoT system (FMAIS), for scalable multi-agent systems (e.g. cloud-native services, wide-scale IoT services). A reliability estimation model called the multi-environment enhanced real-time customer-oriented reliability estimation (ME-ERT-CORE) model is proposed as a method for estimating the reliability of a multi-agent IoT system, where each agent can be specified by its own domain-specific environment (e.g. healthcare, logistics, smart factories, etc.). An estimation of the time complexity of the FMAIS is performed, and a model called ME-ERT-CORE for estimating its reliability is formulated. The results show that the FMAIS can be used for real-time simulations of system behaviour and ME-ERT-CORE can be used for the real-time estimation of its reliability, monitoring purposes, and, for instance, quality of service (QoS) descriptions based on service level agreement (SLA) requirements. The conducted measurements show that the reliability of the FMAIS with 4 layers and 96 applications, where each application deploys 96 instances, can be computed in 8.022 milliseconds. With the proposed optimisation method, the reliability for the same FMAIS can be computed in 0.219 milliseconds, which is 36 times faster than the ME-ERT-CORE reliability evaluation based on the definition. An FMAIS with the aforementioned parameters can be simulated in 84.300 milliseconds.

This article presents a novel approach for simulating indoor radio signal propagation through a heatmap-based strategy, harnessing advanced ray tracing (RT) and global illumination algorithms. Utilizing the desktop modeler SketchUp for 3-D environmental design and the V-Ray plugin for RT, this methodology leverages the spatial analysis of the light intensity. The process can be adjusted to various parameters of materials, including those that are intrinsically specular and transparent or are simulated as such, e.g., certain walls and windows. This generates a comprehensive heatmap of the predicted received signal strength indicator (RSSI) level of the radio signal. Unlike traditional empirical models, prone to inaccuracy with increasing complexity, and deterministic models, experiencing significant prediction time escalation with complexity, this approach provides a thorough view of signal propagation in complex architectural environments. It accounts for material properties that affect signal propagation, which are often overlooked by conventional models. Additionally, it exploits advanced graphics domain techniques, balancing accuracy and detail. The efficacy and accuracy of this approach are evaluated for Wi-Fi technology, and this approach is validated against established methods like the empirical multiwall model and the deterministic multiresolution frequency-domain ParFlow (MR-FDPF) method. A balance is achieved between precision, with a maximum deviation of 14.7% for RSSI = -100 dBm, and computational efficiency, with rendering times typically ranging from units to tens of seconds at specific resolutions from 2 to 5 cm/pixel. Root mean squared error (RMSE) values between 5 and 8 dB are deemed acceptable, showcasing the approach's robustness and practical applicability.

This paper deals with electrolytically manufactured copper foils prepared under different manufacturing conditions. The main goal is to evaluate mechanical and electrical properties concerning the further use of foils for flexible applications in the electronics industry. Four samples of copper foil were prepared using an electrolytic manufacturing process, with different compositions of the electrolyte ($\mathrm{Cu}^{2+} = 50g/1$, $\mathrm{H}_{2}\mathrm{SO}_{4}=70g/1$, $\mathrm{C}_{\mathrm{additives}}=0,5m1/1$, and $\mathrm{Cu}^{2+}=50g/1$, $\mathrm{H}_{2}\mathrm{SO}_{4}=70g/1$, $\mathrm{C}_{\mathrm{additives}}=1m1/1$) and different properties of cathodes (shiny stainless steel and roughened stainless steel, sanded with 1000 grit sandpaper). The current density was 1 $\mathrm{A/dm}^{2}$. The mechanical properties like elongation at break, modulus of elasticity in tension, tensile strength, and hardness were evaluated. The electrical conductivity of manufactured copper foils was also evaluated. The results show that the properties of copper foils were affected not only by changes in electrolyte composition (concentration of additives), but also by the roughness of cathodes (the higher roughness increased the effective surface of the cathode). The electrolytically prepared copper foils were compared with commercially available foil prepared by the metallurgical rolling process. The commercial sample exhibited similar electrical conductivity, lower hardness and higher modulus of elasticity in tension.

RFID systems are often used in industry to reduce costs, increase process efficiency and minimize human intervention. The challenge is to design an RFID system before it is implemented in a specific environment in the shortest possible time and at minimum cost while maintaining the accuracy of the results. In this paper, a new approach to predicting indoor UHF RFID signal coverage is presented. It is based on a graphical ray tracing method. Simulations are performed based on spatial analysis of the illumination of a 3D indoor environment created from a 2D floor plan. The results show a heat map representing the predicted RSSI radio signal levels using a color range. The approach is validated by comparison with the results of the empirical Multi-Wall model. The time complexity of the approach is presented. The proposed approach is able to generate a heat map with the accuracy of the empirical Multi-Wall model. The interior room equipment required to refine the results ought to be investigated in the future.

The negative influence of non-ionizing electromagnetic radiation on organisms, including humans, has been discussed widely in recent years. This paper deals with the methodology of examining possible harmful effects of mobile phone radiation, focusing on in vivo and in vitro laboratory methods of investigation and evaluation and their main problems and difficulties. Basic experimental parameters are summarized and discussed, and recent large studies are also mentioned. For the laboratory experiments, accurate setting and description of dosimetry are essential; therefore, we give recommendations for the technical parameters of the experiments, especially for a well-defined source of radiation by Software Defined Radio.

Rising demand for the integration of IoT services in cloud computing has brought cloud-native principles (e.g., system automation, loosely coupled services, etc.) to the edge of the network. A fundamental element of the cloud-native approach is a microservice — an instance, which is usually virtualised, serving for only a defined purpose. Virtualised microservices are mostly used in cloud-based IoT systems, which can be covered with multi-agent system (MAS) paradigm. The maintenance of a MAS requires a constant monitoring to track the system state and to satisfy the service level agreement (SLA) (or any other) requirements. This paper presents a resource efficient reliability model for MAS IoT systems for monitoring purposes. First, we provide a thorough mathematical analysis to describe the generic system model and its elements. This model takes into account SLA requirements and it is characterised with linear time complexity, simplicity of computations and input metrics (e.g., combination of SLA for CPU and its workload), where all of the input data are aligned to the same range. Then, we evaluate time complexity and provide a measurement to demonstrate the reliability of the model application. The results show that the proposed model is efficient for large number of the IoT agents. It is approximately 98 times faster in computation with 1,000 systems when compared with [D. Ursino, et al. , 2020] and 51 times faster in computations with 1,000 systems when compared with [J. Yao, et al. , 2019].

Health care facilities are subject to high demands on the optimization of the management of medicines and medicaments, resulting inter alia from the requirements of the Joint Accreditation Commission. These demands depend primarily on the quality of the personnel and the ability to prevent errors due to human factors. By meeting these requirements and adhering to them, healthcare facilities will achieve accreditation of the quality of care provided. The whole concept is based on utilization of Auto-ID and Internet of Things technology which brings new opportunities for healthcare sector. To ensure a high standard of care with U-Health concept, we developed e.g. new type of bed that respect the concept of Auto-ID and IoT. This type of bed is equipped with a newly developed intelligent mattress with integrated sensor of surface loading, which enables timely preventive warning when the change of the position is needed.

This paper deals with the issue of mobile device localization in the environment of buildings, which is suitable for use in healthcare or crisis management. The developed localization system is based on wireless Local Area Network (LAN) infrastructure (commonly referred to as Wi-Fi), evaluating signal strength from different access points, using the fingerprinting method for localization. The most serious problems consist in multipath signal propagation and the different sensitivities (calibration) of Wi-Fi adapters installed in different mobile devices. To solve these issues, an algorithm based on fuzzy logic is proposed to optimize the localization performance. The localization system consists of five elements, which are mobile applications for Android OS, a fuzzy derivation model, and a web surveillance environment for displaying the localization results. All of these elements use a database and shared storage on a virtualized server running Ubuntu. The developed system is implemented in Java for Android-based mobile devices and successfully tested. The average accuracy is satisfactory for determining the position of a client device on the level of rooms.

The smart textiles seem to be a very interesting possibility in many industrial fields e.g. medicine, automotive, textile industry etc. These types of textile are mainly based on metalized threads. It is necessary to know the physical characteristics of smart textiles before their use for a specific application. This article deals with the preparation and characterization of three types of textiles – copper-coated non-woven polyamide fabric and copper and nickel coated woven polyester fabric. Characterization was based on the measurement of textiles properties like the thickness of metallization, electrical resistance. The measurements of thickness metallization were done at micro-section by electron microscopy. The electrical resistance was evaluated for further usage of these fabrics as a heating system in smart textiles, where a low resistance of the heating part is desirable. The sheet resistance was measured in different directions to obtain information about the isotropic or anisotropic character of samples. The highest electrical resistance had woven copper-coated polyamide fabrics. The anisotropic character of samples was more obvious for woven polyester fabrics.

The paper introduces a method and system for real-time positioning of mobile terminals in indoor areas. The system uses wireless LAN infrastructure (usually Wi-Fi) and evaluates signal strength from different access points. The system meets requirements and has been implemented in Java for Android-based mobile devices and successfully tested at the Centre for Assistive Technologies (CAT) at the Czech Technical University in Prague, Faculty of Electrical Engineering. The results demonstrate an average accuracy of approximately 2.5 m, which is satisfactory for determining the position of a client device at room-level (e.g. in hospitals for checking whether a patient or staff member is currently in an expected place or for deciding where they can be assigned). Its potential applications are in healthcare, disaster management, supervision of people with disabilities, etc., but also in monitoring staff and goods in closed areas.

This paper proposes a novel technique for radio frequency transmission sources (RFTS) localization in outdoor environments using a formation of autonomous Micro Aerial Vehicles (MAVs) equipped with a rotating directional antenna. The technique uses a fusion of received signal strength indication (RSSI) and angle of arrival (AoA) data gained from dependencies of RSSI on angle measured by each directional antenna. An Unscented Kalman Filter (UKF) based approach is used for sensor data fusion and for estimation of RFTS positions during each localization step. The proposed method has been verified in simulations using noisy and inaccurate measurements and in several successful real-world outdoor deployments.

The goal of this paper is to propose a testing procedure for selected intrusion prevention systems (IPS) in a realistic network traffic in terms of their suitability on a given hardware microcomputers for low-performance devices for internet of things (IoT). We perform an IPS research in terms of resource usage in order to establish a universal procedure of checking, whether a given microcomputer controlling IoT devices (often in overloaded state) can additionally burden the installation and start-up of IPS. The experiment is repeated on several boards under overload condition to determine the maximum data rate, above which transmission degrades. The presented testing method is an exemplary tool for IoT applications concerning the security of embedded devices with low performance.

In this paper, electromagnetic shielding effectiveness of woven fabrics with high electrical conductivity is investigated. Electromagnetic interference-shielding woven-textile composite materials were developed from a highly electrically conductive blend of polyester and the coated yarns of Au on a polyamide base. A complete analytical model of the electromagnetic shielding effectiveness of the materials with apertures is derived in detail, including foil, material with one aperture, and material with multiple apertures (fabrics). The derived analytical model is compared for fabrics with measurement of real samples. The key finding of the research is that the presented analytical model expands the shielding theory and is valid for woven fabrics manufactured from mixed and coated yarns with a value of electrical conductivity equal to and/or higher than σ = 244 S/m and an excellent electromagnetic shielding effectiveness value of 25–50 dB at 0.03–1.5 GHz, which makes it a promising candidate for application in electromagnetic interference (EMI) shielding.

We propose a multi-channel access to improve Quality of Work Life in health care services and Quality of Service in the Internet of Things with suitably chosen infrastructure. The DEMO of the proposed solution of multi-channel communication system is realized for the hospital cleaning staff. The Quality of Work Life is improved by exactly described procedures of work plan and the Quality of Service is improved by redundant transmission channels and technologies, following the scenario and service strategy.

The penetration testing method of provided security protection by IDS/IPS (Intrusion Detection System / Intrusion Prevention System) tool Suricata in the low-performance embedded IoT device is presented. Penetration testing tools are presented with emphasis on software tools, such as NMAP and Metasploit. The used testing method is described in deep. IDS/IPS tool Suricata is implemented in embedded platform Raspberry Pi 3. Main contribution is the implemented testing method for Suricata IPS that can be used in other applications of security rules of embedded IoT devices.