Knowledge Discovery in Smart City Digital Twins

Despite the abundance of available urban data and the potential for reaching enhanced capabilities in the decision-making and management of city infrastructure, current data-driven approaches to knowledge discovery from city data often lack the capacity for collective data exploitation. Loosely defined data interpretation components, or disciplinary isolated interpretations of specific datasets make it easy to overlook necessary domain expertise, often resulting in speculative decision-making. Smart City Digital Twins are designed to overcome this barrier by integrating a more holistic analytics and visualization approach into the real-time knowledge discovery process from heterogeneous city data. Here, we present a spatiotemporal knowledge discovery framework for the collective exploitation of city data in smart city digital twins that incorporates both social and sensor data, and enables insights from human cognition. This is an initial step towards leveraging heterogeneous city data for digital twin-based decision-making

Devising a Game Theoretic Approach to Enable Smart City Digital Twin Analytics

Despite investments in advancing information and communications technology (ICT)-integrated infrastructure systems toward becoming Smarter Cities, cities often face a large gap between smart sustainable supply and demand. Here, we review the core concepts of ICT-integrated infrastructure systems as they pertain to developing smart and sustainable cities, and describe how a game theoretic-based digital twin of a city can enable more visibility and insight into the successful implementation of such systems. This study is a foundational step toward enabling participation of all city stakeholders (i.e., government, industry, and citizens) in the decision making process and the creation of smart sustainable cities. Engaging city stakeholders in such a manner allows for collective participation in changes, which can enable continuous adaptation toward more sustaining growth and prosperity

Towards Smarter Cities: Linking Human Mobility and Energy Use Fluctuations across Building Types

Urban areas consume up to 80 percent of the world\u27s total energy production and are growing in size and complexity. At present, urban building energy consumption is largely considered solely in terms of individual building types, neglecting the effects of residents’ location-based activities that influence patterns in energy supply and demand. Here, we examine the spatial fluctuations of these effects. A spatial regression analysis of 3,613,360 positional records containing human mobility and energy consumption data across 983 areas in Greater London and 801 areas in the City of Chicago in residential and commercial buildings over the course of one month revealed spatial dependencies for both residential and commercial buildings’ energy consumption on human mobility. This dependency represents a strong connection with residential buildings’ energy consumption, with a spatial spillover effect. Future energy efficiency strategies should thus reflect the spatial dependencies, creating new ways for residential buildings to play a major role in energy related strategies

Nonparametric Estimation for SDE with Sparsely Sampled Paths: an FDA Perspective

We consider the problem of nonparametric estimation of the drift and diffusion coefficients of a Stochastic Differential Equation (SDE), based on $n$ independent replicates $\left\{X_i(t)\::\: t\in [0,1]\right\}_{1 \leq i \leq n}$, observed sparsely and irregularly on the unit interval, and subject to additive noise corruption. By \textit{sparse} we intend to mean that the number of measurements per path can be arbitrary (as small as two), and remain constant with respect to $n$. We focus on time-inhomogeneous SDE of the form $dX_t = \mu(t)X_t^{\alpha}dt + \sigma(t)X_t^{\beta}dW_t$, where $\alpha \in \{0,1\}$ and $\beta \in \{0,1/2,1\}$, which includes prominent examples such as Brownian motion, Ornstein-Uhlenbeck process, geometric Brownian motion, and Brownian bridge. Our estimators are constructed by relating the local (drift/diffusion) parameters of the diffusion to their global parameters (mean/covariance, and their derivatives) by means of an apparently novel PDE. This allows us to use methods inspired by functional data analysis, and pool information across the sparsely measured paths. The methodology we develop is fully non-parametric and avoids any functional form specification on the time-dependency of either the drift function or the diffusion function. We establish almost sure uniform asymptotic convergence rates of the proposed estimators as the number of observed curves $n$ grows to infinity. Our rates are non-asymptotic in the number of measurements per path, explicitly reflecting how different sampling frequency might affect the speed of convergence. Our framework suggests possible further fruitful interactions between FDA and SDE methods in problems with replication

The Impact of Nature, The Teaching and Learning of Elementary Lessons in Students 9-11 Years Old (Case Study: Shiraz Elementary Schools)

In today’s world some changes have been occurred in human lifestyle, these changes, along with the advantages, have led to a series of disadvantages including their disconnection with the nature. One of the most important areas to re-establish the relationship is the school. The presence of nature at schools, and holding some classes in nature, in addition to meeting the special needs of children causes their separation from those small and boring classes as well as their interest in courses . This study aimed to investigate the role of nature in children’s learning. For this purpose, third, fourth and fifth grade classes of 3 schools were held outside the school environment and in the nature in 5 courses. The study is a combinational research and field, indirect observation and library data collection methods were applied, where in the indirect observation, two types of questionnaires were prepared related to the students and teachers and were randomly distributed among 580 students and 50 elementary school teachers. Test reliability was assessed using Cronbach’s alpha and it was obtained to be 0.890. The results of this study indicate that the physical place as one of the factors in children’s learning has the maximum impact on teaching and learning of children. At the end of the study and by investigating the existing factors in the environment we understood that the expansion of the nature and natural light of it causes the students’ interest in lessons in nature

Optimal Energy Scheduling of a Solar-Based Hybrid Ship Considering Cold-Ironing Facilities

Abstract There are many restrictions on shipping, which reduce or prohibit the use of diesel generators for feeding the energy demand of the electric ships, especially in ports. Therefore, the use of shore power system (SPS) together with renewable energies and energy storage systems (ESSs) can lead to many environmental benefits while ships are berthing in ports. In this study, the shipboard hybrid power system (HPS) is proposed, including diesel generators, solar photovoltaic panels (PV), ESS and cold‐ironing (CI) facilities for using SPS to efficiently supply the ship's electrical demand. With such HPS aboard, the solar generated power is estimated accurately based on the navigation route. By optimal energy scheduling in a real hybrid cruise ship, the use of diesel generators gets minimised, due to the utilisation of PV and ESS. In addition, using CI service instead of switching on auxiliary diesel generators in ports leads to a 3 h increase in charging and discharging times of the ESS. Furthermore, the efficient use of CI service results in less use of diesel generators even at sailing hours, reducing emissions and minimising the costs of supplying ship's energy demand. The total cost reduction of the HPS in different case studies, without the use of CI services is only 1% to 2%, while this reduction is about 6% to 7% by adding the CI facilities to the HPS. Moreover, the economic characteristics of the proposed diesel‐PV‐ESS‐CI by adding the CI facilities to the HPS are analysed and the profitability of this HPS in reducing the daily costs with considering the share of installation costs on the target day is proved