This is the first issue of the Journal of Smart Cities (JSC), a multidisciplinary forum for publishing original research in the area of smart cities, bringing together scholars from the fields of engineering, urban planning (including transport), computer science, and information and knowledge management. A key objective of the JSC is to promote research for the improvement of all sub-systems of cities, including urban infrastructure, construction, mobility, energy saving and renewable energy, health and social care, safety in the public space, work and innovation, and make the city easily accessible, effective, efficient, and an attractive place to live.

The use of smart technologies combined with city planning have given rise to smart cities, which empower modern urban systems with the efficient tools to cope with growing needs from increasing population sizes. For example, smart sensors are commonly used to improve city operations and management by tracking traffic, monitoring crowds at events, and performance of utility systems and public transportation. Recent advances in nanotechnologies have enabled a new family of sensors, termed self-sensing materials, which would provide smart cities with means to also monitor structural health of civil infrastructures. This includes smart concrete, which has the potential to provide any concrete structure with self-sensing capabilities. Such functional property is obtained by correlating the variation of internal strain with the variation of appropriate material properties, such as electrical resistance. Unlike conventional off-the-shelf structural health monitoring sensors, these innovative transducers combine enhanced durability and distributed measurements, thus providing greater scalability in terms of sensing size and cost. This paper presents recent advances on sensors fabricated using a cementitious matrix with nanoinclusions of Carbon Nanotubes (CNTs). The fabrication procedures providing homogeneous piezoresistive properties are presented, and the electromechanical behavior of the sensors is investigated under static and dynamic loads. Results show that the proposed sensors compare well against existing technologies of stress/strain monitoring, like strain gauges and accelerometers. Example of possible field applications for the developed nanocomposite cement-based sensors include traffic monitoring, parking management and condition assessment of masonry and concrete structures.

Large proportions of the Indian population live in megacities (e.g., Delhi, Mumbai and Kolkata), which are vibrant centers of economic opportunities and offering better quality of social life. Due to increasing migration to these cities, Indian megacities are constantly expanding, which subsequently leads to strain on the environment with a range of impacts at local, regional and global levels. During the last few decades the anthropogenic emissions of greenhouse gases (GHGs) and other air pollutants have increased substantially, resulting in worsening ambient air quality of these cities. With respect to time span the concern over air pollutants has also changed in Indian megacities. Concern over particulate matter, black carbon, NOx and ozone has heightened recently due to their local and regional impacts on air quality and environmental (including public) health and also because they contribute to global climate change. Although authorities have implemented several measures to reduce air pollution and its impacts in Indian megacities, much more is yet to be done to improve their ambient air quality. This paper focuses on major air pollution and GHGs emission issues in Indian megacities and associated problems within the framework of their role in environmental vulnerability.

This paper addresses the problem of low impact of smart city applications observed in the fields of energy and transport, which constitute high-priority domains for the development of smart cities. However, these are not the only fields where the impact of smart cities has been limited. The paper provides an explanation for the low impact of various individual applications of smart cities and discusses ways of improving their effectiveness. We argue that the impact of applications depends primarily on their ontology, and secondarily on smart technology and programming features. Consequently, we start by creating an overall ontology for the smart city, defining the building blocks of this ontology with respect to the most cited definitions of smart cities, and structuring this ontology with the Protégé 5.0 editor, defining entities, class hierarchy, object properties, and data type properties. We then analyze how the ontologies of a sample of smart city applications fit into the overall Smart City Ontology, the consistency between digital spaces, knowledge processes, city domains targeted by the applications, and the types of innovation that determine their impact. In conclusion, we underline the relationships between innovation and ontology, and discuss how we can improve the effectiveness of smart city applications, combining expert and user-driven ontology design with the integration and or-chestration of applications over platforms and larger city entities such as neighborhoods, districts, clusters, and sectors of city activities.

Presented herein is a proposed greedy-search sensor placement optimization heuristic for the detection of water leaks in water distribution networks (WDN). The proposed method is based on entropy, a measure of uncertainty about the source of information, and its main mathematical properties of maximality, subadditivity and equivocation. The method proposes an entropic metric which is subsequently utilized in selecting nodal locations and in heuristically searching for the locations that maximize the total entropy in the WDN, relating maximal entropy with maximal sensing coverage.

Vision techniques are presently developed, within a GIS environment, to detect any type of structural and infrastructure damage caused by natural catastrophic events. The aim of this paper is to report on the implementation of a software tool which is able to identify the border of any system that could be damaged by a negative event. The potential of an open source tool named “Magic Wand” is investigated in order to create an innovative procedure which allows to quickly select buildings and artefacts in disaster areas. The pixels of satellite images are the input that the tool requires. Some examples are presented in order to provide the main features of the proposed function.