Considering the increase of urban population and traffic congestion, smart parking is always a strategic issue to work on, not only in the research field, but also from economic interests. Thanks to information and communication technology evolution, drivers can more efficiently find satisfying parking spaces with smart parking services. The existing and ongoing works on smart parking are complicated and transdisciplinary. While deploying a smart parking system, cities, as well as urban engineers, need to spend a very long time to survey and inspect all the possibilities. Moreover, many varied works involve multiple disciplines, which are closely linked and inseparable. To give a clear overview, we introduce a smart parking ecosystem and propose a comprehensive and thoughtful classification by identifying their functionalities and problematic focuses. We go through the literature over the period of 2000–2016 on parking solutions as they were applied to smart parking development and evolution, and propose three macro-themes: information collection, system deployment, and service dissemination. In each macro-theme, we explain and synthesize the main methodologies used in the existing works and summarize their common goals and visions to solve current parking difficulties. Finally, we give our engineering insights and show some challenges and open issues. Our survey gives an exhaustive study and a prospect in a multidisciplinary approach. Besides, the main findings of the current state-of-the-art throw out recommendations for future research on smart cities and the Internet architecture.

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A Survey of Smart Parking Solutions

Future challenges for smart cities

An increased incidence of food mislabeling and handling in recent years has led to consumers demanding transparency in how food items are produced and handled. The current traceability solutions suffer from issues such as scattering of information across multiple silos and susceptibility in recording erroneous data and thus are often unable to produce reliable farm to fork stories of products. Blockchain (BC) is a promising technology that could play an important role in providing data transparency and integrity due to its salient features which include decentralisation, immutability and auditability. In this paper, we propose a permissioned blockchain framework which is governed by a consortium of key Food Supply Chain (FSC) entities including government and regulatory bodies to promote food provenance. We propose to use a sharded, three-tiered architecture which ensures availability of data to consumers, limits access to competitive partners and provides scalability for handling transaction load. We also propose a transaction vocabulary and access rights to manage read and write privileges to BC supported by the consortium. The framework, ProductChain, ensures that trade flows are kept confidential when provenance information is retrieved by consumers and stakeholders. Simulation results show that query time for a product ledger is of the order of a few milliseconds even when the information is collated from multiple shards. ProductChain is generalised and applicable to supply chains in diverse industries.

ProductChain: Scalable Blockchain Framework to Support Provenance in Supply Chains

Information and Communication Technologies (ICTs), through wireless communications and the Internet of Things (IoT) paradigm, are the enabling keys for transforming traditional cities into smart cities, since they provide the core infrastructure behind public utilities and services. However, to be effective, IoT-based services could require different technologies and network topologies, even when addressing the same urban scenario. In this paper, we highlight this aspect and present two smart city testbeds developed in Italy. The first one concerns a smart infrastructure for public lighting and relies on a heterogeneous network using the IEEE 802.15.4 short-range communication technology, whereas the second one addresses smart-building applications and is based on the LoRa low-rate, long-range communication technology. The smart lighting scenario is discussed providing the technical details and the economic benefits of a large-scale (around 3000 light poles) flexible and modular implementation of a public lighting infrastructure, while the smart-building testbed is investigated, through measurement campaigns and simulations, assessing the coverage and the performance of the LoRa technology in a real urban scenario. Results show that a proper parameter setting is needed to cover large urban areas while maintaining the airtime sufficiently low to keep packet losses at satisfactory levels.

Smart City Pilot Projects Using LoRa and IEEE802.15.4 Technologies

Smart cities (SCs) are becoming highly sophisticated ecosystems at which innovative solutions and smart services are being deployed. These ecosystems consider SCs as data production and sharing engines, setting new challenges for building effective SC architectures and novel services. The aim of this article is to “connect the pieces” among Data Science and SC domains, with a systematic literature review which identifies the core topics, services, and methods applied in SC data monitoring. The survey focuses on data harvesting and data mining processes over repeated SC data cycles. A survey protocol is followed to reach both quantitative and semantically important entities. The review results generate useful taxonomies for data scientists in the SC context, which offers clear guidelines for corresponding future works. In particular, a taxonomy is proposed for each of the main SC data entities, namely, the “D Taxonomy” for the data production, the “M Taxonomy” for data analytics methods, and the “S Taxonomy” for smart services. Each of these taxonomies clearly places entities in a classification which is beneficial for multiple stakeholders and for multiple domains in urban smartness targeting. Such indicative scenarios are outlined and conclusions are quite promising for systemizing.

A Systematic Review for Smart City Data Analytics

This paper presents a real-world proven solution for dynamic street light control and management which relies on an open and flexible Internet of Things architecture. Substantial contribution is brought at the interoperability level using novel device connection concept based on model-driven communication agents to speed up the integration of sensors and actuators to Internet of Things platforms. The paper shows also results from real-world tests with deployed dynamic street lights in urban spaces. The proposed dynamic light control solution permits an energy saving of about 56% compared to classical static, time-based street light control.

IoT-based dynamic street light control for smart cities use cases

There exists, today, a wide consensus that Internet of Things (IoT) is creating a wide range of business opportunities for various industries and sectors like Manufacturing, Healthcare, Public infrastructure management, Telecommunications and many others. On the other hand, the technological evolution of IoT facing serious challenges. The fragmentation in terms of communication protocols and data formats at device level is one of these challenges. Vendor specific application architectures, proprietary communication protocols and lack of IoT standards are some reasons behind the IoT fragmentation. In this paper we propose a software enabled framework to address the fragmentation challenge. The framework is based on flexible communication agents that are deployed on a gateway and can be adapted to various devices communicating different data formats using different communication protocol. The communication agent is automatically generated based on specifications and automatically deployed on the Gateway in order to connect the devices to a central platform where data are consolidated and exposed via REST APIs to third party services. Security and scalability aspects are also addressed in this work.

ConnectOpen - automatic integration of IoT devices

An instrument to improve the quality of life in large cities, helping to reduce the car traffic, is presented in this paper. It will result in a mobile guidance software that will help the drivers looking for a parking place to find it efficiently. SmartPark relies on available parking information systems, as well as on new sensors or even on social data inputs. A fixed magnetic on-street sensor and a video processing smart camera have been developed and prototypes of both devices were tested. Their data is available through a cloud-based Internet of Things infrastructure and continuously updated every few seconds. Databases will be built over time enabling data mining methods to infer parking availability models over time which will be used, eventually, by the algorithms feeding the mobile application.

https://www.computer.org/csdl/pds/api/csdl/proceedings/download-article/12OmNCdTeKt/pdf

Marco Aeberli

Papers

IoT-based dynamic street light control for smart cities use cases

ConnectOpen - automatic integration of IoT devices

Dynamic Street-Parking Optimisation

Dynamic Street Light Management: Towards a citizen centred approach.