Smart cities: a survey

A smart city is one that uses a smart system characterized by the interaction between infrastructure, capital, behaviors and cultures, achieved through their integration. From our survey of the smart city concept by reading recent papers in this field, we found no uniform concept of the smart city; some papers discussed it as a general case study, while others dealt with specific parts. This paper is a survey of a number of articles , which we divided into two categories:1-General case study, which covers the topic of smart city in a general framework, and 2-Specific case study, which covers the topic of the smart city from a specific detailed application, such as Traffic Management System, Smart Grid, Wireless Technology,…etc. The results of our research show that the information of communication technology (ICT) covers all areas on smart cities such as government facilities, buildings, traffic, electricity, health, water, and transport. Until now there is no unique definition for smart cities, most of researcher define the smart city form their needs or prospective

Service Oriented Smart Sustainable City Architecture

In present world development of a country is measured in terms of the communication technology infrastructure of that Country. Information communication technology(ICT) is not  limited to internet usage and mere interconnection of  connecting devices now .but has advanced deep into the major transaction  of our day-to-day operations almost in every aspect of  livelihood be it a health care, personnel, economic transaction, Industry, monitoring ,environment protection or automation process. This has given rise to apt number of concepts and disciplines in the field of ICT. The concept of smart city is one of the outcome of our endeavour to use ICT to its full. Smart cities, which will lead to smart nations and ultimately smart world is the discipline which needs due attention from the researchers, engineering and policy makers. Architecture of the Smart city forms the basis of this concept, which is yet to get the final standard. In this paper an Architecture is proposed which is generic and almost covers most of issues to achieve the goal of smart cities. Keywords: Smart sustainable city, Internet of Things (IOT), Security, Information Communication Technology (ICT

Modeling Autonomous Agents In Military Simulations

Simulation is an important tool for prediction and assessment of the behavior of complex systems and situations. The importance of simulation has increased tremendously during the last few decades, mainly because the rapid pace of development in the field of electronics has turned the computer from a costly and obscure piece of equipment to a cheap ubiquitous tool which is now an integral part of our daily lives. While such technological improvements make it easier to analyze well-understood deterministic systems, increase in speed and storage capacity alone are not enough when simulating situations where human beings and their behavior are an integral part of the system being studied. The problem with simulation of intelligent entities is that intelligence is still not well understood and it seems that the field of Artificial Intelligence (AI) has a long way to go before we get computers to think like humans. Behavior-based agent modeling has been proposed in mid-80\u27s as one of the alternatives to the classical AI approach. While used mainly for the control of specialized robotic vehicles with very specific sensory capabilities and limited intelligence, we believe that a behavior-based approach to modeling generic autonomous agents in complex environments can provide promising results. To this end, we are investigating a behavior-based model for controlling groups of collaborating and competing agents in a geographic terrain. In this thesis, we are focusing on scenarios of military nature, where agents can move within the environment and adversaries can eliminate each other through use of weapons. Different aspects of agent behavior like navigation to a goal or staying in group formation, are implemented by distinct behavior modules and the final observed behavior for each agent is an emergent property of the combination of simple behaviors and their interaction with the environment. Our experiments show that while such an approach is quite efficient in terms of computational power, it has some major drawbacks. One of the problems is that reactive behavior-based navigation algorithms are not well suited for environments with complex mobility constraints where they tend to perform much worse than proper path planning. This problem represents an important research question, especially when it is considered that most of the modern military conflicts and operations occur in urban environments. One of the contributions of this thesis is a novel approach to reactive navigation where goals and terrain information are fused based on the idea of transforming a terrain with obstacles into a virtual obstacle-free terrain. Experimental results show that our approach can successfully combine the low run-time computational complexity of reactive methods with the high success rates of classical path planning. Another interesting research problem is how to deal with the unpredictable nature of emergent behavior. It is not uncommon to have situations where an outcome diverges significantly from the intended behavior of the agents due to highly complex nonlinear interactions with other agents or the environment itself. Chances of devising a formal way to predict and avoid such abnormalities are slim at best, mostly because such complex systems tend to be be chaotic in nature. Instead, we focus on detection of deviations through tracking group behavior which is a key component of the total situation awareness capability required by modern technology-oriented and network-centric warfare. We have designed a simple and efficient clustering algorithm for tracking of groups of agent suitable for both spatial and behavioral domain. We also show how to detect certain events of interest based on a temporal analysis of the evolution of discovered clusters

An indoor test methodology for solar-powered wireless sensor networks

Repeatable and accurate tests are important when designing hardware and algorithms for solar-powered wireless sensor networks (WSNs). Since no two days are exactly alike with regard to energy harvesting, tests must be carried out indoors. Solar simulators are traditionally used in replicating the effects of sunlight indoors - however, solar simulators are expensive, have lighting elements that have short lifetimes, and are usually not designed to carry out the types of tests that hardware and algorithm designers require. As a result, hardware and algorithm designers use tests that are inaccurate and not repeatable (both for others and also for the designers themselves). In this article we propose an indoor test methodology which does not rely on solar simulators. The test methodology has its basis in astronomy and photovoltaic (PV) cell design. We present a generic design for a test apparatus which can be used in carrying out the test methodology. We also present a specific design which we use in implementing an actual test apparatus. We test the efficacy of our test apparatus and, to demonstrate the usefulness of the test methodology, perform experiments akin to those required in projects involving solar-powered WSNs. Results of the said tests and experiments demonstrate that the test methodology is an invaluable tool for hardware and algorithm designers working with solar-powered WSNs

Cyber-Physical Power System (CPPS): A Review on Modelling, Simulation, and Analysis with Cyber Security Applications

Cyber-Physical System (CPS) is a new kind of digital technology that increases its attention across academia, government, and industry sectors and covers a wide range of applications like agriculture, energy, medical, transportation, etc. The traditional power systems with physical equipment as a core element are more integrated with information and communication technology, which evolves into the Cyber-Physical Power System (CPPS). The CPPS consists of a physical system tightly integrated with cyber systems (control, computing, and communication functions) and allows the two-way flows of electricity and information for enabling smart grid technologies. Even though the digital technologies monitoring and controlling the electric power grid more efficiently and reliably, the power grid is vulnerable to cybersecurity risk and involves the complex interdependency between cyber and physical systems. Analyzing and resolving the problems in CPPS needs the modelling methods and systematic investigation of a complex interaction between cyber and physical systems. The conventional way of modelling, simulation, and analysis involves the separation of physical domain and cyber domain, which is not suitable for the modern CPPS. Therefore, an integrated framework needed to analyze the practical scenario of the unification of physical and cyber systems. A comprehensive review of different modelling, simulation, and analysis methods and different types of cyber-attacks, cybersecurity measures for modern CPPS is explored in this paper. A review of different types of cyber-attack detection and mitigation control schemes for the practical power system is presented in this paper. The status of the research in CPPS around the world and a new path for recommendations and research directions for the researchers working in the CPPS are finally presented.publishedVersio

Rich Socio-Cognitive Agents for Immersive Training Environments: Case of NonKin Village

Demand is on the rise for scientifically based human-behavior models that can be quickly customized and inserted into immersive training environments to recreate a given society or culture. At the same time, there are no readily available science model-driven environments for this purpose (see survey in Sect. 2). In researching how to overcome this obstacle, we have created rich (complex) socio-cognitive agents that include a large number of social science models (cognitive, sociologic, economic, political, etc) needed to enhance the realism of immersive, artificial agent societies. We describe current efforts to apply model-driven development concepts and how to permit other models to be plugged in should a developer prefer them instead. The current, default library of behavioral models is a metamodel, or authoring language, capable of generating immersive social worlds. Section 3 explores the specific metamodels currently in this library (cognitive, socio-political, economic, conversational, etc.) and Sect. 4 illustrates them with an implementation that results in a virtual Afghan village as a platform-independent model. This is instantiated into a server that then works across a bridge to control the agents in an immersive, platform-specific 3D gameworld (client). Section 4 also provides examples of interacting in the resulting gameworld and some of the training a player receives. We end with lessons learned and next steps for improving both the process and the gameworld. The seeming paradox of this research is that as agent complexity increases, the easier it becomes for the agents to explain their world, their dilemmas, and their social networks to a player or trainee

Adaptation strategies for self-organising electronic institutions

For large-scale systems and networks embedded in highly dynamic, volatile, and unpredictable environments, self-adaptive and self-organising (SASO) algorithms have been proposed as solutions to the problems introduced by this dynamism, volatility, and unpredictability. In open systems it cannot be guaranteed that an adaptive mechanism that works well in isolation will work well — or at all — in combination with others. In complexity science the emergence of systemic, or macro-level, properties from individual, or micro-level, interactions is addressed through mathematical modelling and simulation. Intermediate meso-level structuration has been proposed as a method for controlling the macro-level system outcomes, through the study of how the application of certain policies, or norms, can affect adaptation and organisation at various levels of the system. In this context, this thesis describes the specification and implementation of an adaptive affective anticipatory agent model for the individual micro level, and a self-organising distributed institutional consensus algorithm for the group meso level. Situated in an intelligent transportation system, the agent model represents an adaptive decision-making system for safe driving, and the consensus algorithm allows the vehicles to self-organise agreement on values necessary for the maintenance of “platoons” of vehicles travelling down a motorway. Experiments were performed using each mechanism in isolation to demonstrate its effectiveness. A computational testbed has been built on a multi-agent simulator to examine the interaction between the two given adaptation mechanisms. Experiments involving various differing combinations of the mechanisms are performed, and the effect of these combinations on the macro-level system properties is measured. Both beneficial and pernicious interactions are observed; the experimental results are analysed in an attempt to understand these interactions. The analysis is performed through a formalism which enables the causes for the various interactions to be understood. The formalism takes into account the methods by which the SASO mechanisms are composed, at what level of the system they operate, on which parts of the system they operate, and how they interact with the population of the system. It is suggested that this formalism could serve as the starting point for an analytic method and experimental tools for a future systems theory of adaptation.Open Acces