Search

In this paper we present an architecture for run-time reconfiguration of network-enabled ubiquitous devices. The whole idea is based on a policy-based system where the whole decision-making (e.g. anomaly detection-related) logic is provided in a form of an externally loaded policy file. The architecture is verified through real-life implementation on an embedded system whose sensitivity can be easily modified should a need arise in run-time without affecting network device/segment (and thus potentially a number of network services) so that they continue working while the re-configuration process is triggered. [ABSTRACT FROM AUTHOR]

Owing to the continuous development of technology, the future generation of wireless communication systems is increasingly becoming more complex to support a spectrum of new and existing services and standards. Consequently, the need for flexible and adaptable radios has become more prominent. Radio signals can be modulated using various methods. Radio modulation recognition refers to a series of processes for acquiring information regarding modulation types of non-cooperative received signals. It plays an important role as a pre-demodulation process required to ensure accuracy, safety, and effectiveness in recovering information. This study proposed a reconfigurable multi-radio platform comprising a reconfigurable antenna and receiver board. The antenna was reconfigurable to facilitate operation in different frequency bands controlled via the receiver board using bias voltages. The receiver board was programmable using custom-built software. Moreover, it can detect the modulation scheme and accurately demodulate signals that are modulated in one of three common modulation schemes: amplitude modulation, frequency modulation, and phase modulation. This solution offers the advantages of reduced size, cost, and power consumption because it uses one hardware system as opposed to the deployment of several individual radios. Moreover, the platform presents an adaptable, cost-effective solution for future-generation wireless networks and a flexible and robust terminal that can operate under changing communication environments. [ABSTRACT FROM AUTHOR]

Our ability to align with the trend of innovations in science and technology will not only emancipate ignorance but also unfold our ability to evaluate, understand and predict possibilities in our society, environment, and the world at large. Radar system technology gives us the privilege to achieve the above-mentioned fact. The word Radar is an acronym for Radio Detection and Ranging. It is a mean of getting information about a distant target, by sending electromagnetic waves to them and analyzing the echoes from the target to generate relevant reports about the target. In this paper, we will focus on some metrics and the effect of changes in them on the performance of the radar system using the MATLAB Radar Designer. [ABSTRACT FROM AUTHOR]

This paper investigates the prototyping and implementation of an output feedback-based robust controller on a Field Programmable Gate Array (FPGA) platform. The Smart System under Test (SSuT) in this submission is a flexible cantilever beam bonded with Piezoelectric (PZT 5H) patches that act as a sensor as well as an actuator (perturbance creation as well as control actuation). For ease of modeling and subsequent controller design in the laboratory studies, the low-frequency dynamics of the smart system are approximated to only a Single Degree of Freedom (SDOF) in terms of flexural vibrations. The SSuT is modeled analytically through finite element modeling and experimentally through sub-space system identification process. The developed models’ accuracy is compared with the experimental results of non - parametric modeling. The developed models are then used to conduct the simulation studies with the designed robust output feedback controller in the closed loop. Apart from the simulation studies, the designed controller was also prototyped on an FPGA platform using LabVIEW FPGA with the associated hardware in loop to carry out the experimental validation of its performance. The robustness and efficiency of the prototype controller to control the system vibrations in real-time were proved through extensive tests at single resonant frequencies and a range of frequencies encompassing the dominant resonant regions in the flexural mode. Findings from this study are further used to ensure satisfactory active vibration control of smart cantilever systems in various heavy/aerospace industries by approximating them to suitable benchmark systems in the laboratory.

Deep Neural Networks (DNNs) have shown impressive performance in computer vision tasks; however, their vulnerability to adversarial attacks raises concerns regarding their security and reliability. Extensive research has shown that DNNs can be compromised by carefully crafted perturbations, leading to significant performance degradation in both digital and physical domains. Therefore, ensuring the security of DNN-based systems is crucial, particularly in safety-critical domains such as autonomous driving, robotics, smart homes/cities, smart industries, video surveillance, and healthcare. In this paper, we present a comprehensive survey of the current trends focusing specifically on physical adversarial attacks. We aim to provide a thorough understanding of the concept of physical adversarial attacks, analyzing their key characteristics and distinguishing features. Furthermore, we explore the specific requirements and challenges associated with executing attacks in the physical world. Our article delves into various physical adversarial attack methods, categorized according to their target tasks in different applications, including classification, detection, face recognition, semantic segmentation and depth estimation. We assess the performance of these attack methods in terms of their effectiveness, stealthiness, and robustness. We examine how each technique strives to ensure the successful manipulation of DNNs while mitigating the risk of detection and withstanding real-world distortions. Lastly, we discuss the current challenges and outline potential future research directions in the field of physical adversarial attacks. We highlight the need for enhanced defense mechanisms, the exploration of novel attack strategies, the evaluation of attacks in different application domains, and the establishment of standardized benchmarks and evaluation criteria for physical adversarial attacks. Through this comprehensive survey, we aim to provide a valuable resource for researchers, practitioners, and policymakers to gain a holistic understanding of physical adversarial attacks in computer vision and facilitate the development of robust and secure DNN-based systems.

An investigation was conducted to examine the impact of training in intelligent systems within engineering courses at the university level, considering the parameters and reports on business trends for 2030, as well as the Sustainable Development Goals (SDGs). The study analyzed 2309 subjects across 66 undergraduate degrees offered at nine universities in the Andalusia region, which is the most populous region in Spain. The objective of this research is to assess whether the training in intelligent systems, specifically in the fields of electrical engineering, electronics, computer science, and telecommunications, adequately prepares students in their final years of study to meet the demands of the labor and business market. Reports and trend studies have identified the urgent areas that require attention, including training in sensors, smart grids, smart cities, IoT, artificial intelligence, embedded systems, among others. The investigation provides insights into the current state of training in intelligent systems within the final years of engineering programs. These findings will inform future curriculum development and teaching guidelines, with the goal of enhancing students’ knowledge and skills in line with technological and engineering trends. The study will analyze subjects across various Spanish universities in Andalusia, considering their rankings. Based on the analysis of the results, recommendations for improvement actions and strategies to strengthen the curriculum will be proposed.

Machine learning (ML) and the internet of things (IoT) are among the most booming research directions. Smart cities, smart campuses (SCs), smart homes, smart cars, early warning systems (EWSs), etc.; or it could be called “Smart x” systems are implemented using ML and IoT. Those systems will alter how various world entities communicate with one another. This paper spots light on the significant roles of the IoT in SS. Also, it focuses on the importance of ML in IoT-based SS. Besides, an overview of smartness and IoT is presented. Then, this paper offers ML benchmarking along with a taxonomy that categorizes the ML models into linear and non-linear ones depending on the problem type (classification or regression). Afterward, the commonly utilized evaluation metrics are provided. In addition, this paper considers the trust techniques used for mitigating different security aspects in IoT networks, which play a crucial part in regulating the new era of communication. Moreover, two case studies devoting ML for IoT-based SS, namely IoT-based SC and IoT-based EWS, are considered for data collection and manipulation with guided research directions. Finally, the paper presents effective recommendations of ML’s significant roles in SC and earthquake EWS for interested scholars.

The demand for artificial intelligence in the world is increasing day by day in the gastronomy sector. In this study, the importance of artificial intelligence in the gastronomy sector is emphasized and the studies on this subject are mentioned. Since the studies in the literature are limited, studies on all sub-branches related to artificial intelligence-based gastronomy and tourism are mentioned. The number of studies related to gastronomy and artificial intelligence in the literature is limited. Therefore, in this study, artificial intelligence applications used in the gastronomy sector are detailed under the subheadings of cuisine, promotion, health, and forecasting. Accordingly, approximately 40 articles were analyzed considering these sub-headings. In light of the information obtained from these studies, artificial intelligence systems to be developed in the gastronomy sector will provide great gains. Moreover, it is estimated that meeting consumer expectations and using innovative technologies in the gastronomy sector will increase the popularity of gastronomy science.

Existing food production and consumption rate, especially from consumer's point of view, cannot be measured as viable due to varieties of social economic factors involved in the food supply chain. Combating food waste contributes extensively to food security measures and easing conservational burden thus improving justifiable consumption of food. Food waste emanating from consumers especially individual households is huge. A systematic approach to mitigate this is creatively enlightening consumers through alertness and campaigns. However, literature reveals that complimentary initiatives are required to confront the problem of consumer waste. Emerging technologies and their uniqueness are comparatively gaining attention to lead consumers carefully using improved technical platforms and solutions in the right direction towards reducing food waste. This study tackles this research gap by conducting comprehensive reviews of articles pointing to food wastage prevention, weaknesses, and potential usage of ICT tools to positively impact consumers and reduce food wastage. The study focuses on the use of ICT tools and techniques as a means to reduce food wastage. The reviews covered existing food wastage-saving measures and applications (e.g., smart kitchen appliances, smart packaging and mobile applications). It further proposed a broad ICT driven food wastage avoidance framework that deals with the problem holistically. The framework shows how various levels of the food supply chain can be integrated to tackle wastages from top to bottom in avoiding consumer wastage. However, future research is required to validate and build on this framework. [ABSTRACT FROM AUTHOR]

This article discusses the relationship between urban slums and the management of the urban infrastructure network (electrification). An extensive survey of the scientific literature on the subject points out the main challenges and possible solutions for fixing precarious electrical infrastructure in urban slums through the promotion of public policies and the establishment of new arrangements based on distributed generation technologies and smart grid. A dialogue was also developed involving topics such as sustainable development and electrification of slums; relationship between communities and modernization of electrification; and emerging and sustainable technologies in the context of urban slums. Thus, a design was constructed that triggered a discussion of the relationship between this work and several other works found in the literature. This research indicates the need to strengthen local governance and the participation of urban slums for the technological modernization of the local electrical network, mainly with the implementation of smart grid and photovoltaic generation systems. [ABSTRACT FROM AUTHOR]

The utilization of Fiber Bragg Grating (FBG) sensors in innovative optical sensor networks has displayed remarkable potential in providing precise and dependable thermal measurements in hostile environments on Earth. Multi-Layer Insulation (MLI) blankets serve as critical components of spacecraft and are employed to regulate the temperature of sensitive components by reflecting or absorbing thermal radiation. To enable accurate and continuous monitoring of temperature along the length of the insulative barrier without compromising its flexibility and low weight, FBG sensors can be embedded within the thermal blanket, thereby enabling distributed temperature sensing. This capability can aid in optimizing the thermal regulation of the spacecraft and ensuring the reliable and safe operation of vital components. Furthermore, FBG sensors offer sev eral advantages over traditional temperature sensors, including high sensitivity, immunity to electromagnetic interference, and the ability to operate in harsh environments. These properties make FBG sensors an excellent option for thermal blankets in space applications, where precise temperature regulation is crucial for mission success. Nevertheless, the calibration of temperature sensors in vacuum conditions poses a significant challenge due to the lack of an appropriate calibration reference. Therefore, this paper aimed to investigate innovative solutions for calibrating temperature sensors in vacuum conditions. The proposed solutions have the potential to enhance the accuracy and reliability of temperature measurements in space applications, which can enable engineers to develop more resilient and dependable spacecraft systems. [ABSTRACT FROM AUTHOR]

Mobile computing has emerged as a pervasive technology that empowers its users with portable computation and context-aware communication. Smart systems and infrastructures can exploit portable and context-aware computing technologies to provide any time, any place digitized services on the go. Despite the offered benefits, such as portability, context-sensitivity, and high connectivity, mobile computing also faces some critical challenges. These challenges include resource poverty as well as data security and privacy that need to be addressed to increase the pervasiveness of mobile systems. We propose to provide a self-protection mechanism for mobile devices against the unforeseen security threats that can attack the critical resources of mobile devices. We have unified the concepts of autonomic computing and computer security to develop a framework that enables adaptive security to dynamically configure the security measures of a mobile device. We have developed a framework - an android-based prototype - that supports automation and user decision to protect the critical hardware and software resources of a device. Evaluation results demonstrate (i) framework's accuracy for runtime detection and minimization of threats, and (ii) framework's efficiency for device's resource utilization. [ABSTRACT FROM AUTHOR]

In this paper we present an architecture for run-time reconfiguration of network-enabled ubiquitous devices. The whole idea is based on a policy-based system where the whole decision-making (e.g. anomaly detection-related) logic is provided in a form of an externally loaded policy file. The architecture is verified through real-life implementation on an embedded system whose sensitivity can be easily modified should a need arise in run-time without affecting network device/segment (and thus potentially a number of network services) so that they continue working while the re-configuration process is triggered.

The presented study proposes a framework for applying smart mobility in contemporary urban contexts. It starts with a literature investigation and analysis; subsequently, it synthesizes the main key findings into a framework for applying smart mobility comprising five main dimensions, seven patterns, and 34 attributes. Then it applied a survey to investigate the applicability of 34 smart mobility attributes in two selected districts in Greater Cairo Region. Results of the presented work highlight the degree of existence of smart mobility attributes in the selected districts, through site visits and community survey. Also, the five smart mobility dimensions are shown to be important regarding experts’ ratings which ranged from 3.5 to 4.7. In addition to smart mobility objectives which ratings ranged from 3.5 to 4.6. Finally, the study compared experts’ and users’ ratings for travel efficiency attributes. Moreover, it points out the potential of smart mobility applications in the Egyptian context.

The advent of Industry 4.0 necessitates substantial interaction between humans and machines, presenting new challenges when it comes to evaluating the stress levels of workers who operate in increasingly intricate work environments. Undoubtedly, work-related stress exerts a significant influence on individuals’ overall stress levels, leading to enduring health issues and adverse impacts on their quality of life. Although psychological questionnaires have traditionally been employed to assess stress, they lack the capability to monitor stress levels in real-time or on an ongoing basis, thus making it arduous to identify the causes and demanding aspects of work. To surmount this limitation, an effective solution lies in the analysis of physiological signals that can be continuously measured through wearable or ambient sensors. Previous studies in this field have mainly focused on stress assessment through intrusive wearable systems susceptible to noise and artifacts that degrade performance. One of our recently published papers presented a wearable and ambient hardware-software platform that is minimally intrusive, able to detect human stress without hindering normal work activities, and slightly susceptible to artifacts due to movements. A limitation of this system is its not very high performance in terms of the accuracy of detecting multiple stress levels; therefore, in this work, the focus was on improving the software performance of the platform, using a deep learning approach. To this purpose, three neural networks were implemented, and the best performance was achieved by the 1D-convolutional neural network with an accuracy of 95.38% for the identification of two levels of stress, which is a significant improvement over those obtained previously.

In this paper, a report on the development of an Internet of Things (IoT)-based connected university system is presented. There have been multiple smart solutions developed at the university over recent years. However, the user base of these systems is limited. The IoT-based connected university system allows for integration of multiple subsystems without the need to implement all of them in the same environment, thus enabling end-users to access multiple solutions through a single common interface. The implementation is based on microservice architecture, with the focus mainly on system robustness, scalability, and universality. In the system design, four subsystems are currently implemented, i.e., the subsystem for indoor navigation, the subsystem for parking assistants, the subsystem for smart classrooms or offices, and the subsystem for news aggregation from university life. The principles of all implemented subsystems, as well as the implementation of the system as a web interface and a mobile application, are presented in the paper. Moreover, the implementation of the indoor navigation subsystem that uses signals from Bluetooth beacons is described in detail. The paper also presents results proving the concept of the Bluetooth-based indoor navigation, taking into account different placements of nodes. The tests were performed in a real-world environment to evaluate the feasibility of the navigation module that utilizes deterministic fingerprinting algorithms to estimate the positions of users' devices. [ABSTRACT FROM AUTHOR]

The present developed a bioprocess to produce nano-biofertilizers from agro-industrial residues by augmentation of microbial agents and vermitechnology. The agroresidues like coir peat, neem cake, pongamia cake, castor cake and polyculture of microorganisms having psuedomonas florescence, microbacterium laevoniformins and pseudomonas putida are added to initiate the degradation of complex biomolecules in the plant biomass into nanosized nutrients line nitrogen (N), phosphorous (P) and potassium (K). The stabilization of produced nano-nutrients are achieved by subjecting to vermitechnology to produce vermicompost aggregates through the associated gut enzymes. The nano-dimension of nutrients are conformed through UV spectrophotometer resulted in higher obsorption compared to control vermicompost. The nano-dimension of nano-nutrients were confirmed by subjecting to dynamic light scattering (DLS) techniques which ranged between 25-50nm. The safety and growth efficiency of nano-fertilizer has been assessed using bioassays like seed germination test on raddish vegetable crop which yielded 100 per cent over vermicompost 90 per cent germination efficiency. The growth indices in the potculutre studies reveals 100 per cent over control vermicompost applied plants showing 90 per cent. This gives scientific support to application of nano-biofertilizer to enhance the growth and yield of the crop and also standardized the process to produce nanobiofertilizers using augmented method of microbial polyculture and vermitechnology. [ABSTRACT FROM AUTHOR]

Robotic Process Automation (RPA) is a rules-based system for automating business processes by software bots that mimic human interactions to relieve employees from tedious work. It was verified in the literature that there are few works related to RPA decision support models. This technology is in great growth and, therefore, it becomes important to study the evaluation of the implementation of RPA. The objective of this work is focused on a literature review for the identification and analysis of Robotic Process Automation implementation models. This work analyses some models or studies available in the literature and, in addition, analyses it from a perspective relating to the Triple Bottom Line (TBL) related to environmental, social and economic effects. Regarding the results obtained, it appears that there is still a lot of room to improve research in this field, for example, with regard to the development of an evaluation model for the implementation of the RPA, taking into account the TBL of the sustainability concept. [ABSTRACT FROM AUTHOR]

With the emergence of new technologies, the design of urban infrastructure is constantly being innovated, and the lawn lamp as urban lighting infrastructure is an important part of urban infrastructure. For the current lawn lamp function, there are single, large power consumption, low light energy utilization and other shortcomings. Combined with deep learning and optical design, this paper constructs an adaptive lighting control system based on the technology of the Internet. Considering the nonlinear and time-varying characteristics of external factors, a fuzzy control model with ambient light level and pedestrian flow as input and dimming coefficient K (0 < K < 1) as output is proposed to adjust the brightness of the light source and achieve energy savings. In order to improve the light energy utilization of the luminaire and reduce the glare index of the luminaire, a free-form total internal reflection (TIR) lens was designed by finding the optimal curvature of the lens through the polycurved edge light principle. The light source of the lawn lamp was simulated by TracePro, and the results showed that the light energy utilization reached 90%. Finally, the ambient illumination and pedestrian flow data of Dalian ZT Park were measured for different time periods at the site, and the data were normalized using the min-max normalization algorithm. The adaptive dimming capability of the system was verified through simulation tests and field tests, and the results showed that the lighting energy efficiency under the control system was 38%. [ABSTRACT FROM AUTHOR]

An emergency water station for migrants crossing the Texas-Mexico border is designed and implemented. This station uses satellite communication to send the number of remaining water jugs to the volunteers in charge of replenishment. This paper outlines the features of the complete design and discusses the primary functions of the main three subsystems of the station. The first subsystem is the station structure, which holds the water jugs, electronics equipment and the flagpole. The second subsystem consists of the electronics/communication system which tallies and transmits the number of water jugs remained in the station. The third component is the solar-based power system to charge the batteries and provide power to the electronic components. The fully constructed design fits within a standard truck bed (78" x 64") for easy transportation. It can withstand an operational temperature of 20°F - 140°F and a maximum wind speed of 40mph. Special attention is paid to the operational cost of the communication system to keep it under $5 per month. The number of one-gallon water jugs remained in the station is reported at least once per day within the accuracy of ±1 jug. The station is visible at night from at least one mile away by using LED mounted on top of a 25-foot pole. [ABSTRACT FROM AUTHOR]

Seeking continuous development, a modern community must also be able to adapt to future possible challenges using constrained or limited resources. As a revolutionary communication paradigm, the Internet of Things (IoT) empowers the cutting-edge and emerging applications which enable manifold new intelligent services towards a smart community. The sophisticated ecosystem of a digital community is made feasible by the IoT infrastructure, which also provides community control with access to a wealth of actual data. In addition, IoT platforms empower the ubiquitous computing ability, providing more potentials to the actuators in perception layer in the IoT architecture. With more and more population in the urban areas, sustainability issues have become a key factor to consider in the development of a digital community. We give a modern survey in this study on the most recent developments in IoT for sustainable digital communities. After carefully examining the most recent literature, we specifically highlight the various smart digital community application scenarios, such as smart buildings, energy management, green transportation, trash management, etc. We also look into a number of major issues facing the use of IoT technology in digital communities. Furthermore, we discuss potential future applications and future research areas for IoT, the critical component of sustainable digital communities.

The distribution system is the power grid component that forms the network pathways of distributing the power generated to their various feeders connected across it to meet the required load demand. As of recent, its operation of distributing quality power to its cherished feeders and consumers has become a major challenge due to the complicated nature of applying smart systems to meet the high and sophisticated load demands in this dispensation where advancement in engineering, science and technology is becoming predominant. Currently, high concerns have been raised on soliciting effective management techniques to curb these problems bedeviling the power distribution network. Hence this research article sort to present an overview of some of the pertinent strategic management techniques of smart systems for power distribution operations to bring security, stability, reliability, power quality to the distribution network and also enhance the system performance of the power grid as a whole.

Sector coupling and energy sharing are key elements in effectively decarbonising the thermal grid. 5th Generation District Heating and Cooling (5GDHC) provides a system for combining heating and cooling via an ambient temperature network. A main design challenge for 5GDHC is establishing a control regime that allows flow bidirectionality and energy synergies between heating and cooling. This work develops and experimentally validates a 5GDHC system wide hydraulic design and two fitting control strategies on a small scale. One has fixed grid return temperatures (T G r i d F i x) while the other free floating grid temperatures (T G r i d F l o a t). Both feature decentralised variable speed pumping and a centralised passive balancing unit aimed at alleviating control instabilities arising from pump hunting. Experiments showed that T G r i d F i x demonstrates slightly higher electrical consumption for the booster heat pump (Seasonal Coefficient of Performance of 3.84 compared to 4.16 for 20 h of operation) due to a mismatch between the evaporator and the grid temperature difference. Overall, T G r i d F i x can lead to low prosumer interaction and better system wide predictability. Further considerations on generalisability of findings and full-scale implementations are highlighted. This works presents a set of detailed and experimentally validated control philosophies for 5GDHC systems, elucidating a key system implementation challenge. • Hydraulic and control designs for 5th Generation District Heating and Cooling. • Experimental validation using Power Hardware in the Loop for prosumer interaction. • Highlighting key design elements for selecting the best control strategy. [ABSTRACT FROM AUTHOR]

Museums environment is complicated and defined by indoor air quality, thermal and lighting comfort. Artifacts deterioration is factored by extreme conditions of thermal exposure or excessive lighting. With high control required for exposed old monuments and visitor comfort, museums energy systems reach extreme levels. In this paper, we aim to find the gap in museums high energy loads and reach solutions through architectural design. The paper studies comparison results for different techniques in fifty recent case studies to identify the specific factors that matter most to museum buildings. These factors are implemented simultaneously on one base model in three climatic states by multi-objective optimization. The best option will showcase each climate optimum conditions. The paper introduces optimum architectural procedures optimizing sDA and ASE to minimum 70% and maximum 10% respectively while decreasing thermal load. The results help architects and policy makers achieve daylighting and energy optimization in museums through architecture. [ABSTRACT FROM AUTHOR]

The Internet of Everything (IoE) represents a paradigm shift in the world of connectivity. While the Internet of Things (IoT) initiated the era of interconnected devices, the IoE takes this concept to new heights by interlinking objects, individuals, data, and processes. Symmetry in IoE innovation and technology is essential for creating a harmonious and efficient ecosystem to ensure that the benefits are accessible to a broad spectrum of society while minimizing potential drawbacks. This comprehensive review paper explores the multifaceted landscape of the IoE, delving into its core concepts, enabling technologies, real-world applications, and the intricate web of challenges it presents. A focal point of this review is the diverse array of real-world applications spanning healthcare, smart cities, industry 4.0, agriculture, and sustainability. Previous works and examples illustrate how the IoE reshapes these domains, leading to greater efficiency, sustainability, and improved decision making. However, the transformative power of the IoE is accompanied by a host of challenges, including security and privacy concerns, interoperability issues, and the ethical implications of ubiquitous connectivity. These challenges are dissected in order to comprehensively understand the obstacles and potential solutions in the IoE landscape. As we stand on the cusp of an IoE-driven future, this review paper serves as a valuable resource for researchers, policy makers, and industry professionals seeking to navigate the complexities of this emerging paradigm. By illuminating the intricacies of the IoE, this review fosters a deeper appreciation for the transformative potential and the multifaceted challenges that lie ahead in the Internet of Everything era.

Smart and integrated urban water systems have important roles in advancing smart cities, but their contributions go much further by supplying needed public services and connecting other sectors to meet sustainability goals. Achieving integration and gaining access to financing are obstacles to implementing smart water systems and both are implicit in the economic framework of smart cities. Problems in financing the start-up of smart water systems are reported often. The local and diverse nature of water systems is another barrier because an approach that works in one place may not work in another with different conditions. The paper identifies the challenges posed by the economic framework and provides examples from four cities with diverse characteristics. It outlines pathways to advance implementation of smart water systems by improving control strategies, advancing instrumentation and control technologies, and most of all, to help transform cities by raising customer awareness and trust through reliable and useful water information.

As far as I am concerned, not at all, and I am going to show why! When most people hear the expression ‘Smart City’, they associate it with a future city where thousands of sensors are installed and connected with each other and the central computer-based unit. Other groups of people think of the smart city as represented by high quality and future visionary high-end instruments and electric cars. However, the smart city is based on an interaction between city systems, public safety, health, education, and citizens’ services. This cooperation makes the city a healthier, safer place for people to live in. Nowadays, public safety is of paramount importance like energy management, smart transport, or building automation. In this article, I am going to describe how we can manage public safety by transforming the city environment in a proprietary way. I use the principles of Crime Prevention Through Environmental Design for redesigning the city environment.

The demand for artificial intelligence in the world is increasing day by day in the gastronomy sector. In this study, the importance of artificial intelligence in the gastronomy sector is emphasized and the studies on this subject are mentioned. Since the studies in the literature are limited, studies on all sub-branches related to artificial intelligence-based gastronomy and tourism are mentioned. The number of studies related to gastronomy and artificial intelligence in the literature is limited. Therefore, in this study, artificial intelligence applications used in the gastronomy sector are detailed under the subheadings of cuisine, promotion, health, and forecasting. Accordingly, approximately 40 articles were analyzed considering these subheadings. In light of the information obtained from these studies, artificial intelligence systems to be developed in the gastronomy sector will provide great gains. Moreover, it is estimated that meeting consumer expectations and using innovative technologies in the gastronomy sector will increase the popularity of gastronomy science. [ABSTRACT FROM AUTHOR]

The issue of Automated Meter Management (AMM), an integral part of modern energy smart grid systems, has become a hot topic in recent years. With the current energy crisis, and given the new approaches to smart energy and its regulation, implemented at the level of the European Union, the gradual introduction of AMM as a standard for the regulation and management of the distribution system is an absolute necessity. Modern smart grids incorporate elements of smart regulation that rely heavily on the availability and quality of the data generated or used during AMM as part of the smart grid. In this paper, based on an analytical view of AMM as a whole and guided interviews with the sponsors of each service and owners of each dataset, criteria are proposed and a Business Impact Analysis (BIA) is implemented, the results of which are used to determine security measures for the safe and reliable running of the AMM system. This paper offers a unique view of the AMM system as an integral part of modern smart grid networks from a data-driven perspective that enables the subsequent implementation and fulfillment of security requirements by ISO/IEC 27001 and national security standards, as the AMM system is also a critical information system under the EU directive regarding the cybersecurity of network and information systems, which are subject to newly defined security requirements in the field of cybersecurity.

The application of internet of things (IoT) has reached all fields and industries with variation among countries. One of the industries that received less attention is the agriculture. This research intended to identify the factors that affect the intention to use IoT (IUIoT) among farmers in developing countries such as Iraq. Based on technology acceptance model (TAM) and theory of planned behavior (TPB), this study proposed that perceived usefulness (PU), perceived complexity (PC), subjective norms (SN), reliability (RE) and cost saving (CS) will affect the IUIoT. Perceived value (PV) is proposed as a mediator while land size is proposed as a moderator. The data of this study was collected from 223 farmers in Iraq using purposive sampling. The analysis of Smart PLS showed that the effect of PU, PC, RE, SN, and CS on IUIoT are significant. PV mediated fully the effect of PC and partially the effect of other variables on IUIoT. Land size did not moderate the effect of PV on IUIoT. Decision makers are recommended to ease the process of using the IoT and to enlighten farmers about the benefits of using the IoT. [ABSTRACT FROM AUTHOR]