Smart Technologies for Smart Cities

The main motivation behind this study was the need to get citizens and parish councils closer. For this purpose, an innovation accelerator to bring smartness to parishes was built. To get all insight, there was the need to learn more about public administration and smart cities and a bit more on innovation and creativity. During the research process, it was also understood that smartness inside a parish must include an improvement on the relationship with citizens, citizens who feel that their opinions count, and citizens’ training to promote digital inclusion and also for parish employees to make sure that their processes are more citizen-centered and an improvement of citizens’ quality of living inside the parish. Those issues were addressed in the final model. The obtained model was validated by a focus group, and it was concluded that the implementation of the proposed framework in a Portuguese parish is aligned with what parishes want for them in the near future.

In parallel with the recent development of technology, users’ interest in smart homes is increasing. Many studies have been carried out to develop smarter products having different technology readiness levels (TRL3–TRL6). The smart home products are on the rise such as smart ovens, smart door systems, smart fire and security systems, etc. Interacting sensors-based smart homes allow users to remotely monitor them either over the Internet or other communication protocols to meet comfort or safety expectations.

This chapter presents a novel mini smart refrigerator that can be used in hotel or village farmhouses. It allows remote monitoring of desired temperature, food and beverage contents and amounts, load shedding, and alarms. The system mounted in a conventional mini-refrigerater consists of microcontroller and Ethernet card, I/O card, LCD display, sensors, and accumulator. The refrigerator with microswitch senses the products inside by microcontroller and Ethernet module. The embedded web pages provided by the OLIMEX-PIC WEB microcontroller are displayed when users want to learn about the products’ information from any web browser.

The designed system is a new low-cost refrigerator that provides user-machine interaction and allows users to remotely monitor their home device. In this context, this chapter provides insight into new trends and innovations in terms of mobility solutions (mobile/web application), conceptual solution architecture, and new hardware and device offerings for visually or other disabled people to increase their social participation in society and contribute to their lives.

The advancements in Internet of things (IoT) technology is quickly transforming the world into a smart network of interoperable devices. Traditional devices are becoming ubiquitous, pervasive, connected, and wearable IoT gadgets. The purpose of this investigation is to develop a smart Child Pocket Monitoring and Protection System (ChildPOPS). ChildPOPS provides a touch of advanced lifestyle by automatically monitoring infant’s health conditions, promoting safe living, and providing an easy-to-deploy system and a user-friendly interface. An IoT Development Model is used to design, represent, and analyze the system through a set of submodels. The main challenges that the proposed system addresses include supporting accurate physiological parameter measurements, remote sensing, and correct detection. This chapter includes studying challenges, such as accurately using the device and the training needed by the users—as related to the adoption of such a modern tool by the target human subjects. The proposed system is supported by two mobile monitoring devices at the child and parent, or caregiver, sides, sensors, wireless communication nodes, control processors, Internet access, and a supporting server. ChildPOPS enables a ubiquitous access using tablets and smartphones through a mobile application or a web browser. This chapter includes studying the effectiveness of adding smart bands, at the child and parents’ sides, to enable accurate monitoring. In addition, the system supports the interaction with a software system that provides assisted communication and intervention when needed. System testing includes multiple detection scenarios and the reliability of interactions. System testing, analysis, and evaluation confirms ChildPOPS effectiveness in application.

Automated fault detection methods (AFDMs) are required to provide a more reliable and stable power system operation and protection. The faults in distributed generators (DGs) connected to the grid must be cleared on time according to the defined Grid Codes, so AFDMs are essential for DGs to improve a smart grid infrastructure. The application of the conventional fault detection methods is highly practical. Besides, difficulties in selecting threshold values, false detection conditions, noise effects in measurement, and uncertain fault conditions in several operating conditions make these methods less reliable.

This chapter generally consists of five main sections. In the introduction, the current fault detection methods used in DG systems are examined. Then, intelligent power quality detection methods are classified, and AFDMs using signal processing techniques in literature are presented. In the second section, FT-based fault detection methods and, in the third section, WT-based fault detection methods are explained. In Section “Detection of Power Quality Events with Wavelet Transform”, different WT methods are also classified and examined. Section “Wavelet Transform-Based Power Quality Disturbance Detection” presents the experimental results obtained from a DG system in real time using the WT method. In this section, some power quality disturbances are investigated in real time by using WT method under different grid conditions. In the last section, the advantages of automatic fault detection methods based on signal processing are explained. As a result, this chapter will help the researchers about studying automated fault detection systems in smart grids consisting of distributed power generators.

The modern power systems require higher levels of secure and reliable power applications for monitoring and controlling the energy of the future cities. The power system state estimation utilises the acquired measurements to deduce the state variables (voltage magnitudes and their phase angles) of the power system. The accuracy and numerical stability of the state estimation is an essential part of the basic unit of the security analysis system in energy control centres. The conventional state estimator is solved by an iterative approach that is sensitive to erroneous measurements. On the other hand, the inclusion of the distribution systems, the radial feeders and the inclusion of the phasor measurement units (PMUs) yield new challenges to the state estimation. This chapter discusses the reasons beyond ill-conditioning, the factors that affect the quality of the state variables, the numerical stability of the state estimator, bad data detection and the available research gaps. Moreover, the presence of high-influential measurements, collinear measurements and their impact on security attack and false data injection are discussed in this chapter with proposing the required solution. However, due to the dual nature of the state estimation (a computer-aided application that is based on the available measurements), the responsibility of enhancing the state estimation is shared among the utilities, the operator and the programmers. Hence, this chapter investigates the problem of enhancing the state estimation by utilising the state-of-the-art statistical studies, measuring devices and meter-based methodologies.

Internet of Things (IoT) is a rapidly emerging field in which everyday things are equipped with sensing and communication capabilities. This is giving rise to numerous innovative solutions in areas such as medical, agriculture, transportation and environment. In this chapter, a vehicular IoT system for real-time air quality monitoring in smart cities is proposed. The main focus of this work is to design a low-cost IoT module for air quality monitoring that can be easily replicated on vehicles and provide good spatial coverage of the status of air quality in a city. The proposed system is an alternative to expensive air quality monitoring stations and provides fine-grained air quality data for better spatial and temporal monitoring. The aim of this chapter is to describe the implementation of a vehicular sensor network that provides high-resolution spatial and temporal monitoring of air quality in smart cities. The air quality sensor data are collected and transmitted to a remote server where a set of analytics tasks are performed in order to calculate the air quality index, thus providing real-time ambient air quality information to the local authorities and population. Moreover, a mobile application was developed for easy access and visualization of the air quality data.

The provision of efficient, sustainable, and personalized mobility services that combine a broad range of transport modes (e.g., public transportation, electric vehicles (EVs), vehicle sharing) constitutes a fundamental challenge in urban environments. This chapter reports on the key results and contributions of the EU-funded research project MOVESMART which addresses the aforementioned challenge. MOVESMART proposes a holistic approach as regards renewable mobility services in smart cities. The MOVESMART approach involves personal mobility services, leverages crowdsourcing techniques for collecting real-time traffic information, and encompasses effective traffic prediction mechanisms. MOVESMART guarantees real-time responses to renewable (on-demand) mobility queries for efficient multimodal route planning that are time-dependent as well as sensitive to aperiodic incidents and traffic prediction forecasts. The core architectural element of MOVESMART is a hierarchical urban traffic infrastructure maintained in a cloud infrastructure. A key outcome of MOVESMART is the design and implementation of novel renewable mobility services which incorporate eco-friendly modes of transport, most notably (shared) electric vehicles. The project delivers a set of innovative cloud-based mobility services; those are delivered through an integrated mobile application which offers a holistic view of renewable mobility incorporating a personalized time-dependent multimodal route-planning service along with EV-sharing and energy efficiency assessment.

Implementing a kriging interpolation model to describe and predict the occurrence of traffic accidents involves the crash with at least one motorcycle. This kind of accidents uses to be disastrous and very tragic. The prediction models can be used to describe the places and situations that cause such accidents and design a solution for this specific problem. Implement a kriging interpolation model to describe and predict the occurrence of traffic accidents that involve the crash with at least one motorcycle. This kind of accidents use to be disastrous and very tragic. The prediction models can be used to describe the places and situations that cause such accidents and design a solution for this specific problem. In the present investigation, the projections for the following 10 years of possible future accidents were modeled on the basis of the repository of traffic accidents related to Italian scooters, and in addition to which, in a trend map, the locations of avenues were specified. It could demonstrate that making proper public policies could improve the awareness of drivers and changes in the timing of traffic and review of alcohol consumption for certain night hours. Finally, there is an improvement guide using a mobile device and the implementation of a ubiquitous computation model.

Since transport is an inalienable right for students in many countries of the world, the problem of school bus routing problem (SBRP) arises, where some students spend a lot of time on these routes. Several restrictions are presented, such as the time of arrival at class and the number of students who can travel on a bus. These restrictions are considered to make the best optimization of routes, with the minimum number of buses needed to move all students, whether from a school or a school district. The school bus routing problem can be modeled computationally, and there are several proposals to solve it, in which some of these were not developed as a program; they remained only in a theoretical approach (as algorithms, pseudocode). There are some proposals in which, if developed as code, such programs are focused on solving the problem in their environment, which makes them difficult to reuse for some other case of school bus routing problem.

Smart mobility is becoming an urgent need in nowadays cities as being one of the major indicators of the quality of life and the key to the economic health of cities. The growing use of information and communication technologies (ICTs) helped people to become more interconnected. Consequently, information are widely shared and used for a better control of humans mobility and for a more efficient use of their time. In this paper, we investigate real-time routing of vehicles serving a set of dispersed customers while minimizing the energy consumption, respecting the vehicles capacities, and the customers service time windows. By means of the shared and collected data, changes in the planned orders and in the environment conditions are revealed overtime and are to be considered to continuously adapt the routes to the new conditions. The problem is modeled as a dynamic vehicle routing problem with time windows, and a new hybrid evolutionary algorithm is proposed to solve it. Our proposal is based on a statistical Pre-Post analysis of the population to create an adaptive balance between the exploration and the exploitation of the search space. In order to validate the proposed approach, a series of experiments is conducted to compare our proposal to several competing approaches from the literature. The experimental results show that the proposed approach excels versus them in most cases.