Architectures, Protocols and Algorithms of Sensor Networks-Second Edition.

Half of the world’s population resides in cities and this percentage is going to rise in the coming years. This rapid transformation of the economy and society is making traditional city management redundant. Intensive urbanization has brought with it some challenges. Scanty resources, population growth, increased carbon footprint, reduced air quality, congestion on roads, depriving health status, and falling food quality, all are prominent parts of cities. Does this bring a question in mind is accelerated growth sustainable? The answer and solution to this is an adaption of the Smart City Concept. A smart city integrates all the available technology with the requirements of city development and builds infrastructure which can improve the quality of life of citizens. Smart cities are designed in a manner to use minimum resources with maximum efficiency in all areas of urban life. It provides smart solutions using smart technologies. Urban needs and technological advancements meet in smart cities. It manages cities more quickly and effectively by using AI, IT technologies, and robotic process automation. Intelligent transportation, intelligent energy, intelligent governance, intelligent security, intelligent healthcare are all central to the idea of smart cities. The emphasis of this essay is on smart transit as a component of smart cities. The movement of people and goods across several geographical boundaries has been significantly aided by the transportation sector. Globally, the majority of smart cities face logistical and transportation issues. Both the fast growing human population and the increase in the number of cars on the road are to blame for this. In order to design and run a sustainable transportation system, technology may be of great assistance. Robotic systems for real-time vehicle data collection, traffic management, and using mobility on demand in trip planning through a single user interface have emerged as cities struggle with traffic congestion. The transportation industry, which faces difficulties including traffic congestion, unanticipated delays, and routing issues that cause businesses to lose money, has successfully used robotic process automation. Robotic process automation provides reliable results and affordable solutions while reducing uncertainty in the decision-making process. It is very helpful in designing and running a successful transit system. Robotic Process Automation (RPA) systems for obtaining real-time data from vehicles, buses, and trucks for traffic management and using mobility on demand in trip planning through a single user interface have emerged as cities struggle with poor management and congestion. By examining different uses of robotic process automation, it is possible to evaluate precise prediction and detection models that are intended to forecast traffic volume, an appropriate route, traffic conditions, accurate information about timing, incidents, and which time and roadway for transport are suitable for running and mobility. The application of RPA in smart cities could be seen in Intelligent Transportation Systems’ Traffic Management, Public Transportation, Safety Management, Manufacturing, and Logistics. The research focuses on areas of concern for smart cities in the sphere of the transportation sector and related difficulties that may be solved via robotic process automation. The article emphasizes the challenges and solutions for making smart transportation more effective by using Intelligent Robotic Transportation Systems.

Aim. Threats of a non-physical nature have a significant effect on the security of intelligent transportation systems (ITS). They may have the form of unlawful interference in the development and implementation of ITS. The creation of a trusted framework for the development and implementation of ITS is examined as in the case of intelligent water transportation systems (IWTS). Problems. By decree of the President of the Russian Federation, ITS, telecommunications and security of information processing are among the priority areas of scientific and technological development. ITS technologies, as well as those involved in the creation of trusted, secure system and application software are among the most important critical high technologies. The operation of ITS involves wide use of computerised systems that implement the latest information and telecommunication technologies, automated and automatic control technologies, artificial intelligence that can pose security threats. ITS are to be developed and operated in a trusted environment. Methods. The paper used the methodology for ensuring the security of IWTS, development of secure hardware and software platforms for secure automated systems, methods of system analysis, dependability theory, information protection, and law. Results. The paper defines the problem of creating a trusted framework for the development and implementation of IWTS, the applicable terminology is developed. The author examined the effect of IWTS on the security of critical information infrastructure (CII) and national security, developed a model of relationships between the IWTS security domains taking into account threats of physical and non-physical origin. Examples of computer incidents within IWTS that caused consequences at the national and international levels are given. The composition of the IWTS facilities attributed to CII is defined, critical processes implemented by standard CII facilities as part of the IWTS are set forth. The author lists conceptual problems of IWTS security, defines the principles of creating a trusted framework for the development and implementation of IWTS. Conclusion. Ensuring the security of IWTS against modern threats requires solving a number of problems associated with the creation of a trusted framework for the development and implementation of IWTS. For the purpose of improving the timeliness and quality of their solution, the paper proposes an intuitive terminology that reflects the subject area and helps finding a common understanding of the security domain by experts from various industries. IWTS facilities have an effect on CII security and national security in general. That is taken into account in the model of relationships between IWTS security domains, demonstrated using cases of computer incidents within IWTS that caused consequences at the national and international level. Given the above, the paper lists IWTS facilities attributed to CII and sets forth examples of critical processes implemented by standard CII facilities as part of the IWTS. The defined list of conceptual IWTS security problems take into account the growing landscape of IWTS security threats that includes insecure software, hardware and software platforms, software and hardware systems and emerging technologies. When developing the principles for the creation of a trusted IWTS development and implementation framework, the author took into account the best practice of implementing the methodology for creating national secure hardware and software platforms of CII facilities that enables the creation of secure automated systems for various applications that are based on domestically-developed solutions. The examined matters are of a systemic nature, which allows using the findings in the development and implementation of ITS in other modes of transportation.

The rapid evolution of advanced robotic systems has significantly enhanced the capabilities of both aerial and ground robots, driving innovations in automation, mobility. The performance of the proposed platform was rigorously evaluated through a multi-faceted analysis. The feasibility of its advanced capabilities is directly enabled by recent breakthroughs in artificial intelligence AI for optimization, advanced composite materials for airframes, and hardware accelerated computing for real time processing. Key point in mechanical considerations include lightweight structural design, dynamic stability, and efficient actuation mechanisms, while electrical design focuses on power distribution, energy efficiency, and real time embedded control. The platform's perception is driven by a tightly coupled multi sensor fusion architecture, creating a robust and precise state estimation critical for autonomous operation in GPS denied environments. Through analytical modeling and experimental validation, this research evaluates design trade-offs and proposes optimization strategies to enhance durability, agility, and operational efficiency. The findings provide valuable insights for the development of next generation robotic systems, with applications in industrial automation, search and rescue, and precision agriculture

Flexible multimode sensors have become key components in intelligent sensing due to their flexibility, multifunctionality, and adaptability, with broad applications in wearables, healthcare, and robotics. This review summarizes recent advances in their structural design, sensing mechanisms, and signal processing strategies, and highlights applications in industrial automation, smart agriculture, and wearable systems. Compared to previous reviews, this work uniquely classifies multimode sensors into three structural types—homogeneous, heterogeneous, and array‐based—and comprehensively compares their design principles and use cases. To address multimodal signal coupling, three decoupling strategies—material‐, structure‐, and algorithm‐driven—providing a holistic perspective rarely integrated in earlier literature is highlighted. Representative case studies demonstrate practical value, while current challenges such as signal crosstalk and manufacturing complexity are outlined. Finally, future directions including biomimetic materials, edge computing, and green manufacturing are proposed to guide further development.

This paper presents a framework to model and analyze the survivability and vulnerability of intelligent transportation system (ITS) networks. The proposed framework includes qualitative and quantitative approaches and can be implemented during the planning and design phase of new ITS projects or assess the survivability and vulnerability of existing ITS networks. The qualitative approach is based on Survivable System Analysis (SSA). It identifies threat mitigation strategies for each threat identified and provides suggestions for improved security and survivability. The paper also presents a quantitative survivable system analysis approach that is aimed to compute the essentiality of ITS network components and rank-order these essentialities to determine the most essential components of the network. The proposed framework provides a significant addition to the current design practices by integration system security, vulnerability, and survivability into the design, operation, and management of ITS networks. While the case-study presented in the paper focused on ITS networks, the proposed framework can be applied to any other critical infrastructure distribution, control, and monitoring networks.

Intelligent sensors with embedded AI are key to modern cyber-physical systems. They find applications in industrial automation, medical diagnostics and healthcare, smart cities, and autonomous systems. Despite their significant potential, they face several hardware challenges related to computing power, energy consumption, communication capabilities, and security, which limit their effectiveness. This article analyzes factors influencing the production and deployment of AI sensors. The key limitations are energy efficiency, computing power, scalability, and integration of AI sensors in real-time conditions. Among the main problems are the high requirements for data processing, the limitations of traditional microprocessors, and the balance between performance and energy consumption. To meet these challenges, the article presents several practical and innovative approaches, including the development of specialized microprocessors and optimized architectures for “edge computing,” which promise radical reductions in latency and power consumption. Through a synthesis of current research and practical examples, the article emphasizes the need for intermediate hardware–software solutions and standardization for mass deployment of AI sensors.

This study proposes a distributed formation control framework for multi-agent systems by integrating deep reinforcement learning (DRL) with interdisciplinary methodologies from control theory, robotics, and artificial intelligence. Aimed at addressing collaborative formation challenges in dynamic environments, the approach uses graph-theoretic modeling for formation-keeping and obstacle avoidance and dynamic Attention-based Advantage Actor-Critic (DA-A2C) algorithm to solve collaborative formation problems in dynamic environments like autonomous drone swarms and robotic fleets. To balance formation consistency and obstacle repulsion, this strategy optimizes neighbor perception dynamic weight allocation using the dynamic Ω-zone mechanism. Experimental validations in simulated environments with static/moving obstacles show superior performance over SA2C, MATD3, and DDPG baselines, covering formation control and obstacle avoidance in complex situations and outperforming other algorithms in adaptability and robustness. This research can improve cross-domain applications in intelligent transportation, industrial automation, and emergency response systems. The method works in multi-robot formation systems, and future study will focus on 3D environment generalization and efficient communication protocols.

Recently, the demand of Wireless Sensor Network (WSN) increased rapidly due to the vast applications in environmental monitoring, health care, Smart cities, Industrial automation, agriculture and Transports, etc. However, limited battery backup in sensor nodes affects the lifetime of the WSN. In this paper, a novel multi objective optimization problem is formulated to maximize the life time by considering the distance distribution of sensor nodes with their Cluster Heads (CHs) and distribution of CH’s life time. The recent multi objective algorithms like Decomposition based Multi Objective Evolutionary (MOEAD), Multi Objective Grasshopper Algorithm (MOGOA), Multi Objective Particle Swarm Optimization (MOPSO), Multi Objective Grey Wolf optimization (MGWO) algorithm and Improved Multi Objective Differential Evolution (IMODE) algorithms are considered for the designing the multi-objective WSN and their performances are compared based on the scalability, lifetime, energy distribution and cluster distribution of sensor nodes. The simulation results demonstrated that MOEAD based WSN achieves 24.2% more life time than second best algorithms. Further, it achieves 97% (in average) accuracy in cluster quality. Moreover, MOEAD outperformed than other algorithms in Pareto optimal solution in terms of convergence, diversity and solution quality.

Intelligent robotic systems increasingly operate in complex, data-rich environments where real-time decision-making and human interpretability are critical. While robots generate vast volumes of sensory and operational data, the lack of effective visualization mechanisms often limits system transparency, debugging, and collaborative interaction. This research presents an enhanced framework that integrates advanced data visualization techniques with intelligent robotic systems to improve situational awareness, system interpretability, and operational efficiency. The proposed framework combines multi-modal data acquisition, intelligent data processing, adaptive visualization layers, and feedback-driven robotic control. By enabling real-time visual analytics of robotic perception, cognition, and action, the framework supports both autonomous decision-making and human-in-the-loop supervision. Experimental evaluation across simulated and real-world robotic scenarios demonstrates improved task performance, reduced error rates, and enhanced user understanding, highlighting the framework’s potential for applications in industrial automation, healthcare robotics, and smart environments.

Smart mobility and transportation, in general, are significant elements of smart cities, which account for more than 25% of the total energy consumption related to smart cities. Smart transportation has seven essential sections: leisure, private, public, business, freight, product distribution, and special transport. From the management point of view, transportation can be classified as passive or non-cooperating, semi-active or simple cooperating, active or cooperating, contract-based, and priority transportation. This approach can be applied to public transport and even to passengers of public transport. The transportation system can be widely observed, analyzed, and managed using an extensive distribution network of sensors and actuators integrated into an Internet of Things (IoT) system. The paper briefly discusses the benefits that the IoT can offer for smart city transportation management. It deals with the use of a hierarchical approach to total transportation management, namely, defines the concept, methodology, and required sub-model developments, which describes the total system optimization problems; gives the possible system and methodology of the total transportation management; and demonstrates the required sub-model developments by examples of car-following models, formation motion, obstacle avoidances, and the total management system implementation. It also introduces a preliminary evaluation of the proposed concept relative to the existing systems.

Plug and Play (PnP) technology has demonstrated superior efficacy in modern computing systems by enabling automatic device detection and configuration without manual intervention. Building upon this principle, this research proposes LitePnP, a lightweight Plug-and-Play model specifically designed for resource-constrained IoT devices, which typically lack comprehensive operating systems and are limited in memory capacity, processing power, and storage capabilities. The model focuses on three primary components: (1) a sensor identification mechanism based on active and passive scanning through RS485/Modbus RTU protocols; (2) lightweight JSON-based drivers that enable sensor operation abstraction while reducing memory overhead; and (3) a minimalist PnP process that faciliates seamless driver installation and service deployment. The significant contribution of this research lies not only in proposing the lightweight PnP model but also in comparing it with typical PnP models such as MicroPnP, IEEE 1451, and TEDS. The comparison demonstrates that while current models provide comprehensive functionality or high standardization, they often require specialized hardware or substantial resources. In contrast, LitePnP model offers minimalism and ease of integration, making it particularly suitable for low-cost IoT devices and opening up a viable approach for large-scale applications in smart agriculture, environmental monitoring, and industrial automation.

This review paper explores the pivotal role of telecommunications in enabling Internet of Things (IoT) connectivity and applications, providing a comprehensive overview of the current landscape and future prospects. The primary objective is to synthesize existing research and industry insights to highlight how advancements in telecommunications infrastructure and technology have catalyzed the adoption and expansion of IoT. The review systematically examines the evolution of telecommunications technologies, including 4G, 5G, and emerging network protocols such as Narrowband IoT (NB-IoT) and Long-Term Evolution for Machines (LTE-M). It assesses how these technologies enhance IoT connectivity by providing the necessary bandwidth, low latency, and reliability for real-time data exchange and device interoperability. Key findings from the literature reveal that the deployment of 5G networks has been a game-changer for IoT, offering unprecedented speeds and connectivity capabilities that support a wide range of applications in smart cities, healthcare, agriculture, and industrial automation. Additionally, the paper discusses the role of telecommunications in addressing challenges related to security, scalability, and energy efficiency in IoT deployments. The review concludes that telecommunications are integral to the growth and sustainability of IoT ecosystems. As telecommunications technology continues to advance, its ability to support increasingly complex and ubiquitous IoT applications will drive innovation and enhance efficiency across various sectors. The paper emphasizes the necessity for ongoing investment in telecommunications infrastructure and research to fully exploit the transformative potential of IoT connectivity and applications.

This article presents an approach to simulation of the rates of road traffic accidents involving unmanned ground vehicles within a multi-agent intelligent transportation system for the ‘smart city.’ A new simulation model of an intelligent transport system has been developed which makes it possible to significantly reduce the number of potential road traffic accidents (TAs) and implements the concept of socially-centered management of the urban economy. The software implementation of such a large-scale agent-based model was carried out using the FLAME GPU framework, which allows us to effectively parallelize the agents’ behaviour logic and consider their individual decision-making systems when modelling the spacial dynamics of an ensemble of unmanned ground vehicles (UGVs) interacting with other road users: the usual manned ground vehicles (MGVs), unexpected obstacles (e.g., pedestrians, etc.). Various scenarios of such agents’ behaviour in an intelligent transportation system are studied, including the occurrence of an accident under certain conditions (e.g., under the high speed and traffic intensity of UGVs, etc.) and various configurations of the digital road network (DRN). We determine the parameter values that provide for the individual decision-making system of UGVs remaining stable with respect to the characteristics of the external environment (including in extreme situations), ensuring the safety of other road users on the scale of the ‘smart city.’

With the use of technologies, ‘cities’ are able to control everything from traffic lights to the distribution of water in the city, traffic, environment, social actions, health, education, urban planning, security, and public administration, are some of the main areas of activity. The implementation of technology also brings other concerns such as data security and vulnerability and the privacy of individuals. The evolution of intelligent transport systems (ITS) has been accelerated, multifaceted, and often based on the technological advances considered revolutionary for the Urban Mobility sector. Recently, the widespread use of ITS in the operation and management of urban mobility is part of everyday life. Numerous tools are now available for a variety of contexts and scales, with applications that directly impact both locally and globally. This dissertation seeks to analyze the security risk within smart cities. It addresses the theme of what are intelligent transport systems and what are the main solutions to ensure the safety of these systems. To this end, is performed an analysis and classification of ITS threats. With the help of the NS-3 network simulator to model, the ITS communications architecture and the Simulation of Urban Mobility (SUMO) traffic simulator an urban road area scenario was generated. Finally, lessons learned and future research challenges to improve the security of ITS systems are presented.KeywordsSmart citySafetyPrivacyDataInfrastructuresMobilityInternet of Things (IoT)Traffic controlE-GovernanceCybersecurityHackers

Intelligent transportation systems effectively implement dynamic monitoring in transportation through intelligent sensing technologies, but the energy dependency of large‐scale sensor networks is increasingly prominent. Triboelectric nanogenerator (TENG), an innovative environmental energy harvesting technology, utilizes nanomaterials to efficiently convert mechanical energy into a stable electrical output. Additionally, TENG can be deployed as microsensors to form high‐precision sensing networks. Given TENG's technical prospects in transportation, this paper first introduces the fundamental mechanisms and operational modes in specific scenarios. Moreover, it systematically reviews research advances in energy harvesting, infrastructure monitoring, vehicle state sensing, and intelligent system integration. Finally, we discussed challenges for TENG in intelligent transportation, with proposed future research directions and development strategies. These suggestions are proposed for promoting engineering applications of TENG and facilitating the triple transition of intelligent transportation systems toward self‐powered, intelligent sensing, and eco‐friendly directions.