When considering the concept of distributed intelligent control, three types of components can be defined: (i) fuzzy sensors which provide a representation of measurements as fuzzy subsets, (ii) fuzzy actuators which can operate in the real world based on the fuzzy subsets they receive, and, (iii) the fuzzy components of the inference. As a result, these elements generate new fuzzy subsets from the fuzzy elements that were previously used. The purpose of this article is to define the elements of an interoperable technology Fuzzy Applied Cell Control-soft computing language for the development of fuzzy components with distributed intelligence implemented on the DSP target. The cells in the network are configured using the operations of symbolic fusion, symbolic inference and fuzzy–real symbolic transformation, which are based on the concepts of fuzzy meaning and fuzzy description. The two applications presented in the article, Agent-based modeling and fuzzy logic for simulating pedestrian crowds in panic decision-making situations and Fuzzy controller for mobile robot, are both timely. The increasing occurrence of panic moments during mass events prompted the investigation of the impact of panic on crowd dynamics and the simulation of pedestrian flows in panic situations. Based on the research presented in the article, we propose a Fuzzy controller-based system for determining pedestrian flows and calculating the shortest evacuation distance in panic situations. Fuzzy logic, one of the representation techniques in artificial intelligence, is a well-known method in soft computing that allows the treatment of strong constraints caused by the inaccuracy of the data obtained from the robot’s sensors. Based on this motivation, the second application proposed in the article creates an intelligent control technique based on Fuzzy Logic Control (FLC), a feature of intelligent control systems that can be used as an alternative to traditional control techniques for mobile robots. This method allows you to simulate the experience of a human expert. The benefits of using a network of fuzzy components are not limited to those provided distributed systems. Fuzzy cells are simple to configure while also providing high-level functions such as mergers and decision-making processes.

Wi-Fi fingerprinting positioning systems have been deployed for a long time in location-based services for indoor environments. Combining mobile crowdsensing and Wi-Fi fingerprinting systems could reduce the high cost of collecting the necessary data, enabling the deployment of the resulting system for outdoor positioning in areas with dense Wi-Fi coverage. In this paper, we present the results attained in the design and evaluation of an urban fingerprinting positioning system based on crowdsensed Wi-Fi measurements. We first assess the quality of the collected measurements, highlighting the influence of received signal strength on data collection. We then evaluate the proposed system by comparing the influence of the crowdsensed fingerprints on the overall positioning accuracy for different scenarios. This evaluation helps gain valuable insight into the design and deployment of urban Wi-Fi positioning systems while also allowing the proposed system to match GPS-like accuracy in similar conditions.

Positioning systems based on location fingerprinting have become an area of intense research, mainly with the aim of providing indoor localization. Many challenges arise when trying to deploy location fingerprinting to an outdoor environment. The main problem is achieving coverage of large outdoor spaces, which costs time and needs an intensive data gathering effort. This paper proposes the use of mobile crowdsourcing in order to build a fingerprint database consisting of Wi-Fi networks received signal strength. The primary objective of this paper is to prove the feasibility of outdoor positioning using Wi-Fi crowdsourced data by showing that Wi-Fi networks are ubiquitous in urban areas. We then examine the gathered data and report our findings on challenges in building and maintaining a large-scale crowdsourced fingerprint database, the influence of fading on crowdsourced measurements. As Wi-Fi access-points are shown to exhibit mobility, we also propose and analyze methods for detecting and classification of mobile and static access-points.

- This paper presents an in-depth description of a multi-modal security solution based on a blockchain architecture developed within the CHRISS (Critical infrastructure High accuracy and Robustness increase Integrated Synchronization Solutions) project. Specifically, the focus in the paper is on the description of the proposed security architecture, functionalities and security measures based on modern blockchain solutions developed for the CHRISS project. The CHRISS project proposes an innovative solution that comes to increase the robustness of synchronization signal distribution mechanisms in telecommunications networks. The proposed solution allows a superior monitoring of the operation of synchronization signal distribution equipment in telecommunications networks, equipment generically called TSU (Time Synchronization Unit). These equipment generically contain a GNSS (Global Navigation Satellite Systems) signal reception system from which the time reference is extracted through a complex procedure and a complex mechanism for transmitting these signals on SFP (Small Form-factor Pluggable) optical ports using the specific PTP (Precision Time Protocol) protocols. Robust and detailed monitoring of the operation of TSU equipment in the context of the existence of a hostile operating environment that implies the possibility of jamming or interference attacks, spoofing or dedicated cyber-attacks is vital. Affecting the operation of this equipment entails disruption to the operation of an entire telecommunications network. This is possible because these systems contribute directly to the network-wide distribution of the synchronization signal. By leveraging the inherent characteristics of blockchain solutions, such as immutability, decentralization, and cryptographic security, the proposed security architecture increases the resilience and security of time distribution services, thereby mitigating the associated risks. This paper describes the relationship between blockchain-based security architecture and the specific manner of monitoring and protecting TSU equipment.

Algorithms for noise reduction that use the translation invariant wavelet transform indirectly are spatially selective filtering algorithms in the wavelet domain. These algorithms use the undecimated wavelet transform to accurately determine the coefficients corresponding to the contours in the images, these being processed differently from the other wavelet coefficients. The use of the undecimated wavelet transform in image noise reduction applications leads not only to an improvement in terms of Mean Square Error (MSE), but also in terms of the content quality of the processed images. In the case of noise reduction procedures by truncation of wavelet coefficients, artifacts appear, especially in the approximation of singularities, due to some pseudo-Gibbs phenomena. These artifacts, which appear locally, are troublesome in the case of object recognition applications from images acquired in conditions of nonuniform illumination and low contrast. In this work we propose a method of feature extractor based on undecimated wavelet transform (UWT) and local binary pattern (LBP). The results obtained on images acquired from drones in adverse conditions show promising results in terms of accuracy. The authors show that the displacement-invariant wavelet transform is an very good method of compression and noise reduction in signals.