Through the clouds : urban analytics for smart cities

Data has been collected since mankind, but in the recent years the technical innovations enable us to collect exponentially growing amounts of data through the use of sensors, smart devices and other sources. In her lecture Nanda will explore the role of Big Data in urban environments. She will give an introduction to the world of Big Data and Smart Cities, and an assessment of the role that data analytics plays in the current state of the digital transformation in our cities. Examples are given in the field of energy and mobility

Recent advances in industrial wireless sensor networks towards efficient management in IoT

With the accelerated development of Internet-of- Things (IoT), wireless sensor networks (WSN) are gaining importance in the continued advancement of information and communication technologies, and have been connected and integrated with Internet in vast industrial applications. However, given the fact that most wireless sensor devices are resource constrained and operate on batteries, the communication overhead and power consumption are therefore important issues for wireless sensor networks design. In order to efficiently manage these wireless sensor devices in a unified manner, the industrial authorities should be able to provide a network infrastructure supporting various WSN applications and services that facilitate the management of sensor-equipped real-world entities. This paper presents an overview of industrial ecosystem, technical architecture, industrial device management standards and our latest research activity in developing a WSN management system. The key approach to enable efficient and reliable management of WSN within such an infrastructure is a cross layer design of lightweight and cloud-based RESTful web service

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

Empowering citizens' cognition and decision making in smart sustainable cities

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Advances in Internet technologies have made it possible to gather, store, and process large quantities of data, often in real time. When considering smart and sustainable cities, this big data generates useful information and insights to citizens, service providers, and policy makers. Transforming this data into knowledge allows for empowering citizens' cognition as well as supporting decision-making routines. However, several operational and computing issues need to be taken into account: 1) efficient data description and visualization, 2) forecasting citizens behavior, and 3) supporting decision making with intelligent algorithms. This paper identifies several challenges associated with the use of data analytics in smart sustainable cities and proposes the use of hybrid simulation-optimization and machine learning algorithms as an effective approach to empower citizens' cognition and decision making in such ecosystemsPeer ReviewedPostprint (author's final draft

Service Oriented Big Data Management for Transport

International audienceThe increasing power of computer hardware and the sophistication of computer software have brought many new possibilities to information world. On one side the possibility to analyse massive data sets has brought new insight, knowledge and information. On the other, it has enabled to massively distribute computing and has opened to a new programming paradigm called Service Oriented Computing particularly well adapted to cloud computing. Applying these new technologies to the transport industry can bring new understanding to town transport infrastructures. The objective of our work is to manage and aggregate cloud services for managing big data and assist decision making for transport systems. Thus this paper presents our approach to propose a service oriented architecture for big data analytics for transport systems based on the cloud. Proposing big data management strategies for data produced by transport infra‐ structures, whilst maintaining cost effective systems deployed on the cloud, is a promising approach. We present the advancement for developing the Data acquisition service and Information extraction and cleaning service as well as the analysis for choosing a sharding strategy

The Need of Multidisciplinary Approaches and Engineering Tools for the Development and Implementation of the Smart City Paradigm

This paper is motivated by the concept that the successful, effective, and sustainable implementation of the smart city paradigm requires a close cooperation among researchers with different, complementary interests and, in most cases, a multidisciplinary approach. It first briefly discusses how such a multidisciplinary methodology, transversal to various disciplines such as architecture, computer science, civil engineering, electrical, electronic and telecommunication engineering, social science and behavioral science, etc., can be successfully employed for the development of suitable modeling tools and real solutions of such sociotechnical systems. Then, the paper presents some pilot projects accomplished by the authors within the framework of some major European Union (EU) and national research programs, also involving the Bologna municipality and some of the key players of the smart city industry. Each project, characterized by different and complementary approaches/modeling tools, is illustrated along with the relevant contextualization and the advancements with respect to the state of the art